Self-Study Report for Bachelor of Science in Computer Engineering at University of Washington, Study notes of Artificial Intelligence

Download Self-Study Report for Bachelor of Science in Computer Engineering at University of Washington and more Study notes Artificial Intelligence in PDF only on Docsity! 1 of 291 ABET Self-Study Report for the Bachelor of Science in Computer Engineering at University of Washington Seattle, Washington January 2019 2 of 291 Table of Contents Contents Table of Contents ............................................................................................................................ 2 BACKGROUND INFORMATION ............................................................................................... 7 A. Contact Information ............................................................................................................... 7 B. Program History ..................................................................................................................... 7 C. Options ................................................................................................................................... 8 D. Program Delivery Modes ....................................................................................................... 8 E. Program Locations.................................................................................................................. 9 F. Public Disclosures ................................................................................................................ 10 G. Deficiencies, Weaknesses or Concerns from Previous Evaluation(s) and the Actions Taken to Address Them ....................................................................................................................... 10 CRITERION 1. STUDENTS ....................................................................................................... 11 A. Student Admissions.............................................................................................................. 11 B. Evaluating Student Performance .......................................................................................... 13 C. Transfer Students and Transfer Courses .............................................................................. 14 C.1 Acceptance of Transfer Students .................................................................................... 14 C.2 Evaluation of Transfer Credit ......................................................................................... 15 D. Advising and Career Guidance ............................................................................................ 15 D.1 Advising ......................................................................................................................... 15 D.2 Career Guidance ............................................................................................................. 16 E. Work in Lieu of Courses ...................................................................................................... 17 F. Graduation Requirements ..................................................................................................... 18 G. Transcripts of Recent Students ............................................................................................ 18 CRITERION 2. PROGRAM EDUCATIONAL OBJECTIVES ................................................. 19 A. Mission Statement ................................................................................................................ 19 Mission Statement—UW ...................................................................................................... 19 B. Program Educational Objectives .......................................................................................... 19 C. Consistency of the Program Educational Objectives with the Mission of the Institution.... 20 D. Program Constituencies ....................................................................................................... 20 E. Process for Revision of the Program Educational Objectives .............................................. 20 CRITERION 3. STUDENT OUTCOMES .................................................................................. 22 A. Student Outcomes ................................................................................................................ 22 B. Relationship of Student Outcomes to Program Educational Objectives .............................. 22 CRITERION 4. CONTINUOUS IMPROVEMENT ................................................................... 24 A. Student Outcomes ............................................................................................................... 24 A.1 Data Sources................................................................................................................... 24 Table 4-1 Information sources for assessment................................................................... 24 Table 4-2 Assessment procedures for student outcomes ................................................... 25 A.2 Assessment Process Overview ....................................................................................... 26 Figure 4-1 Summary of Department Assessment and Improvement Processes ................ 27 A.3 Targeted Assessment of Outcomes in Courses .............................................................. 29 A.4 Additional Assessment Processes .................................................................................. 34 5 of 291 CSE 461 Introduction to Computer-Communication Networks ...................................... 161 CSE 469 Computer Architecture I ................................................................................... 163 CSE 470 / EE 470 Computer Architecture II................................................................... 165 CSE 474 Introduction to Embedded Systems .................................................................. 167 CSE 475 Embedded Systems Capstone ........................................................................... 169 CSE 481A Capstone Software Design: Operating Systems ............................................ 172 CSE 481C Capstone Software Design: Robotics............................................................. 174 CSE 481N NLP ................................................................................................................ 176 CSE 481S Security ........................................................................................................... 178 CSE 481V AR/VR ........................................................................................................... 180 Appendix B – Faculty Vitae ................................................................................................... 182 Anderson, Richard .............................................................................................................. 182 Anderson, Ruth E. ............................................................................................................... 184 Anderson, Thomas E. .......................................................................................................... 186 Balazinska , Magdalena ...................................................................................................... 191 Beame, Paul ........................................................................................................................ 193 Bricker, Lauren ................................................................................................................... 195 Ceze, Luis............................................................................................................................ 198 Choi, Yejin .......................................................................................................................... 200 Curless, Brian L. ................................................................................................................. 204 Domingos, Pedro ................................................................................................................. 206 Farhadi, Ali ......................................................................................................................... 208 Fogarty, James .................................................................................................................... 210 Fox, Dieter .......................................................................................................................... 213 Froehlich, Jon E. ................................................................................................................. 215 Gollakota, Shyamnath ......................................................................................................... 217 Grossman, Dan .................................................................................................................... 218 Heimerl, Kurtis.................................................................................................................... 222 Hemingway, Bruce.............................................................................................................. 224 Jamieson, Kevin .................................................................................................................. 225 Karlin, Anna R .................................................................................................................... 226 Krishnamurthy, Arvind ....................................................................................................... 228 Kemelmacher-Shlizerman, Ira (Irena) ................................................................................ 230 Kohno, Tadayoshi ............................................................................................................... 232 Lin, Huijia (Rachel) ............................................................................................................ 233 Lee, James R. ...................................................................................................................... 235 Mones, Barbara ................................................................................................................... 239 Oskin, Mark ........................................................................................................................ 240 Patel, Shwetak N. ................................................................................................................ 242 Perkins, Hal ......................................................................................................................... 244 Rao , Anup .......................................................................................................................... 245 Reges, Stuart ....................................................................................................................... 246 Reinecke, Katharina ............................................................................................................ 248 Roesner, Franziska .............................................................................................................. 250 Ruzzo, Walter L. ................................................................................................................. 253 6 of 291 Schafer, Hunter ................................................................................................................... 256 Seelig, Georg ....................................................................................................................... 257 Seitz, Steve .......................................................................................................................... 259 Shapiro, Linda G. ................................................................................................................ 261 Smith, Joshua R................................................................................................................... 263 Suciu, Dan ........................................................................................................................... 265 Tanimoto, Steven L. ............................................................................................................ 267 Tatlock, Zachary ................................................................................................................. 269 Taylor, Michael Bedford ..................................................................................................... 272 Tompa, Martin .................................................................................................................... 274 Wang, Xi ............................................................................................................................. 275 Weld, Daniel S. ................................................................................................................... 277 Zahorjan, John ..................................................................................................................... 281 Appendix C – Equipment........................................................................................................ 283 Appendix D – Institutional Summary ..................................................................................... 285 1. The Institution ............................................................................................................... 285 2. Type of Control ............................................................................................................. 285 3. Educational Unit ........................................................................................................... 285 4. Academic Support Units ............................................................................................... 287 5. Non-academic Support Units ........................................................................................ 287 6. Credit Unit..................................................................................................................... 288 7. Tables ............................................................................................................................ 288 Table D-1. Program Enrollment and Degree Data.......................................................... 288 Table D-2. Personnel ...................................................................................................... 290 Submission Attesting to Compliance ...................................................................................... 291 7 of 291 BACKGROUND INFORMATION A. Contact Information List name, mailing address, telephone number, fax number, and e-mail address for the primary pre-visit contact person for the program. Professor Arvind Krishnamurthy Paul G. Allen School of Computer Science & Engineering Box 352350 University of Washington Seattle WA 98195-2350 Email: arvind@cs.washington.edu Phone: (206) 616-0957 B. Program History Include the year implemented and the date of the last general review. Summarize major program changes with an emphasis on changes occurring since the last general review. The University of Washington’s Department of Computer Science & Engineering began as an inter-college graduate program in 1967. In 1975 a bachelor’s degree program in Computer Science was initiated, targeted to graduate 40 students per year. Departmental status was conferred, and the department was placed under the College of Arts & Sciences. In 1989 the department moved to the College of Engineering, changed its name to the Department of Computer Science & Engineering, and initiated a second bachelors degree program -- an ABET- accredited Bachelor of Science in Computer Engineering degree targeted to graduate 40 students per year. In 1999 the department expanded its bachelors program in Computer Engineering to 80 graduates per year (160 total bachelors graduates per year, equally divided between Computer Science and Computer Engineering). In 2012, we increased total program enrollment to 200 students per year. In 2013 we expanded again up to 250 bachelor’s degrees. In 2015 we grew to 345 degrees, and in 2017 to 370. In 2017 - our 50th anniversary year - the University of Washington Board of Regents voted to create the Paul G. Allen School of Computer Science & Engineering, elevating the status of CSE within the university and linking us in perpetuity with the internationally renowned investor, philanthropist and computing pioneer. CSE currently has roughly 70 faculty, 70 technical and administrative staff members, 500 graduate students (350 in the full-time program and 150 in the Professional Master’s Program), and 1,300 undergraduate students. We will soon award more than 450 bachelor’s degrees per year of which about 90 will be Computer Engineering. As of 2019, the School continues to offer a Bachelor of Science in Computer Engineering degree through the College of Engineering and a Bachelor of Science in Computer Science through the College of Arts & Sciences. While in the past we did not set quotas between Computer Science and Computer Engineering, we now have a target of maintaining approximately 20% of our degrees for Computer Engineering. Although our students are differentiated by the degree program they choose, they are otherwise treated very similarly with 10 of 291 F. Public Disclosures Provide information concerning all the places where the Program Education Objectives (PEOs), Student Outcomes (SOs), annual student enrollment and graduation data is posted or made accessible to the public. If this information is posted to the Web, please provide the URLs. Program URL: https://www.cs.washington.edu/ABET. G. Deficiencies, Weaknesses or Concerns from Previous Evaluation(s) and the Actions Taken to Address Them Summarize the Deficiencies, Weaknesses, or Concerns remaining from the most recent ABET Final Statement. Describe the actions taken to address them, including effective dates of actions, if applicable. If this is an initial accreditation, it should be so indicated. The only concern expressed from our ABET 2013 review was that students might be able to graduate without completing the required 45 credits of math and science and 67.5 Engineering units. There was concern that as changes were made to the program, students could fail to meet these requirements. To address this possibility, we have now added an explicit component to the degree that requires all students to complete additional engineering courses. This is checked automatically by the university's Degree Audit Reporting System (DARS). 11 of 291 GENERAL CRITERIA CRITERION 1. STUDENTS A. Student Admissions Summarize the requirements and process for accepting new students into the program. Until Fall 2018, UW students generally applied to majors at the end of their sophomore year – a situation encouraged by Washington state’s higher education policy that anticipates a large number of transfers from our two-year community colleges. Unusually, our department was also admitting roughly 20% of our students through freshman Direct Admission. Direct Admission was a better experience for the students as they could start off as Computer Engineers from day one without waiting one or two years uncertain if they would eventually be admitted. While we’ve expanded this program for our Computer Science degree, for our Computer Engineering students, we have transitioned to a new, college-wide Direct to College (DTC) freshman pathway. This past year, Engineering programs adopted a policy of admitting up to 50% of future graduating classes directly as freshman as part of DTC. These students enter the College on admission to the University. They are then placed into Engineering programs between the end of their freshman year and the middle of their sophomore years. This change in admissions has a very positive impact on degree programs; with the additional certainty and time in the major this program affords students, they can better plan their major requirements and are more likely to consider and undertake research and cooperative education experiences that enhance their education. We still admit roughly 34% of our students from the current UW student body. These are generally students who came to UW intending to study other majors but are excited by Engineering and apply to our program after finishing a series of prerequisite courses. We also admit about 16% of our students directly as transfer students from other colleges, primarily Washington state’s two-year schools. Finally, we also take small number of students through the College of Engineering STARS program: STARS is a two-year program with a specialized curriculum designed to build learning skills and strengthen academic preparation for core math and science prerequisites. STARS scholars are guaranteed placement into an engineering or computer science major. Our Undergraduate Advising Office coordinates the departmental undergraduate admissions effort. Admission to the department is highly competitive. As mentioned above, there are four paths into the major (Direct to College placement, STARS students, current UW student admission, and transfer student admission). All paths except STARS, use the same criteria for admission: grades in prior courses, especially in math, science and engineering, a written personal statement, and potential to contribute to the field of computing. In the pathway for current UW students, students apply to the program after completing a set of program prerequisites. Prerequisite courses include one year of calculus (Math 124, 125, 126 or the honors series 134, 135, 136), two quarters of programming (CSE 142 and 143), 5 credits of science (Physics 121) and 5 credits of English Composition. Our Admissions Committee is comprised of faculty members and undergraduate advisors. 12 of 291 All admissions forms are online and students can complete the process remotely. Once the online application is completed, students receive email confirmation of their submitted application. They receive admission notifications about three weeks after the application deadline. There are two standard admissions cycles per year, with deadlines of July 1 for Autumn and January 15th for Spring. Our School is very active in recruiting the best students to our program. We host information sessions several times each quarter during the academic year in order to introduce prospective students to our department. We also present at several targeted sessions across campus for students in the Robinson School Early Entrance program, Honors program, and various other diverse organizations. In addition to general recruitment, we are actively trying to increase diversity by more broadly attracting applicants through different mechanisms. Our efforts supporting diversity and inclusion have expanded greatly over the past few years, with new activities, better engagement from Allen School students and faculty, and more attention to supporting underrepresented minority and low-income students (along with continued programming for women in computing). Comprehensive lists of ongoing and recent work can be found at: • https://www.cs.washington.edu/diversity/ongoing-activities • https://www.cs.washington.edu/diversity/latest-initiatives Current efforts include: • We expanded our K-12 outreach. A team of paid student Ambassadors (majority underrepresented) reaches more than 1,500 K-12 students annually through workshops, schools visits, and tours. Summer camps host 200+ students, half girls, with scholarships available for low-income students. We now participate in UW pre-college programs such as the College of Engineering Math Academy and initiatives though the Office of Minority Affairs & Diversity. And we continue to lead teacher workshops and participate in an annual NCWIT Award for Aspirations in computing. • We instituted a holistic admissions process utilizing non-academic factors to promote diversity. • New academic support courses for Intro Programming to serve low-income engineering and computer science students in the College of Engineering STARS program. https://www.engr.washington.edu/stars • A new seminar for our diverse population of transfer students provides community, academic advice, and connection to resources. • A new one-month summer class for incoming freshmen from underrepresented backgrounds has served 70 students: half women, plus URM students, low-income students, and students with disabilities. The course teachers CS skills along with basic college preparation and community development. https://www.cs.washington.edu/students/ugrad/directadmission/startup 15 of 291 Community college course work generally covers only our introductory programming courses (CSE 142 and 143), calculus, science, and English Composition. Most other transfer credits are from four-year institutions – usually out-of-state. Courses in engineering that come from an EAC/ABET accredited program are usually accepted readily. Other courses, including from international institutions, are considered with great care. If the courses completed are on our list of pre-approved transfer courses (primarily, from the state’s community colleges) then credit is granted immediately. Otherwise, the student is asked to go through the petition process described below in the Evaluation of Transfer Credit section. The possible outcomes are transfer credit is granted, denied (and the student must take the course in our department for credit), or granted under the condition that the student makes up for some gaps in material. The overwhelming majority of our transfer credits are from Washington State Community Colleges with which we have course articulation agreements. C.2 Evaluation of Transfer Credit Transfer credit is accepted subject to the evaluation of each course. The UW provides a centralized evaluation process that we use for non-computing courses. For each course in the major, a petition is submitted online that includes copies of a syllabus, homework assignments, exams, etc. There are faculty leads for every course who review the petitions and accompanying documents and make the final determinations on whether transfer credit should be granted. The courses that most often fall into this category are our introductory programming courses. The department has a program for the state’s community colleges to have their courses pre-approved. D. Advising and Career Guidance Summarize the process for advising and providing career guidance to students. Include information on how often students are advised, who provides the advising (program faculty, departmental, college or university advisor). D.1 Advising We have an Undergraduate Advising Office with eight full-time professional staff members: Crystal Eney, Director of Student Services; Raven Avery, Assistant Director of Diversity and Outreach; Jenifer Hiigli, Lead Academic Adviser; Maggie Ryan, Senior Academic Adviser; Chole Dolese, Senior Academic Adviser; Leslie Ikeda, Academic Adviser; and Kim Nguyen, Career Advising Specialist. We also have a Course Coordinator (Pim Lustig) and an Outreach Assistant (Jeremy Munroe). The Faculty Undergraduate Program Coordinator (Arvind Krishnamurthy) supervises the overall advising effort. Our departmental advising office provides both pre-major advising for prospective students and advising and curriculum planning for current majors. The CE program is well documented and can be found online at: • For current students: https://www.cs.washington.edu/academics/ugrad, which summarizes in detail the program requirements and advising process. • For prospective students, https://www.cs.washington.edu/academics/ugrad/admissions, which serves both an educational role (“Why Choose CSE?”) and provides information on how to prepare for and apply to the major. The undergraduate advising team also manages the 5th year master’s (Combined BS/MS) program. There is a separate Graduate Advising Office supervised by another faculty coordinator for our other two graduate programs. 16 of 291 The CSE Advising Office serves both Computer Engineering and Computer Science majors. All advisors are knowledgeable about both degree programs and can advise any CSE student. The program information for the two majors is closely coordinated to take advantage of the commonality of the two degrees. Visits to advising are optional, but the majority of our students (over 70% of all CE majors) visit advising every year. In the 2019-2020 academic year we will be initiating a primary adviser model where one adviser will be responsible for tracking a smaller group of students. This will further ensure that all students have an additional layer of support. D.2 Career Guidance Since our last ABET review in 2013, we have significantly grown our career guidance resources. Most importantly, this past year we hired Kim Nguyen to our advising team as a Career Advising Specialist. Kim is an alumna of UW who earned Computer Engineering and Electrical Engineering degrees and then worked at Microsoft as a program manager and finally as a company recruiter. She has ramped up the career guidance and preparation services we provide our students. In addition to now being able to provide one-on-one counseling appointments, we offer group presentations and small group activities to get students prepared for industry. This fall (2019), we are introducing a 1 credit seminar on “everything you need to know on how to land a job in the software industry”. Over the last couple of years, our students had expressed a desire for stronger career preparation through various feedback channels like surveys, lunch with the director, and the like. Kim has led our response. Below we document the career events that are now available: Employer Panel (Fall Quarter) The Employer Panel is the first CSE recruiting preparation event of the year. The panel consists of four employer representatives: one recent grad/engineer, one large company HR rep, one small company HR rep, and one hiring manager. The purpose of the panel is to inform students about the recruiting process from the presenters’ perspectives. To accomplish this, recent grads discuss their own job search, hiring managers discuss what they look for in candidates, and HR reps discuss how recruiting works within their companies. While the represented companies certainly provide some level of self-promotion, their focus is on providing a peek inside the recruiting process so the students will know how to best prepare. This year’s panelists were from Google, Indeed, Code.org, and Salesforce. Internship Panel (Winter Quarter) The internship panel helps students interested in internships. The panel consists of recent CSE grads from companies such as Amazon, Zillow, Google and Microsoft. The panelists provide advice on how to secure the best-fitting internships, how to prepare for those internships, and what to expect during the internship. Additional focus is on guiding students to make the best early decisions to pave the way for a successful transition into full-time employment in the future. Resume Review Workshop (Fall and Winter Quarters) In this workshop, HR reps and recruiters (or other people within companies who screen résumés or serve as the first or second-line reviewers) sit with small groups of CSE students for 15-20 minutes to critique resumes, offer suggestions, and help them refine the way they 17 of 291 present themselves on paper. It is a chance for students to get honest feedback about what is working, what is not, and to see examples from other students to help them craft a polished and effective résumé Mock Technical Interviews (Fall and Winter Quarters) Mock technical interviews afford students the opportunity to participate in a one-on-one simulated interview. Engineers, hiring managers, and other technical employees from local software companies conduct the technical interviews. The interviews consist of whiteboard questions, problem solving puzzles, and coding questions. Interviews last 30 minutes, with an additional 10 minutes allotted for interviewers to give the students open feedback on how they did and what they can do to improve their technical interview performance. Technical Interview Coaching (Fall and Winter Quarters) This event is designed for CSE undergrads who will be interviewing for a full-time or internship position in the coming year. It is a preview of the types of technical interview questions they will likely encounter. Recruiting 101 (Fall, Winter and Spring Quarters) This presentation covers introductory information about what students can expect and how they should prepare for their internship or job hunt. Topics covered include an organized strategy to approaching the job search, how to effectively use time at the career fair, basics of a resume, how to correspond with recruiters, recruiting timelines, and what to expect in a technical interview. Negotiating Your First Job Offer (Fall, Winter and Spring Quarters) This presentation covers basic strategies students can use to negotiate full-time offers. We cover how to evaluate the monetary aspects of a job offer, including stock, stock options, relocation, salary, sign-on bonuses, yearly bonuses, and health benefits. Discussion of more qualitative aspects of an offer, like location, job content, career trajectory, and work/life balance, helps students understand how to holistically evaluate their options. Current industry trends for compensation and benefits are discussed so that proper expectations can be set. Several scenarios are walked through to show examples of how to navigate various negotiation situations. E. Work in Lieu of Courses Summarize the requirements and process for awarding credit for work in lieu of courses. This could include such things as life experience, Advanced Placement, dual enrollment, test out, military experience, etc. Except for a limited number of co-op credits (ENGR 321 and CSE 301), the University of Washington does not award course credit for work. A student with significant outside experience may be allowed to test out of a course by interviewing with the faculty lead in charge of that course. The student would then use a higher level course to satisfy the credits. 20 of 291 Economic Impact: Our graduates will enhance the economic well-being of Washington State through a combination of technical expertise, leadership and entrepreneurship. Lifelong Learning: Our graduates will adapt to new technologies, tools and methodologies to remain at the leading edge of computer engineering practice with the ability to respond to the challenges of a changing environment. C. Consistency of the Program Educational Objectives with the Mission of the Institution Describe how the program educational objectives are consistent with the mission of the institution. The departmental program objectives are completely consistent with those of the University of Washington. The key sentence of the University of Washington’s mission statement (http://www.washington.edu/admin/rules/policies/BRG/RP5.html) is “The primary mission of the University of Washington is the preservation, advancement, and dissemination of knowledge.” These correspond to our engineering quality, leadership and economic impact, and lifelong learning objectives. Our program objectives address both the education and impact aspects of that goal. D. Program Constituencies List the program constituencies. Describe how the program educational objectives meet the needs of these constituencies. Our primary responsibility as part of the University is education. Our most important constituents are: • Computer Engineering students • CSE faculty For students, our educational objectives enable them to use computer engineering as they lead impactful, meaningful lives and successful careers. For faculty, our educational objectives are an essential motivation for pursuing academic careers. Our strong and successful students and alumni help recruit, retain, and motivate our world-class faculty. E. Process for Revision of the Program Educational Objectives Describe the process that periodically reviews the program educational objectives including how the program’s various constituencies are involved in this process. Describe how this process is systematically utilized to ensure that the program’s educational objectives remain consistent with the institutional mission, the program constituents’ needs and these Criteria. 21 of 291 Our Program Educational Objectives have remained stable and have withstood the test of time, so reviews are typically brief. However, we do have several processes in place to ensure periodic review. First, any substantial curriculum change is considered in light of our program educational objectives. As described later in this report, our substantial revision and alignment with Electrical Engineering courses in 2015 was performed in this context. At that time, the department’s Executive Committee reviewed our program educational objectives and did not change them. Second, any change to the institutional mission causes us to revisit our own mission as we are an integral part of the University of Washington. As discussed above, our objectives are fully aligned with UW’s mission. Third, in Fall 2017, our students initiated a conversation with our advising staff about creating a Student Advisory Council (https://sac.cs.washington.edu/). This advisory council has both elected and appointed members who represent a diverse set of interests among the undergraduate population. The council’s main objective is to improve the overall experience of undergraduates in the Allen School. The council hosts presentations in addition to gathering feedback to pass on to the Allen School administrative units. This group has been a huge asset as we continue to work on improving our program. The inherent turn-over among student leadership on an annual basis provides a natural opportunity to review our program educational objectives with this constituency. Finally, we seek validation for our objectives from outside our constituencies, primarily through employers of our graduates and our alumni. The fact that we are one of the top suppliers in the nation to Amazon, Microsoft, Google, and Facebook, as well as being the predominate supplier to small and mid-size companies in the Puget Sound region, means that program leadership is in close touch with recruiting managers and engineers at these companies, providing a tight feedback loop. A full-time external relations director provides a formal connection to over 100 companies in our Industrial Affiliates program. 22 of 291 CRITERION 3. STUDENT OUTCOMES A. Student Outcomes List the student outcomes and state where they may be found by the general public as required by APPM Section I.A.6.a. If the student outcomes used by the program are stated differently than those listed in Criterion 3, provide a mapping of the program’s student outcomes to the student outcomes (1) through (7) listed in Criterion 3. Our mission statement, program objectives, and student outcomes are all publicly available at http://www.cs.washington.edu/ABET/. Our student outcomes comprise the set of skills and abilities that our curriculum is intended to give our students so they can meet the educational objectives we have set for them: 1. an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics 2. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors 3. an ability to communicate effectively with a range of audiences 4. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts 5. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives 6. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgement to draw conclusions 7. an ability to acquire and apply new knowledge as needed, using appropriate learning strategies. B. Relationship of Student Outcomes to Program Educational Objectives Describe how the student outcomes prepare graduates to attain the program educational objectives. We have four broad program educational objectives. We examine each in turn and indicate which student outcomes are the most directly relevant to achieving the program objectives. Engineering Quality: Our graduates will engage in the productive practice of computer engineering to identify and solve significant problems across a broad range of application areas. All our student outcomes contribute to this objective, so we do not enumerate them here. 25 of 291 Assessment Process Description Frequency Where Maintained Targeted Course Work Individual assignments and exams, or portions of assignments or exams, may be targeted to assess particular outcomes. Regularly UW Office of Educational Assessment and CSE Chair’s Office Capstone Courses Capstones are showcases for many student outcomes. Regularly CSE Instructors; Dept. Videos Per-Course Instructor Hand-Off Documents Many of our courses, particularly at the 300-level, have multiple instructors each year, who regularly hand-off materials and “to do” lists Yearly Varies by course due to differences in infrastructure and tooling. Full Faculty Approvals All curriculum changes (requirements, pre-requisites) are approved by the full faculty, usually via unanimous consent after any helpful discussion As needed Emails to faculty mailing list Curriculum Committee Department level examination of multi- course portions of the curriculum. Approves all curricular changes (e.g., requirements, pre-requisites) before seeking full faculty approval Weekly Google Drive for the Committee Special Case Reviews In 2018-2019, a committee of senior faculty reviewed our 100-level course offerings and their relationship to admissions and the major, producing a substantial report with over 30 recommendations Various Final report issued in May 2019 to the CSE administration, curriculum committees, relevant faculty, and other campus stakeholders Student Advisory Council A student led council that plans presentations for students and gathers feedback from students. Quarterly SAC student organization and reports are maintained by the student org Ugrad Lunch with the Director Open meeting with the Director to hear about the School news and ask questions Quarterly Advising Notes in Team Drive Climate Study Survey of all CSE majors and pre majors Annually Advising and Admin Files Anonymous Feedback A portal for current students to give feedback anonymously to the advising staff Various Advising notes in Team Drive Table 4-2 Assessment procedures for student outcomes Student Outcome Primary Data Sources Significant Additional Sources 1. an ability to identify, formulate, and solve complex engineering problems by applying Regular Course Work Targeted Course Work Capstones Alumni survey Employer feedback 26 of 291 Student Outcome Primary Data Sources Significant Additional Sources principles of engineering, science, and mathematics Per-Course Instructor Hand-Off Documents Instructor Reflections 2. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors Targeted Course Work Capstones Employer feedback Instructor Reflections 3. an ability to communicate effectively with a range of audiences Targeted Course Work Capstones Employer feedback Alumni survey 4. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts Targeted Course Work Capstones Employer feedback Exit Surveys 5. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives Targeted Course Work Capstones Alumni survey Climate Studies 6. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgement to draw conclusions Targeted Course Work Capstones Alumni survey 7. an ability to acquire and apply new knowledge as needed, using appropriate learning strategies. Targeted Course Work Capstones Employer feedback Alumni survey A.2 Assessment Process Overview The frequency with which these assessment processes are carried out Figure 4-1 gives a high level overview of our assessment and evaluation procedures. Here we provide a more global view of how these pieces interact with clear feedback loops that guide how we engage with the data and use it to drive continuous improvement. The flow-chart below also includes two items not covered by the sources in Table 4-1: 1. External Advisory Committee: Every UW program must undergo a review every ten years in which an external committee reviews all aspects, including curricular goals and outcomes. Beyond that, we had maintained a standing advisory committee, but in the last few years have experimented with replacing that static body with a set of external focus groups (alumni, employers, senior technology leaders, etc.). A set of groups held meetings in 2014-2015 and notes were taken by School leaders. While useful at the time, we concluded the effort was burdensome and ad hoc, so we plan to create a new external advisory committee (returning to the old model) in the coming year. 27 of 291 2. Student course evaluations, managed by the standard UW processes, provide quantitative and qualitative information on each course. Per UW rules, quantitative results are shared with both instructors and School leadership, but qualitative results are shared only with instructors, who can (and do) use them to inform their self-reflections and instructor hand-offs, as described in Table 4-1. Figure 4-1 Summary of Department Assessment and Improvement Processes There are two primary feedback loops in our process, one best suited to quickly refining individual courses and our program, and another suited to making improvements that cut across courses. The large feedback loop evaluates the program as a whole from the standpoint of our objectives and how well our curriculum prepares students to achieve these objectives. This loop uses feedback from current students, graduating students, alumni and our industrial affiliates. We used to ask an outside group, the Center for Instructional Development and Research (CIDR), to interview our graduating students. Their office has recently lost a number of employees, so at this point in time we are handling these evaluations internally. Additionally, we run an exit survey that includes both qualitative and quantitative assessments of our program by our graduating students, as well as alumni surveys soliciting feedback from our students after they have experience in the workplace or graduate school. Finally, we get feedback from our 30 of 291 1. an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics 2. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors 31 of 291 3. an ability to communicate effectively with a range of audiences 4. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts 32 of 291 5. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives 6. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgement to draw conclusions 35 of 291 10. Knowledge of contemporary issues 11. Ability to use the techniques, skills, and modern computer engineering tools necessary for engineering practice 12. Ability to think critically 13. Ability to manage change 14. Understanding of office dynamics Figure [4-1] shows average survey results for co-ops that took place between Autumn 2017 and Summer 2018. Figure [4-2] shows average survey results for co-ops that took place between Autumn 2018 and Winter 2019 (note that we did not have any CE students participate in a co-op during Spring of 2019 and Summer 2019 data is not available as of the submission of this report). Both of these graphs show similar trends. The first observation is that students do perceive an improvement in each of their surveyed categories upon the completion of their internship (varying from incremental to significant improvement). The second observation is except on two occasions, employers perceive students to be performing as well as, or better, than students perceive themselves to be performing upon completion of their internship. Figure 4-1 Co-Op Evaluation Data 2017-2018 36 of 291 Figure 4-2 Co-Op Evaluation Data 2018-2019 In addition to the quantitative data just shown, we also make use of the free form comments made by employers. We cite here some typical examples the 2017-2019 surveys, selected because they reflect directly on our four program educational objectives, as listed in Section 2.B. Engineering Quality They surprise me by their ability to judge things, identify compromises and make decision. They are definitely not a typical intern and demonstrate an unexpected level of maturity for somebody relatively new at computer sciences On quality of work: Notable for a solid transfer of knowledge at the end of internship to remaining team. They were able to work on the full project phases from design to implementation to testing. Even though they were unfamiliar with either development environment, they wrote code that followed best practices in those areas. They sometimes reworked code after feedback. Leadership I have witnessed them helping others on numerous occasions. Everybody likes working with them. They worked independently and sought help from subject matter experts when it was needed. They, along with the other interns, had great working relationships. They, along with the other interns, designed a spirit contest aiming to boost camaraderie. 37 of 291 They always do what they say they are going to do, despite the fact that our environment is pretty challenging with high priority disrupting tasks almost every day. Economic Impact They completed projects for us that will help us do integration testing, and a service that allows us to do feature toggles and A/B testing. They worked well with the team. Required minimal supervision. Knew when to ask questions, which is very important. Produced tools that the team will use for a long time after he is gone. Very satisfying outcome all around. Lifelong Learning Not only are they always interested in expanding their scope and learning new things, they are also particularly good at switching with minimal ramp up time. They were a very independent learner and did not need any remedial instruction. A.4.3 End-of-program interviews From 2005 through 2015, we asked staff from the UW Center for Instructional Development and Research (CIDR) to interview our soon-to-be-graduating students. Current students were surveyed by staff from the Center for Instruction Research, either through live group interviews or by web-based surveys, near the end of the program. Based on their experience with the two, CIDR reports different advantages to each, but felt that the online surveys gave a more accurate picture of student sentiment since it eliminated social pressure that might arise to agree with the majority in a group meeting. The questions CIDR asked (and that we now ask in our alumni survey) focus on the extent to which the students feel they have successfully met the student outcomes we set. Students are asked how well they think the department has helped them achieve each of our outcomes (1-7) (Section 3.A). Students rank the contribution on a scale of 0 to 5. The student responses for the most recent two years are shown below in Figure 4-3. 40 of 291 Figure 4-5 Graduate Exit Survey Destination Data for Undergraduates (2019) The CSE survey asks for broader feedback on students’ general satisfaction with the experiences and courses provided in CSE. Student comments are collated by the Director of Student Servies and reported to the Undergraduate Program Coordinator and the Allen School Director. We use the departmental exit survey as one of many tools to proactively detect problems with our program. Comments on the department are almost uniformly positive. Students are happiest with the quality of their education, the faculty and advising. Some students expressed that the wait on email responses was a bit longer than hoped for during peak times. Students also asked for more courses on cloud computing, parallel computing and computational biology. A.4.5 Student course evaluations During course evaluations, students rate detailed aspects of the course and also give an overall score. These scores are one mechanism we use to monitor the quality of course delivery. While student happiness with a class is not a foolproof indicator of its quality, we have found a high correlation between the two. Figure 4-6 Core Course Student Evaluations (2016-2019) 0 1 2 3 4 5 6 CSE 142 CSE 143 CSE 311 CSE 312 CSE 332 CSE 351 CSE 369 CSE 403 CSE 474 CSE 484 Core Course Student Evaluations 2016 2017 2018 2019 41 of 291 Figure 4-7 Capstone Course Student Evaluations (2016-2019) Student rankings are on a five point scale, but because the university applies a normalization function that takes into account the size, difficulty, and workload of a course, “adjusted” scores can be somewhat higher than five. Figures 4-6 and 4-7 show the adjusted student ratings for each offering of each core course and each capstone course. The x-axis has the average adjusted mean score for all offerings of a course in a particular year, and the y-axis is the adjusted mean overall score for that offering. The results are generally quite good. Courses that warrant monitoring are typically ones taught infrequently and by only one or two faculty members, a combination that can sometimes make updating a course more of a struggle then it would be in the typical case. A.4.6 Student Anonymous Feedback In 2015, we built an anonymous-feedback tool to allow students in any of our courses to provide feedback to their instructor anonymously. In 2018, we extended this tool in two directions: to allow students to also direct their feedback to Allen School academic leadership and/or the Director of Student Services, and to allow TAs to use the tool for the course they are TAing. Despite advertising these new feedback channels, so far these extensions have seen only modest use – a handful of messages with a couple complaining about grading or instructor interactions and a couple raving about excellent faculty. We need to continue publicizing this feedback channel, but its modest use is probably a good sign in and of itself. 0 1 2 3 4 5 6 CSE 428 CSE 441 CSE 460 CSE 475 CSE 481a CSE 481c CSE 481n CSE 481s CSE 481v Capstone Course Student Evaluations 2016 2017 2018 2019 42 of 291 A.4.7 TA Review In 2018, we also rolled out two new review mechanisms related to Teaching Assistants, an evaluation of TAs by instructors and a lightweight survey for TAs to provide feedback about our courses. Both mechanisms have results reviewed by Allen School leadership and fed back to instructors to guide continuous improvement. Both review mechanisms have had extremely positive results: Instructors indicate our TAs are excellent and TAs indicate the courses and their TAing experience are excellent. A.4.8 Faculty self-evaluations Our full-time faculty, both tenure-track and teaching (lecturers), go through a merit-review process annually. For junior faculty, there is a much more rigorous annual review process in which faculty members prepare self-assessment materials, a faculty committee reviews them and generates a report, and faculty of more-senior ranks discuss and identify feedback delivered via the Director. Course instruction is a key part of this review, considering not only student evaluations, but curricular innovations, the faculty member’s self-reflection, and peer classroom observations. Many of our faculty also regularly utilize the College of Engineering’s Center for Teaching and Learning, which has a well-honed procedure for visiting classrooms during terms to receive feedback from students, producing quantitative and qualitative reports that are shared back with the faculty member. A.4.9 Capstone design projects The capstone courses are the centerpiece of our program and are key to providing and assessing student outcomes. In a capstone course, students work in teams to design and implement a substantial project comprising multiple components. As part of their project, they produce project reports and make class presentations where they present their design, describe the design choices they made, and the tradeoffs they considered. At the end of the course, the project teams demonstrate their projects to their peers, and, in many cases, to members of affiliate companies, to the department as a whole, and to the public. Many outcomes are integral to the student’s success in the capstone course, from the mastery and application of fundamental concepts in mathematics, science and computer engineering, to evaluating design tradeoffs and making effective design decisions, to working effectively as part of a team, to self-learning of new concepts and tools, to understanding the impact of computer engineering on society, to effective oral and written communication. The project reports, demonstrations, and presentations provide the instructor a direct mechanism to assess whether students have met outcomes 1 through 7. It is common for final project demonstrations to be open to the public. We also capture many projects from our capstone projects in video productions that highlight the projects as well as the design process and tools the students used in the class. This allows our outside constituencies, particularly our industrial affiliates, to assess the quality and scale of these capstone projects. Some of these videos are available online at https://www.youtube.com/user/UWCSE/videos. 45 of 291 faculty size and the consequent increase in diversity of areas of faculty interest. Table 4-6 presents summaries of these changes. Table 4-6 Courses Introduced Since 2013 Course Title Pre-majors Courses CSE 160 Data Programming CSE 163 Intermediate Data Programming CSE 180 Introduction to Data Science Non-core Majors Courses CSE 190a Direct Admission Seminar CSE 340 Interaction Programming CSE 390t Transfer Seminar CSE 369* Introduction to Digital Design CSE 371* Design of Digital Circuits and Systems CSE 402 Design and Implementation of Domain-Specific Languages CSE 442 Introduction to Data Visualization CSE 447 Natural Language Processing CSE 469* Computer Architecture I CSE 470* Computer Architecture II CSE 478 Autonomous Robots CSE 490 Deep Learning (permanent number pending) CSE 490 Cryptography (first offering Fall 2019, permanent number pending) CSE 490 Tech for the developing world (offered Fall 2018, permanent number pending) Capstone Design Courses CSE 481a Operating systems Capstone CSE 481g Distributed Systems Capstone CSE 481s Security Capstone CSE 481c Robotics Capstone CSE 481v Virtual Reality Capstone CSE 481n Natural Language Processing Capstone CSE 482 Capstone Software Design to Empower Underserved Populations * Courses marked with (*) are new courses with new content, but also include content that overlap with retired courses (CSE 352, CSE 471). Not included above are course re-numberings to better align numbers with cross- listed EE courses as re-numberings do not reflect true innovation/improvement. Greater Alignment with Electrical Engineering In 2015, we completed a significant reorganization of core pieces of our computer engineering curriculum to align with Electrical Engineering. The result is: 1. More cross-listed courses, allowing students additional flexibility in offerings. 46 of 291 2. Better shared teaching resources across the departments, again allowing more offerings but also providing better alignment for the several joint faculty between the programs 3. Better use of facilities: sharing lab space for shared courses 4. More senior-level opportunities for students: Via shared cross-listed courses, more Computer Engineering students have the pre-requisites for senior-level EE courses and vice versa. 5. More rational division of material into courses and less redundancy across courses. Full documentation of the rationale and changes from 2015 is available. Here we sketch the key pieces: • We removed CSE 352, a hardware design course that was focused mostly on very basic processor design and which was a poor fit for students with no prior hardware-lab experience. • We created CSE 369, a “bridge course” that leverages the Boolean logic material in CSE 311 to quickly get students hardware-lab experience. Basically, this 2-credit course is enough for students to gain the experience necessary for CSE/EE 371 rather than completing the 5-credit EE 271. CSE 369 does the EE 271 labs, providing shared knowledge. • CSE/EE 371 cross-lists what was previously a CSE-only course. This is the most advanced required digital design course for Computer Engineering. • CSE/EE 469 and CSE/EE 470 provide a two-course sequence in processor design. Prior to the cross-listing, we did not have the teaching resources to provide a two-course sequence. • As mentioned above, this alignment enables Computer Engineers to have the pre- requisites for additional EE senior electives, notably courses in VLSI. The process was a broad collaboration of many faculty in both the Allen School and Electrical Engineering with a careful cataloguing of material moved, added, or removed. Full “master syllabi” for all new or renumbered courses were compiled and submitted to the faculty for approval as well as then sent through the University’s processes for new courses and degree- requirement changes. Allen School faculty meetings reviewed the overall curriculum change twice before it was approved. Other Program Changes While adding over a dozen new courses and completely reorganizing our digital logic and computer architecture courses comprise the most substantial improvements since our previous review, other program changes are worth noting as well. We catalog them here. 1. Ethics: As described in Criterion 5, our educational outcomes related to ethics and professional responsibility are ensured through material in CSE 403, CSE 474, and CSE 484, but our students and faculty want both opportunities for deeper discussions of ethical 47 of 291 challenges our field is facing and additional opportunities to connect technical material to societal challenges. We have made progress on both fronts and hope to further cement this progress in the coming year or two. For deeper discussions, we have offered four seminars on ethics in the last two years. Two were fairly conventional discussion seminars where students prepared by reading about a topic (e.g., biased artificial intelligence or online privacy) and then discussed. The other two took a much broader view of the future of artificial intelligence, with readings and discussion ranging from philosophy to neuroscience and more. For additional connections, discussions of bias, fairness, and accessibility are now common in new courses, notably natural language processing and interaction programming. Plans for the next year include better cataloguing where these modules appear and encouraging them to happen more regularly. 2. Project practicum: We encourage students to learn through team-based projects, but we noticed and fixed a gap in our courses. We had course numbers for capstones (described in detail elsewhere) and for independent research, but not for team projects that may not be aimed toward novel research results. We fixed this by adding the CSE 495 course number. To date, we have used this number for two purposes: For faculty-advised projects that contribute meaningfully to open-source projects, and for a number of projects in which students have contributed to making technology more accessible for people with disabilities. 3. CSE 332: We made substantial changes to CSE 332, including all new projects and more focus on using modern software tools and processes. 4. CSE 312, 332, 333 content shift: At the time of our 2013 review, our 300-level courses were only 2-3 years old and “what fit where” was still solidifying as our first students taking these coursers were graduating. In 2014 or so, we moved around some topics to improve 300-level course outcomes and balance student workload. Specifically: • Material on intractability and P vs. NP moved from 312 to 332 • Material on concurrency moved from 332 to 333 (material on parallelism remained in 332) 5. More seminars: Our students benefit immensely from low-credit seminar courses that complement their technical, graded courses. In addition to the ethics seminars discussed above and existing seminars on entrepreneurship and on career-advice-from-alumni/ae, we have been adding new seminars more often. In the last two years, we have had seminars on software reliability engineering, career patterns for success, and the history of computing. 6. End-of-year optional poster fair: Many of our capstone courses as well as other project courses have open poster sessions at the end of the term that attract members of our community and give our students a chance to communicate their ideas. In 2017, we added an annual end-of-year fair open to all students from all courses in which we have a dozen or so alumni or other supporters come to interact with students and award a prize. 7. TA training: While we have long had a TA training for TAs in our large introductory courses (CSE 142 and CSE 143), in 2016 we created a complementary weekly training for undergraduate TAs in our other courses. The content of the training has been evolved and assessed over the last three years. 50 of 291 CRITERION 5. CURRICULUM Since our last ABET program review in 2013, the Allen School has designed and implemented an update to our core curriculum. We changed how the senior electives were distributed in order to ensure all students graduating with a Computer Engineering degree met the necessary engineering course requirements. We also introduced courses co-listed with Electrical and Computer Engineering (ECE) to broaden our course offerings in hardware courses. These changes were motivated by and designed with feedback from undergraduates and employers, as well as the observations of our own faculty. We began teaching the new curriculum in 2015. During a transition period we offered both the old and new courses. We completed introducing the new set of courses during the 2016-17 academic year, and at this point are no longer offering the old courses. We are just now seeing the graduation of the last of the students who started the program under the old set of courses and graduation requirements. Effect of the Revision We have had two sets of graduation requirements for our computer engineering degree since Autumn of 2013. We try to give here an overall sense of the changes that have taken place. Details on the graduation requirements can be found online, however: Spring 2013 – Spring 2015 https://s3-us-west-2.amazonaws.com/www-cse- public/ugrad/curriculum/CompE_wi14.pdf Autumn 2015 - present https://s3-us-west-2.amazonaws.com/www-cse- public/ugrad/curriculum/CompE_au16.pdf At the highest level, our degree requirements consist of a “Computer Engineering Component” and a “General Education Component.” The total number of credits required in each of those two broad categories has remained nearly constant – there has been no significant reduction or rebalancing. Within the Computer Engineering component we distinguish between Required courses, CSE System Elective courses, and what we will call CSE General Electives. The former are required; there is some flexibility in the latter two (along the lines of “4 courses chosen from…”) while ensuring that every graduate has taken a set of courses that together meet our student outcomes. A. Program Curriculum A.1 Tables 51 of 291 Table 5-1 Curriculum Computer Engineering Year; Semester or Quarter Course (Department, Number, Title) Required, Elective or Selected (R, an E or SE.)1 Category (Credit Hours) Last Two Terms the Course was Offered Maximum Section Enrollment for the Last Two Terms Math & Basic Sciences Eng Topics Check if Contains Significant Design General Educatio n Other 1 Yr/ 1st Qtr Math 124 Calc w/Anal Geometry R. 5 ( ) Wi 2019 & Sp 2019 657,248 Natural Science Elective S.E. 5 ( ) Wi 2019 & Sp 2019 175, 175 English Composition S.E. ( ) 5 Wi 2019 & Sp 2019 30,30 1 Yr/ 2nd Qtr Math 125 Calc w/Anal Geometry R. 5 ( ) Wi 2019 & Sp 2019 1006, 442 Phys 121 R. 5 ( ) Wi 2019 & Sp 2019 551, 546 VLPA/I&S Elective S.E. ( ) 5 Wi 2019 & Sp 2019 NA 1 Yr/ 3rd Qtr Math 126 Calc w/Anal Geometry R. 5 ( ) Wi 2019 & Sp 2019 1004, 827 Physics 122 R. 5 ( ) Wi 2019 & Sp 2019 556,425 VLPA/I&S Elective S.E. ( ) 5 Wi 2019 & Sp 2019 NA 2 Yr/ 1st Qtr Natural Science Elective S.E. 5 ( ) Wi 2019 & Sp 2019 175, 175 52 of 291 Year; Semester or Quarter Course (Department, Number, Title) Required, Elective or Selected (R, an E or SE.)1 Category (Credit Hours) Last Two Terms the Course was Offered Maximum Section Enrollment for the Last Two Terms Math & Basic Sciences Eng Topics Check if Contains Significant Design General Educatio n Other CSE 142 Computer Programming I R. 4 ( ✓) Wi 2019 & Sp 2019 894, 487 VLPA/I&S Elective S.E. ( ) 5 Wi 2019 & Sp 2019 NA 2 Yr/ 2nd Qtr Math 308 Linear Algebra R. 3 ( ) Wi 2019 & Sp 2019 1011,644 CSE 143 Computer Programming II R. 5 ( ✓) Wi 2019 & Sp 2019 823, 591 VLPA/I&S Elective S.E. ( ) 5 Wi 2019 & Sp 2019 NA Math Science from Approved List S.E. 3 ( ) Wi 2019 & Sp 2019 50, 50 2 Yr/ 3rd Qtr EE 205 Introduction to Signal Conditioning/ EE 215 option for either one R. 4 ( ✓) Wi 2018 & Au 2018 23, 10 ENGR 231 Intro. to Technical Writing R. ( ) 3 Wi 2019 & Sp 2019 221, 223 VLPA/I&S Elective S.E. ( ) 5 Wi 2019 & Sp 2019 NA CSE 311 Foundations of Computing II R. 2 2 ( ) Au 2018 & Sp 2019 306,249 3 Yr/ 1st Qtr CSE 351 The Hardware/Software Interface R. 4 ( ✓) Wi 2019 & Sp 2019 155, 217 55 of 291 Year; Semester or Quarter Course (Department, Number, Title) Required, Elective or Selected (R, an E or SE.)1 Category (Credit Hours) Last Two Terms the Course was Offered Maximum Section Enrollment for the Last Two Terms Math & Basic Sciences Eng Topics Check if Contains Significant Design General Educatio n Other OVERALL TOTAL CREDIT HOURS FOR COMPLETION OF THE PROGRAM 45 70 42 23 PERCENT OF TOTAL 25% 39% Total must satisfy either credit hours or percentage Minimum Semester Credit Hours 32 Hours 48 Hours Minimum Percentage 25% 37.50% Required courses are required of all students in the program, elective courses (often referred to as open or free electives) are optional for students, and selected elective courses are those for which students must take one or more courses from a specified group. 1. For courses that include multiple elements (lecture, laboratory, recitation, etc.), indicate the maximum enrollment in each element. For selected elective courses, indicate the maximum enrollment for each option. 56 of 291 A.2 Curriculum Alignment with Program Educational Objectives Describe how the curriculum aligns with the program educational objectives. Our program educational objectives are engineering quality, leadership, economic impact, and lifelong learning. All of these require strong preparation in the concepts, skills, and abilities of a computer engineer. Additionally, they require an understanding of the context in which contributions may be made and the processes by which substantial projects can be accomplished. Our curriculum aims to provide experiences that enable our students to perform at a high level in all these areas. Our computer engineering curriculum provides depth and breadth across topics in computer science and computer engineering as described in detail in Section B.4 and Appendix A. The specific required mathematics, science and engineering knowledge is acquired as follows: • Discrete mathematics is covered in depth in CSE 311 (Foundations I) and extended in other courses such as CSE 332 (Data Abstractions) • Probability and Statistics is taught in CSE 312. • Differential and integral calculus is covered in MATH 124, 125 and 126, the sequence on calculus and analytic geometry. • Science background is covered in Physics 121 (Mechanics) and Physics 122 (Electromagnetism and Oscillatory Motion) and the natural science requirement. Our Computer Engineering program focuses on the interface in computer systems between the hardware and software level. That is, computer engineers are faced with the design of systems that involve significant interaction between hardware and software and must have the knowledge required to deal with both sides of this interaction. Traditionally, this interface has been drawn close to the circuit level of hardware, where the computer engineer must have knowledge of analog and digital circuits, and understand computing systems comprised of these elemental building blocks. All our students must take CSE 351, the Hardware/Software Interface, as an introduction to this level of modern computer systems. Students in Computer Engineering learn the underlying fundamentals of circuits and electrical engineering in EE 205 (Introduction to Signal Conditioning) or EE 215 (Introduction to Electrical Engineering), and the fundamentals of digital circuits in CSE 369 and CSE/EE 371. These courses involve a substantial laboratory component and hands-on design. All students must take at least one of CSE 403 (Software Engineering), CSE 474 (Software for Embedded Systems), or CSE 484 (Security). These courses involve teamwork, a consideration of ethical responsibility, and an awareness of contemporary issues. All students must take at least one capstone design course. These courses address a large variety of specific topics, but all include heavy emphasis on teamwork, design, independent learning, and communication. The typical format involves a combination of a large project design and implementation and some number of lectures. Project goals are typically set by the team, within a broad set of constraints imposed by the instructor. Regular assessment of progress is performed, and most often teams are required to regularly document the current state of the project and to provide a plan for its completion. Public presentations of projects are commonplace, although sometimes substantial reports take their place. 57 of 291 In summary, students in the Computer Engineering program learn the concepts required to analyze and design complex systems comprising hardware and software at the level appropriate to their specialization. A.3 Curriculum & Student Outcomes Describe how the curriculum and its associated prerequisite structure support the attainment of the student outcomes. Table 5-2 Student outcomes and mapping to curricular and extra-curricular elements. Curriculum Component (credits) Extra-curricular VLPA/ IS Commun Math/ Statis Science CE core Selective Elective Capstone Electives Industry internships Research project TA Experience (1) an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics M M H H H H H H (2) an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors H H H H H M (3) an ability to communicate effectively with a range of audiences H M L H H M H (4) an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgements, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts M H H (5) an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives L L H H M H (6) an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgement to draw conclusions L M H M M H (7) an ability to acquire and apply new knowledge as needed, using appropriate learning strategies M H H H H H L 60 of 291 A.4 Course Prerequisite Structure Attach a flowchart or worksheet that illustrates the prerequisite structure of the program’s required courses. Computer Engineering Courses - & S 61 of 291  62 of 291 A.5 and A.6 Meeting Degree Requirements Describe how the program meets the requirements in terms of hours and depth of study for each subject area (Math and Basic Sciences, Engineering Topics) specifically addressed by either the general criteria or the program criteria. Describe the broad education component and how it complements the technical content of the curriculum and how it is consistent with the program educational objectives. The curriculum is structured to provide both depth and breadth. Students majoring in Computer Engineering have some flexibility to tailor the program toward different career specializations. For example, we offer capstone design courses in topics as diverse as robotics, computational biology, embedded systems, and virtual reality. We do not require any single such course. Instead, we ensure that all of them fulfill broad curriculum needs, such as training in communication and extensive design and teamwork, and then allow students to choose. A set of common core courses form a foundation on which senior requirements are layered and appropriate capstone design courses provide an in-depth design experience. Our courses are structured to ensure that all students can achieve all the outcomes that we have defined for the program. Our curriculum requirements are grouped into 9 categories: • General education • Visual, literary, and performing arts/Individuals & societies • Written and oral communication • Mathematics and statistics • Science • CSE core • CSE system electives • CSE senior electives • Free electives General education and VLPA/IS1 requirements expose our students to a variety of topics in the humanities and the natural world. Students select the courses they wish to take in these areas based on their interests, and we encourage them to explore general education outside of their chosen degree/career path. General education courses complement the technical aspects of our computer engineering degree and support our program objectives by expanding our students’ experiences and worldview. The field of computer engineering is highly interdisciplinary, and a student’s ability to communicate ideas, work in teams, obtain new knowledge, and understand others is necessary for technical skills to be useful. A broad perspective and diverse skill base are fundamental to our students’ ability to effectively engage in engineering quality, leadership, economic impact, and lifelong learning across interdisciplinary environments. 1 Visual, Literary, and Performing Arts / Individual and Societies 65 of 291 A.7 Design Experience Describe the major design experience that prepares students for engineering practice. Describe how this experience is based upon the knowledge and skills acquired in earlier coursework and incorporates appropriate engineering standards and multiple design constraints. Students gain significant design experience throughout the program, starting with relatively small design problems in the core courses and proceeding to substantial, quarter-long team projects in the capstone courses. Many of the required senior-level courses are taught in the context of a substantial design project experience. Selective Elective Courses These courses all contain a significant design component. CSE401 – Introduction to Compiler Construction: This has always been a project class in our department. The class implements new features in a scaled down, but running, mini- compiler. This differs from the build everything from scratch approach and is preferred by UW faculty because it models the typical industry situation of working with someone else's code. Students must “get their brain around” the compiler's structure before writing their own code. Further, it shows them good practice, as the mini-compiler is beautifully written. Students extend the language by adding statements and operations, and extend the compilation by improving code generation, etc. They touch all phases from lexing to target code generation. They use source-control tools, lex-generator, parse-generator, and development tools like debuggers. Of course, along with all of the implementation, concepts, theory and best practices are covered in lecture. Past graduates have commented years after leaving campus that it was one of perhaps two most important classes for preparing them for a development career. CSE402 – Design and Implementation of Domain-Specific Language: This course uses a number of modern tools and concepts for implementing programming languages, typically by embedding new languages within higher-level languages. In the last 3 weeks of the course, students design and implement their own language using the ideas and techniques learned via earlier assignments. They not only gain the ability to succeed in building a new language, but in motivating the need for a special-purpose language and in designing how to meet that need. CSE403 – Software Engineering: Students complete a 9-week design and implementation project. The students propose ideas for software systems to build and are placed into groups of 5-8. Several deliverables are required during the course of the projects, including a requirements analysis, design specification, beta and final code releases, and testing materials. The design specification includes the submission of several documents and diagrams describing the system to be built. The students are taught and asked to use modern tools such as content management systems, design diagrams, and testing frameworks to generate their materials. Examples of engineering design decisions students were required to make included: • What features should the project have? What is the relative importance of these features, i.e., which ones should be cut if time becomes tight? 66 of 291 • What languages and tools should we use to design and implement these features? This includes CASE tools such as design diagram editors, schedulers, version control, bug tracking tools, as well as the overall programming language(s), APIs / libraries, and IDEs used to write the code. • What should the testing plan be? This includes unit testing as well as system testing in some form. CSE 444 – Database System Internals: This course teaches the internals of relational database management systems and how to build such systems. It builds on the material in CSE 344. The course covers the full stack. Starting from a quick review of the relational model and SQL, the course dives into the architecture of a DBMS and then goes in depth into each component: storage manager, query executor, query optimizer, transactions, parallel processing, distributed transactions, data replication, architecture of NoSQL and NewSQL systems, etc. Students get to implement each of the components in their own Java DBMS. At the end of the quarter, successful students have a working DBMS that can execute SQL queries, update data, run concurrent transactions, recover from failures, and either execute in parallel or optimize queries. CSE451 – Operating Systems: The objectives of the project component of CSE 451 are to a) provide experience in working in teams to design, implement, and evaluate important components of modern operating systems, b) provide experience in recognizing, evaluating, and making the engineering design tradeoffs that characterize operating system design and, in fact, many other aspects of computer system design, c) provide experience in conducting performance experiments and understanding the performance tradeoffs that are crucial in operating system design and, again, in many other aspects of computer system design, and d) provide experience in producing coherent written technical descriptions and assessments of designs, design tradeoffs, and implementations. The exact nature of the course depends on the operating system chosen as the exemplar. In most cases it is Linux, but in some offerings it is Windows. In both cases, students design features that have to be integrated with the existing, actual OS code base. In the most common instantiation of the course, students design and implement sophisticated components of modern systems, such as threads and synchronization primitives, resource managers, and components of the virtual memory and file systems. Feedback from our alumni and their employers consistently indicates that this course is one of the most beneficial in our curriculum in terms of preparing students for engineering careers where they will tackle these sorts of issues on a regular basis. CSE 452 - Distributed Systems: Distributed systems have become central to many aspects of how computers are used, from web applications to e-commerce to content distribution. This senior-level course covers abstractions and implementation techniques for the construction of distributed systems, including client server computing, the web, cloud computing, peer-to- peer systems, and distributed storage systems. The course has a demanding set of projects wherein students develop fault-tolerant distributed systems, including primary-backup systems, replicated state machines, and transactions across replicated state machines. The course project is designed to help students understand the implementation issues in modern cloud-scale systems, and they implement simplified versions of Google’s Chubby and Spanner systems. 67 of 291 CSE 461 – Introduction to Computer-Communications Networks: Students learn the fundamentals of networking layers, from physical through application. Additionally, they implement significant networked software that also highlights the operating system interfaces for networking and the behavior of real-world distributed software systems. There is considerable emphasis on dealing with errors and doing so efficiently. Project specifications are for protocols, some of which may be developed communally. Student implementations of the protocols are intended to inter-operate with each other and with reference implementations. CSE474– Embedded Systems: The laboratories require the student to assess and analyze the assignment, then apply basic engineering knowledge to either solve the problem or state why (based upon their analysis) they are unable to fully satisfy the requirements. The laboratories assign a particular design problem to be solved. The final project brings all of the concepts together through the development of a (simplified) real world project. Each of the design projects provides a high-level requirements specification and a design specification for the problem that must be solved and each student must think about the broader implications of their designs. For the final project, the students are given only a set of requirements and they must interpret the requirements and implement the design specification. CSE 469 – Computer Architecture I: Strong knowledge of hardware design and Verilog from EE 271 or CSE 369 is essential. The major goals of the class are to familiarize you with basic structure of microprocessors. As part of this, students will develop a Verilog implementation of a simple RISC microprocessor based upon the ARM instruction set. We will cover: o Introduction to processor architecture. o Assembly language programming. o Computer Arithmetic. o Performance measures. o Processor Datapaths & Control. o Pipelining. o Memory hierarchy, caches, virtual memory. o Advanced topics in computer architecture CSE 470 – Computer Architecture II: Students learn key architectural techniques from original research papers and discuss in class how those solutions are implemented, their trade- offs and relevance to today. Students discuss and learn about contemporary needs and how key hardware design techniques are useful for addressing them. Students produce a written deep-dive summary of a research topic that synthesizes core knowledge in the area. CSE 484 – Computer Security: Computer security and privacy are increasingly critical issues as our world becomes more computerized and interconnected. This senior-level course complements the rest of students' computer science education by providing a broad foundation in computer security and privacy, teaching them a "security mindset" and techniques for evaluating the designs of computer systems and ultimately designing systems 70 of 291 As an example of the scope, organization, and activities in our capstones is seen in the course page for the robotics capstone from Winter 2019: https://sites.google.com/view/cse481wi. We chose this capstone simply because it has the pertinent information on a single web page, making it easy to review. Recent Capstone Offerings We describe here some of the capstone projects that have been done in the past few years. These projects are often presented to the larger department community, including colleagues and industrial affiliates, in the form of live demonstrations, videotaped productions, and documentation published on the Web. CSE 428 – Computational Biology Capstone: In this capstone, students are taught the basic tools of computational biology, including molecular biology, biological sequence analysis, current computational tools and databases for computational molecular biology. They then apply their computer software engineering skills in teams to design, implement, and test a software system to perform high throughput analysis of a problem in molecular biology. In most cases, the project teams each contribute a part of the overall solution and must co-ordinate their efforts to produce the final product. Example projects have included developing software that identifies evolutionarily conserved motifs in the DNA regulatory regions of homologous genes from multiple bacteria, phylogenetic footprinting in yeast species, and cataloguing the prokaryotic regulatory elements. CSE 441 – Advanced HCI: Students will work in groups of three or four on a single project that parallels the experience of delivering an interactive prototype within a company or with a customer. Students are expected to already possess knowledge of appropriate HCI methods, and will focus on independently applying those methods in the context of your project. There will therefore be little lecture material in this course. Course staff will instead work closely with students to critique and advise on their group project. Students will experience the end-to-end product cycle from design to deployment. CSE 460 – Animation: Students apply the knowledge gained from CSE 458 to produce an animated short film. Students will go through an animation industry standard production pipeline that involves modeling, shading, lighting, animating, rendering, and post-production. CSE 475 – Embedded Systems Capstone: This course has a strong focus on hardware/software integration and embedded systems design. This includes hardware-intensive projects that are implemented using large FPGA platforms or distributed embedded sensor platforms. Students apply significant amount of knowledge gained from their embedded systems prerequisites and low-level programming language classes. In addition, projects must consist of a combination of hardware and software components and leverage the different expertise of the project team members. Thus, students apply general software engineering practices, database and networking knowledge, interface design, and other specialized computer science concepts to build end-to- end final projects. CSE 481A – Operating Systems: 481A is a capstone course on operating systems, with an emphasis on virtualization. In lectures we introduce lvisor, a minimal x86 hypervisor based on KVM. We expect students to work on a project related to lvisor, finish exercises, discuss research papers, and make a presentation of their projects at the end of the quarter. 71 of 291 CSE 481C – Robotics Capstone: The robotics capstone teaches Computer Science & Engineering students the basics of robotics and gives them experience programming a mobile manipulator robot. The course covers robot motion, navigation, perception, manipulation, and user interaction through mini-lectures, labs and assignments. Students integrate these components to create autonomous or semi-autonomous robotic functionalities for a realistic robotic application. They learn to use libraries and tools within the most popular robot programming framework called ROS (Robot Operating System). The project gives students team-work experience with large scale software integration and gets them to explore opportunities for using robots to make people's lives easier. CSE 481N - Natural Language Processing: In this capstone, students will work in small teams of 2-3 to build applications, prototype systems, and investigate scientific hypotheses using state of the art Natural Language Processing (NLP) technology. Areas of applications include text classification, information extraction, social media analysis, summarization, conversation (usually called dialogue by researchers), interpretation of deep neural models, question answering, and semantic parsing. In addition, cross-disciplinary applications are also encouraged, for example, image captioning, code generation from natural language descriptions, language based robot manipulation and navigation, connecting NLP with various disciplines such as computer vision, robotics, HCI, and programing languages. CSE481S – Security: Student teams will be tasked with creating a computer security themed product. The work will progress from product conception to requirements to design to implementation to evaluation. Along the way, students will incorporate key computer security tools and practices, including threat modeling, penetration testing, and bug fixing. Examples include password managers, censorship resistance systems, and mobile payment systems. CSE481V - AR/VR: Virtual and Augmented reality are promising technologies that are certain to make an impact on the future of business and entertainment. In this capstone, students will work in small project teams to build applications and prototype systems using state of the art Virtual Reality (VR) and Augmented Reality (AR) technology. Seattle is a nexus of VR tech, with Oculus Research, Valve, Microsoft (hololens), Google (cardboard, jump), and teams in the area. We will be developing on the latest VR/AR headsets and platforms, and will bring in leading VR experts for lectures and to supervise student projects. Students will experience the end-to-end product cycle from design to deployment, and learn about VR/AR technology and applications. The capstone culminates in a highly anticipated demo day where the students demonstrate their creations to other students, faculty and industry luminaries. CSE 482 – Accessibility Capstone: Accessibility is quickly emerging as a leading consideration for product design and engineering. Disability is part of the human condition – almost everyone will be temporarily or permanently impaired at some point in life, and those who survive to old age will experience increasing difficulties. Disability is complex and heterogeneous, and the technological interventions to accommodate different abilities are wide ranging and vary with context. Many familiar technologies like voice recognition, text-to-speech, and gaze detection were initially engineered to assist people with disabilities gain more access and increase participation in daily life. Students will work in interdisciplinary project teams that include community members with expertise on project needs. Groups will follow participatory design practices and apply design and engineering skills to create technology solutions that increase independence and improve quality of life for people of all abilities. Teams will complete one 72 of 291 end-to-end product iteration cycle: ideation, design, specification refinement, prototype and usability testing 75 of 291 Five faculty members have received the University of Washington Distinguished Teaching Award, two have received the University of Washington Marsha L. Landolt Distinguished Graduate Mentor Award, two have received the University of Washington Outstanding Public Service Award, one has received the David B. Thorud Leadership Award, one was named the University of Washington Annual Faculty Lecturer, and three have received the College of Engineering Faculty Achievement Award. Our faculty continually strives to improve its teaching performance. Curriculum quality is enhanced through faculty self-assessments of their teaching performance after each course, peer evaluations of teaching, and student evaluations of each course. The self and peer evaluations touch upon not only teaching performance in specific course offerings but also consider curriculum development, development of course infrastructure, future plans for the course content and assignments, and how previously identified issues were handled. All our courses are evaluated by students. The faculty takes full advantage of the resources the University and College have to offer. In particular, many of our faculty have had the College of Engineering’s Center for Teaching and Learning visit classes. Several of our instructional faculty are part of a campus-wide initiative on evidence-based teaching practices. The faculty is extremely active in research and our department is consistently ranked in the top 10 in the nation in our discipline. There are strong ties with industry, with many faculty receiving research and educational support from corporations. National visibility is high, with several faculty members serving on National Science Foundation advisory boards, National Research Council study panels, Department of Defense research organizations, and more. 76 of 291 Table 6-1 Faculty Qualifications Faculty Name Highest Degree Earned- Field and Year T y p e o f A ca d em ic A p p o in tm en t2 T , T T , N T T F T o r P T 3 Years of Experience P ro fe ss io n al R eg is tr at io n / C er ti fi ca ti o n Level of Activity4 H, M, or L G o v t. /I n d . P ra ct ic e T ea ch in g T h is I n st it u ti o n P ro fe ss io n al O rg an iz at io n s P ro fe ss io n al D ev el o p m en t C o n su lt in g /s u m m e r w o rk i n i n d u st ry Anderson, Richard PhD, Computer Science Stanford, 1985 P T FT 33 33 L M L Anderson, Ruth Ph. D., Computer Science University of Washington, 2006 O NTT FT 19 14 M L N Anderson, Tom PhD, Computer Science Washington, 1991 P T FT 4 27 21 H M L Balazinska, Magdalena PhD, Computer Science MIT, 2006 P T FT 13 13 H H M Beame, Paul PhD, , Computer Science Toronto, 1987 P T FT 31 31 H H L Bodik, Rastislav PhD, University of Pittsburgh, 1999 P T FT 19 4 M H M Bricker, Lauren Ph.D. Computer Science UW, 1998 O NTT FT 22 14 2 L M L Cakmak, Maya PhD, Robotics, Georgia Institute of Technology, 2013 AST TT FT 1 6 6 L M L Ceze, Luis PhD, Computer Science UIllinois Urbana-Champaign, 2007 ASC T FT 12 12 H Cheung, Alvin PhD, Computer Science, MIT, 2015 AST TT FT 4 4 L Choi, Yejin PhD, Computer Science, Cornell, 2010 ASC T FT 9 5 M H H Curless, Brian PhD, Electrical Engineering Stanford, 1997 P T FT 19 19 M H L 77 of 291 Faculty Name Highest Degree Earned- Field and Year T y p e o f A ca d em ic A p p o in tm en t2 T , T T , N T T F T o r P T 3 Years of Experience P ro fe ss io n al R eg is tr at io n / C er ti fi ca ti o n Level of Activity4 H, M, or L G o v t. /I n d . P ra ct ic e T ea ch in g T h is I n st it u ti o n P ro fe ss io n al O rg an iz at io n s P ro fe ss io n al D ev el o p m en t C o n su lt in g /s u m m e r w o rk i n i n d u st ry Domingos, Pedro PhD, Computer Science UC-Irvine, 1997 P T FT 22 20 L H L Ernst, Michael PhD, Computer Science Washington, 2000 P T FT 20 11 H M Farhadi, Ali PhD, Computer Science U Illinois Urbana-Champaign, 2011 ASC TT FT 7 7 L H H Fogarty, James PhD, Computer Science Carnegie Mellon, 2006 P T FT 13 13 H L Fox, Dieter PhD, Computer Science U Bonn, 1998 ASC T FT 4 19 19 H M Froehlich, Jon PhD, Computer Science, U. of Washington, 2011 ASC T FT 8 2 Gollakota, Shyamnath PhD, EE & Computer Science, MIT, 2013 ASC TT FT 7 7 H Grossman, Daniel PhD, Computer Science Cornell, 2003 P T FT 16 16 H H L Guestrin, Carlos PhD, Computer Science Stanford, 2003 P T FT 1 15 7 H Hannaneh Hajishirzi PhD, Computer Science UIUC, 2011 AST TT FT 1 4 M H M Heer, Jeffrey PhD, Computer Science UC Berkeley, 2008 P TT FT 6 11 6 M M H Heimerl, Kurtis PhD, Computer Science UC Berkeley, 2013 AST TT FT 3 3 3 L M L Hemingway, Bruce AB, Music Indiana U, 1973 O NTT PT 32 19 17 L L L Hsia, Justin PhD, Computer Science UC Berkeley, 2013 O NTT FT 1 4 3 L L N 80 of 291 Faculty Name Highest Degree Earned- Field and Year T y p e o f A ca d em ic A p p o in tm en t2 T , T T , N T T F T o r P T 3 Years of Experience P ro fe ss io n al R eg is tr at io n / C er ti fi ca ti o n Level of Activity4 H, M, or L G o v t. /I n d . P ra ct ic e T ea ch in g T h is I n st it u ti o n P ro fe ss io n al O rg an iz at io n s P ro fe ss io n al D ev el o p m en t C o n su lt in g /s u m m e r w o rk i n i n d u st ry Rothvoss, Thomas PhD, Mathematics EPFL, 2009 ASC T Joint FT 5 5 M M N Ruzzo, Larry PhD, Computer Science UC Berkeley, 1978 P T FT 5 42 42 N H N Schafer, Hunter MS, Computer Science UW, 2018 O NTT FT 1 1 N L N Seelig, Georg PhD, Physics U of Geneva, 2003 ASC T Joint FT 10 H Seitz, Steve PhD, Computer Science U Wisconsin, 1997 P T FT 3 22 19 L H L Shapiro, Linda PhD, Computer Science U Iowa, 1974 P T FT Joint 2 43 33 M H L Smith, Joshua PhD, Media Arts & Sciences MIT, 1999 P TT FT- Joint 11 9 9 L H M Smith, Noah PhD, Computer Science Johns Hopkins, 2006 P T FT 1 13 4 H H H Suciu, Dan PhD, Computer Science U Pennsylvania, 1995 P T FT 5 22 19 M H M Tanimoto, Steve PhD, Computer Science Princeton, 1975 P T FT 0 44 42 M H H Tatlock, Zachary PhD, Computer Science & Eng UC San Diego, 2014 AST TT FT 6 6 M M L Taylor, Michael PhD, EECS MIT, 2007 ASC T FT 2 13 2 M H L Tessaro, Stefano PhD, Computer Science ETCH Zurich, 2010 ASC T T 6 1 L H L Tompa, Martin PhD, Computer Science U Toronto, 1978 P T PT 4 37 37 L H H 81 of 291 Faculty Name Highest Degree Earned- Field and Year T y p e o f A ca d em ic A p p o in tm en t2 T , T T , N T T F T o r P T 3 Years of Experience P ro fe ss io n al R eg is tr at io n / C er ti fi ca ti o n Level of Activity4 H, M, or L G o v t. /I n d . P ra ct ic e T ea ch in g T h is I n st it u ti o n P ro fe ss io n al O rg an iz at io n s P ro fe ss io n al D ev el o p m en t C o n su lt in g /s u m m e r w o rk i n i n d u st ry Torlak, Emina PhD, Computer Science MIT, 2009 ASC T FT 3 5 5 M M L Wang, Xi PhD, Computer Science MIT, 2014 AST TT FT 5 5 Weld, Daniel PhD, Artificial Intelligence MIT, 1988 P T FT 31 31 H H H Zahorjan, John PhD, Computer Science U Toronto, 1980 P T FT 39 39 L L L Zettlemoyer, Luke PhD, Computer Science MIT, 2009 ASC T FT 8 8 M H H Instructions: Complete table for each member of the faculty in the program. Add additional rows or use additional sheets if necessary. Updated information is to be provided at the time of the visit. 1. Code: P = Professor ASC = Associate Professor AST = Assistant Professor I = Instructor A = Adjunct O = Other 2. Code: T = Tenured TT = Tenure Track NTT = Non Tenure Track 3. Code: FT = Full-time PT = Part-time Appointment at the institution. 4. The level of activity (high, medium or low) should reflect an average over the year prior to the visit plus the two previous years. 82 of 291 B. Faculty Workload Complete Table 6-2, Faculty Workload Summary and describe this information in terms of workload expectations or requirements. Table 6-2 Faculty Workload Summary Faculty Member (name) PT or FT1 Classes Taught (Course No./Credit Hrs.) Term and Year2 Program Activity Distribution3 % of Time Devoted to the Program5 Teaching Research or Scholarship Other4 Anderson, Richard FT 18:au: CSE 490b, 19wi: CSE 421, 19sp: CSE 482b 33% 50 17% 100% Anderson, Ruth FT 18au: CSE 332, CSE590E; 19wi: CSE 332, CSE590E; 19sp: CSE 351, CSE590E 80% 10% 10% 100% Anderson, Tom FT sabbatical 22% 61% 17% 100% Balazinska, Magdalena FT 18au: CSED516; 19wi & 19sp: leave 22% 61% 17% 100% Beame, Paul FT sabbatical 22% 61% 17% 100% Bodik, Rastislav FT 18au: release; 19wi: CSE501; 19sp: CSE402 33% 34% 33% 100% Bricker, Lauren FT 18au: CSE 190Z, CSE 154; 19wi: CSE 190Z; 19sp: CSE 190Z, CSE 154 50% 10% 40% 100% Cakmak, Maya FT 18au: MSTI 510 19wi: CSE 481 C 22% 61% 17% 100% Ceze, Luis FT 22% 61% 17% 100% Cheung, Alvin FT Partial leave 80% 20% Choi, Yejin FT 18sp: 481 N, 18wi: CSE 447, 19wi: CSE 517 22% 61% 17% 100% Curless, Brian FT 19sp: CSE P 557 11% 56% 33% 100% Domingos, Pedro FT 100% 100% Ernst, Michael FT 22% 61% 17% 100% Farhadi, Ali FT 18: au: CSE 599 10% 80% 10% 100% 85 of 291 Faculty Member (name) PT or FT1 Classes Taught (Course No./Credit Hrs.) Term and Year2 Program Activity Distribution3 % of Time Devoted to the Program5 Teaching Research or Scholarship Other4 Ruzzo, Larry FT 18au: CSE 427, CSE 590C; 19wi: CSE 417, CSE 590C; 19sp: CSE 427, CSE 590C 33% 50% 17% 100% Schafer, Hunter FT 18au: CSE 143; 19wi: CSE 143; 19sp: CSE 163 90% 10% 100% Seelig, Georg FT 11% 72% 17% 100% Seitz, Steve FT 11% 72% 17% 100% Shapiro, Linda FT 18au: EE 562; 19wi: CSE 473; 19sp: CSE/EE 576 25% 50% 25% 100% Smith, Joshua FT 100% 100% Smith, Noah FT 19wi: CSE 447; 19sp: CSE 481N 25% 50% 25% 100% Suciu, Dan FT 18au: CSE344; 19wi: CSE344; 19Sp: CSE414 33% 50% 17% 100% Tanimoto, Steve FT 18au CSE 473, 19wi CSE 415, 19sp CSE 415 22% 61% 17% 100% Tatlock, Zachary FT 18au CSE 505, 19wi CSE 341, 19sp CSE P505 33% 50% 17% 100% Taylor, Michael FT 19wi CSE 567, EE 477, EE 525 20% 63% 17% 100% Tessaro, Stefano FT CSE P590 30% 40% 30% 100% Tompa, Martin PT 19wi CSE 312 100% 100% Torlak, Emina FT 22% 61% 17% 100% Wang, Xi FT 22% 61% 17% 100% Weld, Daniel FT CSEP 573 12% 30% 8% 50% Wortzman, Brett FT 18au: CSE 142, CSE 391; 19wi: CSE 391, CSE 390 HA; 19sp: CSE 142, CSE 391, CSE 390 HA 80% 5% 15% 100% Zahorjan, John FT 18au CSE 481SYS ; 19wi CAE 451; 19sp CSE 461 60% 10% 30% 100% Zettlemoyer, Luke FT 18au CSEP 517; 19sp CSE 473 22% 61% 17% 100% 1. FT = Full Time Faculty or PT = Part Time Faculty, at the institution 86 of 291 2. For the academic year for which the self-study is being prepared. 3. Program activity distribution should be in percent of effort in the program and should total 100%. 4. Indicate sabbatical leave, etc., under "Other." 5. Out of the total time employed at the institution. 87 of 291 C. Faculty Size Discuss the adequacy of the size of the faculty and describe the extent and quality of faculty involvement in interactions with students, student advising and counseling, university service activities, professional development, and interactions with industrial and professional practitioners including employers of students. The department has about 75 tenure-line faculty members (counting joint appointments fractionally), 10 instructors, and around 35 postdocs. Since 2013 the department has made 27 tenure-track hires, a central piece of our aggressive growth. The most relevant for CompE are Rene Just (403), Ratul Mahajan (461), Michael Taylor (VLSI), Ras Bodik (402), Kurtis Heimerl (461, ICTD), and Franzi Roesner (484). D. Professional Development Provide detailed descriptions of professional development activities for each faculty member. In CSE, sabbaticals are permitted every 7 years and are supported by providing 2/3’s salary over three quarters. The department has very liberal policies with regard to faculty leaves to spend time in industry or to spin out department-developed technology. In general, we support faculty members’ requests for industrial interaction as we believe it enhances both our educational and research missions, creates new connections to industry, and gives faculty insight into important current problems faced by industry. Our Industrial Affiliates Program provides connections with over 100 high-tech companies both locally and nationally. CSE provides support for staff members, instructors, and students to travel to workshops, seminars, and meetings. We also support the creation of campus-wide technical communities in areas of importance to us. E. Authority and Responsibility of Faculty Describe the role played by the faculty with respect to course creation, modification, and evaluation, their role in the definition and revision of program educational objectives and student outcomes, and their role in the attainment of the student outcomes. Describe the roles of others on campus, e.g., dean or provost, with respect to these areas. Faculty take the lead in delivering existing courses, proposing new courses, evaluating individual courses and the curriculum as a whole, and in assigning grades. While we provide similar experiences within a course from quarter to quarter, there is considerable flexibility at the upper level, which allows faculty to innovate rapidly on assignments and, to a lesser extent, on topics. 90 of 291 Our new Gates Center facility includes an undergraduate commons where students can study, relax and work together, with adjacent computing labs, TA meeting rooms and collaboration spaces. Four workrooms for our outstanding interdisciplinary computer animation capstone, and other capstone design courses. Improved facilities for teaching assistants to meet with students, as well as a large advising suite where all undergraduate and graduate advisors are located. Interview rooms where industry representatives can meet with students. A total of more than 13,000 sq feet dedicated to undergraduate labs and support spaces. The Hardware Design/Embedded Systems Capstone Lab (CSE 003E) additionally contains many test instruments and hardware platforms for design of hardware projects and embedded systems. The lab has 16 workbenches, equipped with a workstation, oscilloscope, logic analyzer, function generator and power supply. Additional test equipment like multimeters and logic programmers are also available. B. Computing Resources Describe any computing resources (workstations, servers, storage, networks including software) in addition to those described in the laboratories in Part A, which are used by the students in the program. Include a discussion of the accessibility of university-wide computing resources available to all students via various locations such as student housing, library, student union, off-campus, etc. State the hours the various computing facilities are open to students. Assess the adequacy of these facilities to support the scholarly and professional activities of the students and faculty in the program. The Allen School provides a substantial instructional Linux compute/cycle cluster consisting of 8 servers where course software is installed. We also provide a Windows Virtual Lab (VDI) with 18 nodes that can be connected to by personal devices. There are also dedicated Linux and Windows servers available for special-purpose projects. We provide students with access to local high-bandwidth file storage, and hosting for both personal and class project oriented web pages. We provide hosting and support for course database projects - primarily PostgreSQL and MySQL/MariaDB. Secure Git repository management, code reviews, issue tracking, wikis are provided via our locally-hosted GitLab service. We perform nightly incremental backups of data on these systems, then replicate that data to a secondary site, and can restore files by request or in case of catastrophic system failure. We maintain disaster recovery copies of most research data on 'off-site' central IT tape service. These resources are available 24 hours a day, 7 days a week, to all CSE students and others enrolled in CSE major and graduate courses. Other University campus computing labs are also available to CSE students. The University Libraries offers some of the largest labs on campus with hundreds of PCs. Most library labs are open to students 24 hours a day M-F during the quarter and more limited hours on weekends. More recently many of the development tools required by CSE courses are also distributed on these campus computers. 91 of 291 C. Guidance Describe how students in the program are provided appropriate guidance regarding the use of the tools, equipment, computing resources, and laboratories. Use of computing is inherent in all our courses, and students acquire needed skills as part of doing course work. Our tech staff team provides general help. A help desk is open every day, and additional help is available online. Students receive an introduction and overview of the Computing lab facilities, IT services and policies during orientation to the School. The School maintains extensive webpages that outline these IT services https://www.cs.washington.edu/lab and also provides an overview and links to UW and School policies for use of computing resources http://www.cs.washington.edu/lab/policies-and-guidelines/ and that give instructions on how to use the resources available to them. Additionally, the technical group sends out a periodic newsletter announcing new services or reminders about existing services. Students can contact the CSE Support Office directly (by email or in person during business hours) for assistance with questions. D. Maintenance and Upgrading of Facilities Describe the policies and procedures for maintaining and upgrading the tools, equipment, computing resources, and laboratories used by students and faculty in the program. The Allen School has a full-time IT and Facilities teams dedicated to the care and upgrading of all the facilities mentioned above. Most computing hardware is on a planned 5 year refresh cycle. Student assistants on both the IT and Facilities team check laboratories daily. Instructional computing equipment is monitored by an hourly ‘ping’ utility that gauges relative health workstations in the laboratories. As well, centrally reporting boot time scripts on each workstation log hardware components and patch/version level of software. Printers are routinely checked (often daily) to ensure they are in working order and that supplies are stocked. For Windows software images, machines images are “frozen” and reset all file modifications to original settings after a student logs out, to ensure uptime and student privacy between user sessions. Software updates and security patches are pushed weekly during a staggered ‘Maintenance Hour’. For Linux software, package updates and patches are pushed centrally, on- demand by tech staff. Major refresh/upgrades to instructional software packages most often are saved for quarter breaks. The School has written many successful grants to a local Student Tech Fee Program (uwstf.org) every few years to provide funding for new computing equipment. The Allen School provides additional funding from time to time to purchase new computing equipment for use in instruction. Computing hardware and facility upgrade opportunities are explored at least once a year. E. Library Services Describe and evaluate the capability of the library (or libraries) to serve the program including the adequacy of the library’s technical collection relative to the needs of the program and the faculty, the 92 of 291 adequacy of the process by which faculty may request the library to order books or subscriptions, the library’s systems for locating and obtaining electronic information, and any other library services relevant to the needs of the program. The UW College of Engineering Library is a great resource for students, faculty and staff. The Collections and Resources available are listed here: http://www.lib.washington.edu/engineering/resources and include everything from ACM Depository Collection to conference proceedings to technical reports. Our faculty and students have access not only to UW materials, but they can order from any organization within the Interlibrary Borrowing program. There is also a dedicated librarian to answer discipline-specific questions. F. Overall Comments on Facilities Describe how the program ensures the facilities, tools, and equipment used in the program are safe for their intended purposes. (See the 2019-2020 APPM section I.E.5.b.(1).) Most of our computing equipment is generic computing. There is some electronics work, but it is primarily low voltage. In the rare case that a student might encounter a piece of equipment that could cause injury, there is warning signage posted and/or required supervision by trained course staff if that equipment is to be operated by students. 95 of 291 • Describe strategies used to retain current qualified faculty D.1: Hiring of new faculty Faculty hiring is managed through a Faculty Recruiting Committee (FRC), appointed by the Director. FRC is responsible for writing and publishing advertisements for open positions, evaluating applicants in collaboration with faculty in relevant areas, and ultimately choosing the slate of candidates to be invited for interviews. Hiring decisions are made by the faculty as a whole through a set of faculty meetings held throughout the recruiting season. Final offers are chosen through a vote of the entire faculty. Last year (2018) the department hired 9 new faculty members – 3 senior faculty members at the Associate Professor level, 4 junior faculty members at the Assistant Professor level, and 2 Lecturers. This year (2019), our search is not yet concluded at the time of this writing. We have made 9 Assistant Professor offers and 3 Lecturer offers. Currently 1 Assistant Professor offer has been accepted and 1 declined, while 1 Lecturer offer has been accepted and 2 declined. We will learn about the other 7 outstanding offers in the weeks ahead. The School has a highly collegial and collaborative work environment, which along with outstanding students at all levels, provides an exciting and enjoyable work atmosphere. Our positive culture is well known nationally and helps to attract and retain faculty. The department supports its faculty by providing outstanding staff for grant administration and technical support. Seattle is a highly desirable location given the technology ecosystem surrounding the department. We have close ties to Microsoft Research, Google Seattle, Amazon, and many other technical companies in the area; this provides opportunities for faculty and students for industrial collaboration, summer or sabbatical visits, student support and internships, etc. Of particular note is a close relationship with the Allen Institute for Artificial Intelligence which performs open research to benefit humanity and is directed by a long-time faculty member. Overall, since 2013, a five-year period, we have hired 35 total faculty while losing 8 tenure-track faculty (3 to industry, 2 to other institutions [Stanford, Berkeley], 2 to retirement, 1 to death) and 3 lecturers (2 to industry, 1 to another institution [Cal Tech]). At our size of 75 faculty FTE, we anticipate an average of 2 departures per year as a natural consequence of scale. Proactive retention raises and other salary-increasing mechanisms (such as “A/B salary” – see below) have helped to increase salaries to remain competitive. D.2 Strategies to Retain Current Qualified Faculty In addition to the CSE retention efforts stated above, the College of Engineering uses the following to retain current qualified faculty members by: A. Implementing Retention Salary Adjustments – The Dean may request retention salary adjustments for qualified faculty through the Office of the Provost. Retention salary adjustments receive case-by-case review by the Office of the Provost, and additional documentation may be required such as a current curriculum vitae or case specific details. 96 of 291 As a general principle, retention salary adjustments are expected to provide a minimum 5% salary increase. Generally, an individual may not receive a retention salary adjustment for a period of three years from the effective date of the most recent retention adjustment. B. Making opportunities available for A/B Retention Salary Adjustment - The fundamental purpose of the A/B Salary Policy for Faculty Retention is to ensure that sufficient mechanisms exist to support the retention of UW tenured and tenure-track faculty consistent with the University of Washington Faculty Salary Policy. An A/B salary is comprised of an annual base salary with an A salary component and a B salary component. The A component is the state-committed salary support associated with tenure that is matched with an institutional expectation of teaching, research, and service contributions. The B component is the balance of the base salary funded from non-state appropriated sources (e.g., grants, contract, and self-sustaining). The B component is contingent upon the faculty member’s ability to generate funding from grants, contracts, or other applicable sources. The University’s policies on A/B salaries are in flux and this opportunity may not be available going forward. E. Support of Faculty Professional Development Describe the adequacy of support for faculty professional development, how such activities such as sabbaticals, travel, workshops, seminars, etc., are planned and supported. At UW, sabbaticals are permitted every 7 years and are supported by providing 2/3s salary over three quarters. The department has very liberal policies with regard to faculty leaves to spend time in industry or to spinout department-developed technology (e.g., in startups). In general, we support faculty members’ requests for industrial interaction because we believe it enhances both our educational and research missions, creates new connections to industry, and gives faculty insight into important current problems faced by industry. In a time of industry boom, particularly in our region, it is also essential for faculty retention. CSE provides support for staff members, instructors, and students to travel to workshops, seminars, and meetings. We also support the creation of campus-wide technical communities in areas of importance to us. In particular, the eScience Institute and the Design, Use, Build (DUB) grassroots organization for HCI are strong campus entities to which we have provided substantial leadership. The University of Washington and the College of Engineering have extensive faculty professional development programs. Many of them focus on new faculty but some are for all faculty. The University of Washington's Faculty Fellows Program orients new faculty to the University campus community. The Program is facilitated by a number of campus educators, including those that have received campus-wide teaching awards. Presenters and facilitators actively 97 of 291 engage our new faculty members on a number of topics including, but not limited to, panel discussions with UW students, effective teaching methods and techniques for balancing the demands of successful teaching and research. The University of Washington's Royalty Research Fund awards grants to faculty of up to $40,000 to advance new directions in research, in particular: • in disciplines for which external funding opportunities are minimal; • for faculty who are junior in rank; • in cases where funding may provide unique opportunities to increase applicant's competitiveness for subsequent funding. Funded projects often lead to new creative activities or scholarly understandings, new scholarly materials or resources, and significant data or information that increase a faculty member's chances of obtaining new external funding. The University of Washington Provost's Office provides bridge funding to support faculty to span the gap in critical research programs. Faculty can receive up to $50,000 (with a required 1:1 match from the department or college, meaning up to $100,000) to help them maintain research productivity while they seek to obtain external funding for their labs. There are a number of additional faculty professional development programs run by the College of Engineering: • Center for Teaching & Learning (CTL) CTL supports the University of Washington, College of Engineering’s mission by taking a leadership role in developing and supporting engineering instructional excellence. The CTL faculty development program employs an integrated multi-pronged agenda for improving engineering learning and teaching, which includes working with individual faculty members, conducting teaching workshops and seminars, providing teaching resource materials, and active participation in strategic-level initiatives. The CTL approach to professional faculty development begins with meeting and resolving the immediate concerns of faculty members. Simultaneously CTL helps faculty members place their improvement efforts within a larger cycle of ongoing improvement, implementation, and assessment. Workshop topics and specific instructional development activities and resources are identified through close cooperation with engineering faculty members. CTL services are available to all faculty members in the College of Engineering. For more information on CTL services see the CTL description in Table D-4 Non-academic Support Units.