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Computer EngineeringUCSC Baskin School of Engineering

Richard Hughey, Chair

Alexandre Brandwajn, Graduate Director Tracy Larrabee, Undergraduate Director

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Agenda• 12:45-1:00 Assistive Technology Demo

– Roberto Manduchi• 1:00-1:45 Lunch, Introductions, Overview & Discussion

– Richard Hughey• 1:45-2:00 Research Talk

– William Dunbar– Feedback Control Applied to the Nanopore

• 2:15-2:45 Internships & Career Discussion– Richard Hughey, Brad Smith

• 2:45-3:30 Undergraduate Program and Accreditation– Joel Ferguson

• 4:00-??? Senior Design Contest

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Mission

Computer Engineering focuses on the design, analysis and application of computers and on their applications as components of systems. The UCSC Department of Computer Engineering sustains and strengthens its teaching and research program to provide students with inspiration and quality education in the theory and practice of computer engineering.

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Computer Engineering Programs

• BS, BS/MS, – 175 majors/premajors

• 2 Minors– Comp. Engineering– Comp. Technology

• MS, PhD– 70 graduate students– Down somewhat– Many students advised for

other programs.

• MS in CE/Network Engineering– Part-time at SVC

Software Systems

Network Systems

Digital Hardware

Computer Systems

Robotics and Control

Undergraduate Concentrations

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New Courses• Undergraduate

– Introduction to Autonomous Systems (8, Fall)– Assistive Technology & Universal Access (80A,W)– Hands-On Computer Engineering (1, FWS, in third

year)– Human-Computer Interaction (W)

• Graduate– Applied Graph Theory (277, Fall)– Autonomous Control sequence (240 F, 241 W) – Unix networking internals (258, Fall)– Network security (253, Spring)– Graduate Technical Writing (285, Spring)– Human Factors (Spring)

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Bioengineering B.S.

• BME, CE, EE, MCD– Multi-Department, Multi-Division Program

• Approved Spring 2007

• One of the most popular engineering majors

• Nationally, 40% of bioengineering B.S. graduates are women

• First real class will be Fall 2008

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Bioengineering B.S.

• LD Breadth (2 courses, 10 units)– Bioethics, Assist Tech, Clinical Health Care

• Basic Science (10 courses, 59 units)– Physics (3), Chem (3), Bio (2), Orgo (1), Bioch (1)

• Math (6 courses, 33 units)– Standard, Biostat (AMS7/L), EE103

• Engineering (4 courses, 24 units)– Programming, Tech Writing, Circuits

• 2 New Core Classes (2 courses, 14 units)– Biomolecular Mechanics, Physiological Systems

• 4 Electives (4 courses, 20 units)• Senior Design 123A/B (2 courses, 12 units)

Total: 30 courses, 172 units

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New Communities

• Engineering Honor Society– Expected to be installed as Tau Beta Pi in Spring 2007 – Many service projects

• eWomen– Graduate group– Lunches, lectures, and outreach– Baskin School third in nation in percentage of MS

degrees awarded to women (44.2% in 2004-5, Prism 1/2007)

• SURF-IT – Summer undergraduate research program

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Computer Engineering Research

• Computer System Design, CAD of VLSI

• Networks

• Digital Media and Sensor Technology

• Embedded and Autonomous Systems

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Computer System Design/CAD of VLSI

• Recent Accomplishments– Sun Center of Excellence in OpenSPARC

– Redesign of undergrad/grad FPGA/VLSI sequence

– New Assist. Prof.: Matthew Guthaus

• FacultyPak ChanF. Joel Ferguson Tracy Larrabee

Martine Schlag Matthew Guthaus

Alexandre Brandwajn Andrea Di Blas

Jose Renau Richard Hughey

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Matthew (Matt) Guthaus• PhD University of Michigan

• Experience at IBM Research and ASIC Consulting with National Semiconductor

• Current Research– VLSI Physical Design Automation

– Robust/Variation-Aware Circuit Design

– Embedded Systems-on-Chips

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Computer Networks• Accomplishments

– JJ leads a 7-university MURI • And collaborates on 3 more.

– Anujan, Finisar, Infinera, Internet2, Level 3 Communications demo 100GbE

– Cisco Networking Lab Established– New Adj. Assist. Prof. Brad Smith

• Faculty– J.J. Garcia-Luna-Aceves, Katia Obraczka,

Brad Smith, Anujan Varma

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Networks Lab• Graduate and undergraduate training

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Digital Media and Sensor Technology

• Video data processing and communication, camera networks, assistive technology

• Accomplishments– New assistive technology grants

– New faculty member Sri Kurniawan (HCI)

• Faculty:– Sri Kurniawan, Roberto Manduchi, Pat Mantey,

Hai Tao

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Sri Kurniawan

• Ph.D. Industrial and Manufacturing Engineering, major in HCI, minor in Computer Science, Wayne State University

• MPhil in Human Factors, BEng in Electronics

• Joining UCSC from University of Manchester

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Research interest: combining HCI and AT

Interaction

Soc, CS, Psy

Input devices

CS, EE, AT

• Mobile phones, interactive TV, Internet and older persons

• Entertainment software for children with cognitive disabilities

• Blind people’s interaction with document formatting and layout

• Joystick-operated screen magnifier

• Non-speech vocal input

• Performance and behavioural models + evaluation framework of assistive input devices

Collab Collab

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Research Approaches

• Analysis:– Qualitative: content analysis, behavioural models– Quantitative: Statistical analyses (ANOVA, factor

analysis, structural equation modelling), Fitts’ Law, cognitive models

• Measurement: – Subjective: focus group discussions, Delphi

interview, contextual inquiry– Objective: psychometrics tests, controlled & in-

context experiments, questionnaire, ethnographic study

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Quantitative approach: model of older people‘s reaction time

using stylus

Qualitative approach: Behavioural model of older people using stylus for point-and-click task

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Keyboards: mapping,

gesture, morse

Non-Speech Verbal Input: Controlling keyboards and cursor using humming

Tetris

Cursor control through pitch inflection

• Tested with users with various characteristics (older users, people with motor impairment, teenagers, etc)

• Using established HCI evaluation techniques

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Joystick-operated screen magnifiers

Screen magnifier modes

Pluscolour inversion, smoothing,

magnification level (x, y, both).

Low-cost commercial joystick

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Embedded and Autonomous SystemsComputer systems that interface the physical world to solve

problems. • Accomplishments

– Redesign of graduate and undergraduate robotics and controls courses and concentration

– Plans for B.S. in Mechatronic Engineering in 3-4 years– NIH retraining grant

FacultyLuca de Alfaro Gabriel Elkaim William Dunbar

2007-8 Recruitment in Autonomous Systems (may be AT)2009-10 Recruitment in Autonomous Systems (may be AT)20010-11 Recruitment in Autonomous Systems (may be AT)

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Computer Engineering Research

• By the numbers…..• 18 T/TT faculty, 6 additional faculty• $4M Gifts & Awards, 2005-6, 20% growth

– $250,000/FTE among 16 LR faculty in 2005-6– Total was our goal for 2008– Per capita was our goal for 2010

• Including new CAREER and K25 grants• Graduated 19 MS, 7 PhD students

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Hiring Foci

• Complete core areas– Maximum impact with large groups and multi-PI grants

• Research emphasis in assistive technologies– Attacking one of 4 technological challenges the Engineer

of 2020 faces– Opens up NIH funding– A component of bioengineering program

• Graduate program in autonomous control– Graduate group structure

• Complements AMS plans in control– Will lead to mechanical-related engineering degrees

• Help expand to a full-service School of Engineering

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Hiring Plan

• 2007-8 – Autonomous Systems (potential AT)

• Tenured leader to head graduate group in control

• 2008-9– Networks

• Assistant-Associate Professor (rising star)

• 2009-10– Autonomous Systems/Embedded Systems (possible AT)

• 2010-11– Autonomous (possible AT)

Autonomous Systems will enable creation of graduate and undergraduate programs in Mechatronic, Mechanical or Micromechanical Engineering (depending on hires)

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Recent Practices in CE• Concentration on the Frosh Experience

– Keep students engaged with engineering throughout their years

• Publications and publicity– Posters and brochures about programs– We should have an SOE-wide plan with budget

and expertise.

• Building communities

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Diversity and Retention• Graduate Student & Faculty

– eWomen– SURF-IT Summer Research Program

• Undergraduate– CE1, CE8, CEFULS, better tools for monitoring

students, careful selection of faculty for introductory courses

– Rethink (with EE & AMS) the path through math and circuits

• Both– Develop areas such as Assistive

Technology/Bioengineering that have higher diversity than EECS.

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More Numbers

AY00 AY05 %Change

LR Faculty 13 16 +23%

Enrollments 289 330 +14%

Grants/Gifts 1,200,000 4,000,000 +233%

Degrees 61 67 +10%

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2004-5 Research SupportMany of these awards have unlisted co-PIs, many projects also unlisted as co-PI)

Funds and gifts received July 2004 through June 2005

91,429 De Alfaro, Luca NSF CAREER: Structured Design of Embedded Software

150,000 Larrabee, Tracy NSF Fault Diagnosis for Yield Improvement and Silicon Debug25,000 Varma, Anujan UARC Optical Data Router (ODR) Architecture Design and Evaluation

100,000 Tao, Hai NSF CAREER: Elements in Solving the Multiple Object Tracking Problem

134,311 Garcia, J.J UCSD MURI: Space-Time Processing for Enhanced Mobile Ad-Hoc Wireless Networking

139,267 Hughey, BME NIH/NIGMS Predoctoral Bioinformatics Training at UCSC

164,183 Manduchi, Roberto NASA/Ames Managing the Information Flow in a Network of Visual Sensors

575,000 Garcia-Luna, Obraczka, Sadjadpour

US Army/AROD DAWN: Dynamic Ad-hoc Wireless Networking

20,000 Renue, Jose U Illinois HPCS Complexity Management

23,798 De Alfaro, Luca UARC Timed Interfaces for Real-Time Software

26,018 Elkaim, Gabriel UARC Metasensor Technology - High Performance GNC Using Low-Cost Sensors

526,191 Manduchi, Roberto NSF Sensors: Exploring the World with a Ray of Light: An Environmental Sensor for the Blind

6,457 Obraczka, Katia UC/MICRO Energy-Efficient Medium Access Control for Wireless Sensor Networks

9,461 Obraczka, Katia UC/MICRO Secure and Robust Routing for Multi-Hop Ad Hoc Networks

9,375 Ferguson, Joel UCOP MEP Scholarships51,000 Obraczka, Katia NSF Supplement to Collaborative Research: A Hybrid Systems Framework for Scalable Analysis and Design of

Communciation Networks360,021 Elkaim, Dunbar NSF MRI: Development of an Autonomous Robotic Vehicle Instrument (ARVIN)300,000 Hughey, Manduchi NSF REU Site: REU in Information Technology at the UCSC Baskin School of Engineering

80,000 Renue, Jose NSF CAREER: Understanding, Estimating, and Reducing Processor Design Complexity

47,328 Renue, Jose UARC Fault Tolerant FPGA System on a Chip

34,518 Dunbar, William UARC Adaptive Optimal Air Traffic Routing: Improving Robustness to Weather Uncertainty by Leveraging Forcasts in Real-Time

143,015 Garcia, J.J US Army/AROD Instrumenting DAWN

32,000 Obraczka, Smith CISCO Systems, Gift: Networks laboratory

14,500 Obraczka Wionics Research Gift: Networks research3,000

21,000deAlfaroTao

Microsoft CorpNEC

GiftGift

850,000 Elkaim SVORA Gift: Silicon Valley Overland Robotics Association , Overbot Autonomous Vehicle

3,875 Computer Engineering Various Donors Gifts

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Agenda• 12:45-1:00 Assistive Technology Demo

– Roberto Manduchi• 1:00-1:45 Lunch, Introductions, Overview & Discussion

– Richard Hughey• 1:45-2:00 Research Talk

– William Dunbar– Feedback Control Applied to the Nanopore

• 2:15-2:45 Internships & Career Discussion– Richard Hughey, Brad Smith

• 2:45-3:30 Undergraduate Program and Accreditation– Joel Ferguson

• 4:00-??? Senior Design Contest

Biophysics Laboratory, Biomolecular Science & Engineering, U.C. Santa Cruz

Dynamics and Control Laboratory,Computer Engineering, U.C. Santa Cruz

Research Supported by NIH NHGRI grant K25 HG004035-01

Feedback Control Applied to the Nanopore

General Definitions:Feedback Control - a tool to make dynamic systems self-regulating (automated).

Control Logic - hardware/software that collects system measurements, and converts them into commands to influence the system.

Traditional Example: Cruise Control

System - the car

Measurement signal - car speed (V)

Command signal - throttle (T)

Objective - automate T so that V remains at a constant desired value (Vdes)

Control Logic - T = Tstat + Tdyn

Tdyn = a[Vdes-V ], a>0

too slow accelerate, too fast decelerate

roadcar

V

T

time

time

Vdes

Feedback Control Enables Self-Regulation

Feedback Controlled Nanopore: Automating Detection and Fast Voltage Reaction

Control logic programmed in a finite state machine (in SW), and implemented with a field-programmable gate array (HW).

Control Logic programmed using a Finite State Machine (FSM) in software

FSM made up of states, transitions between states, and actions.Cruise Control Revisited:

Control Logic: Tdyn = a[Vdes-V ], a>0 roadcar

Control Logic in an FSM:

States - status of V

Transitions - based on value of V relative to Vdes

Actions - assign a value to Tdyn for each state

FPGA Combines Speed and Flexibility for Fast Signal Monitoring and Voltage ControlFPGA – multiple tasks in parallel with no overheadPC with DAQ card – tasks are performed in series with overhead of OS

Images taken from: apple.com, fluke.com, ni.com, and xilinx.com

Speed

Fle

xibi

lity

Manual Signal Measurement DAQ Hardware

Computer with Operating System FPGA Hardware

More

Less

Field-programmable Gate Array (FPGA) Hardware Enables Fast Control Logic Execution

Recent Results Demonstrate Detection and Manipulation of Enzyme/DNA complex “states”. (soon to be submitted to Nature)

Career and Internship Discussion

• Exit interviews– Students would like more career-fair

opportunities for engineers• The campus fair only attacts a handful of

technology companies

– Students would like more internships• Many graduate students find internships

through faculty connections• Fewer undergraduates do

Careers and Internships

• UCSC Career Fair in Silicon Valley?

• Career Mingles or Panels?

• Other enticements for companies?

Careers and Internships

• Formal Internship Programs– ISM/Seagate– CE/Cisco possibility– Other connections?

Careers and Internships

• Developing Faculty Relationships– Group company visits/research days?– SVC showcase?– Other ideas?

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Accreditation Issues

Tracy Larrabee

Undergraduate Director

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Mission

• Computer Engineering focuses on the design, analysis and application of computers and on their applications as components of systems. The UCSC Department of Computer Engineering sustains and strengthens its teaching and research program to provide students with inspiration and quality education in the theory and practice of computer engineering.

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Objectives

• The UCSC Computer Engineering program prepares graduates for a rewarding career in engineering. UCSC Computer Engineering graduates will have a thorough grounding in the principles and practices of Computer Engineering and the scientific and mathematical principles upon which they are built; they will be prepared for further education (both formal and informal) and for productive employment in industry.

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How well prepared do you feel you are to apply your knowledge of mathematics, science, and engineering?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q1: Apply STEM

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How well prepared do you feel you are to design and conduct experiments?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q2: Design Experiments

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How well prepared do you feel you are to analyze and interpret data?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q3: Analyze Data

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How well prepared do you feel you are to design a system, component or process to meet desired needs?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q4: Design System

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How well prepared do you feel you are to function on multi-disciplinary teams?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q6: Multidisciplinary Team

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How well prepared do you fel you are to identify, formulate, and solve engineering problems?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q7: Engineering Problems

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3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

in writing (CE)

orally (CE)

interpersonally (CE)

in writing (EE)

orally (EE)

interpersonally (EE)

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How well prepared do you feel you are to communicate effectively in writing

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q7A: Written

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How well prepared do you feel you are to communicate effectively in oral presentations

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q7B: Oral

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How well prepared do you feel you are to communicate effectively in interpersonal communications

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q7C: Interpersonal

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How well prepared do you feel you are to understand the impact of engineering solutions in a global/societal context?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q8: Impact of Engineering

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How well prepared do you feel you are to use the techniques, skills and modern engineering tools necessary

for engineering practice?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q9: Skills and Tools

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How well prepared do you feel you have an understanding of professional and ethical responsibility?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q10: Professional and Ethical

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Do you feel you recognize the need to engage in life-long learning?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q11: Life-long Learning

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Do you feel you have a knowledge of contemporary issues as they relate to engineering?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q12: Contemporary Issues

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How would you rate Faculty advising?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q13: Faculty Advising

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How would you rate the advising you got from the Undergraduate Advising Office?

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

2003 Average 2004 Average 2005 Average 2006 Average

CE

EE

Q14: Staff Advising

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Computer Engineering

3.03.23.43.63.84.04.24.44.64.85.0

Q1 Q2 Q3 Q4 Q5 Q6 Q7a Q7b Q7c Q8 Q9 Q10 Q11 Q12 Q13 Q14

2003 2004 2005 2006 2007

Q1 Apply STEM Q5 Multidisc. Teams Q7c Interpersonal Comm. Q11 Life-long Learning

Q2 Design Experiments Q6 Engr Problems Q8 Impact of Engineering Q12 Contemporary Issues

Q3 Analyze Data Q7a Written Comm. Q9 Skills and Tools Q13 Faculty Advising

Q4 Design System Q7b Oral Comm. Q10 Professional, Ethical Q14 Staff Advising