Strategic Academic Focusing Initiative

Our faculty-focused development of a strategic academic vision

Revision of 2020 vision for Electrical Engineering and Computer Science at UC Merced from March 1, 2014 - 9:30am

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Proposal Status: 
Principal Authors: 

EECS Core Faculty: Stefano Carpin, Miguel Carreira-Perpinan, Alberto Cerpa, YangQuan Chen, Ariel Escobar, Marcelo Kallmann, Shawn Newsam, David Noelle, Florin Rusu, Mukesh Singhal, Ming-Hsuan Yang.

EECS Affiliate Faculty: Changqing Li, Paul Maglio, Erik Rolland.

Executive Summary: 

The EECS program has already achieved significant research excellence. The 11 core and three affiliated faculty have brought over $7M in extramural funds; have been awarded four NSF CAREER Awards, one DOE Early Career Scientist and Engineer Award, and one Presidential Early Career Award for Scientists and Engineers; serve on the editorial boards of 24 high-impact journals; advise 33 mostly PhD graduate students; and have graduated 5 MS and 12 PhD students who have been placed in faculty, competitive postdoc, and industrial research positions. We will build on this strong foundation to reach a group of around 30 members by 2020 who will advise in excess of 120 graduate students, a significant contribution to UCM’s goal of enrolling 1,000. This growth will be achieved, in part, by strengthening the group’s EE component. Having strong EE research and education programs is critical for the continued growth of the School of Engineering.

Initiative Description: 

The EECS faculty envisions developing a full-fledged Electrical Engineering and Computer Science area of excellence at UC Merced. This plan has research and educational components instrumental to create the next great University of California campus.

On the research side, EECS will continue to build strength in the present themes, and break ground into new research areas as the field evolves and to adapt to future societal needs. We will build strength not only in core areas such as computer architectures, operating systems, networks, parallel/distributed systems, artificial intelligence, programming languages, software engineering, databases, machine learning, etc., but also in applied areas such as graphics, computer vision, robotics, image processing, cognitive science. Our vision is to build strength in key core and applied areas so that an assortment of multi-disciplinary collaborations can be established with other programs in the School of Engineering and other Schools in the University.

On the educational side, EECS aims at continue growing a robust graduate program in EECS and expanding the undergraduate program to include an Electrical Engineering offering. This offering should be launched after an adequate expansion of the faculty and after the first buildings of the new development phase become available. We maintain that these steps are essential to achieve the objective set forth in the 2020 vision for UC Merced.

Now more than ever, researchers in EECS face research challenges with the potential to radically change our every day life. These include the development of a fully autonomous intelligent computer system/robot, development of an absolutely secure system, development of computer algorithms to perform analysis of huge data sets, design of self-healing robust computer networks, development of accurate face-recognition systems, development of a safe, secure Cloud system, etc. Each of these challenges has huge societal and economical impacts.

These research problems are aligned with research currently done at UC Merced, but to achieve national and international excellence a significant, targeted growth is necessary. If UC Merced does not invest in these areas, our institution will be a spectator rather than a driving force.

To this end, at least 30 EECS faculty members are needed and we foresee that the whole group could reach 50 units when counting affiliate faculty from other programs or schools. With a conservative estimate of 4 graduate students for each core member, the graduate program would easily exceed 120 students. This target number will contribute to achieving the institutional goal of 1000/10% graduate students by 2020. Evidently, to achieve this size it will be necessary to allocate appropriate resources to attract top faculty and the best students. These include: infrastructures with adequate space for research and graduate education (see appendix for a tentative list); competitive startup packages with flexible terms of use; state-of-the-art technology in equipments, computer hardware and software, networks, and interfaces; library resources including broad selection of a research-oriented collection books and journals in EECS. With the ever-increasing competition for highly qualified graduate students, to successfully compete with other institutions it will be necessary to create attractive multi-year financial offers.

Eventually, with the growth in size, it can be anticipated the EECS will form its own bylaw 55 unit (aka department). This will require several staff members: couple of secretaries, a full time undergraduate advisor, etc. In addition to 120 graduate students, we anticipate around 900 students in the undergraduate programs in Electrical Engineering and Computer Science (see attached impact metric worksheet).

Currently, EECS is a growing program and intends to expand steadily for many years. By 2020, we would like the EECS program to have a strong EE component and we aspire to be like similar program at UCSD, UCI, Penn State University, Purdue University, and SUNY Stony Brook.

In conclusion, the projected growth of EECS is instrumental to implement UCM vision growth (by 2020, 10000 students with 10% graduate students). Projected growth in the size of the graduate program will be healthy for the research productivity and PhD out of UCM. The proposed increase in graduate program will greatly strengthen the EE and CSE undergraduate programs in many ways, like providing undergraduate more opportunities for participation in research projects and internship programs. In addition, a strong graduate program will create a pool of qualified teaching assistants. A strong EECS program will have a great potential for significant cross-disciplinary research activities with other programs on the campus.

 

Appendix

Shared facilities necessary to implement the 2020 EECS vision.

Cluster Core Facility:

-       Shared cluster among all users wanting to experiment in the high performancecomputing domain. The model should be flexible and open enough such that people could contribute hardware and get CPU time, as well as pay as you use. 

Electronics Manufacturing Core Facility:

-       Small to medium scale jobs, dual layer boards, thousands of components maximum.

-       Design and build electronic boards.  CNC Router, Laser and/or Chemical processes.

-       Automatic assembly of components (chips, resistors, capacitors, etc.) and boards.  Pick & place machine.

-       Manual soldering station for small jobs.

-       Computer workstations with all the software installed to run the machines above.

Signal and Systems Core Facility:

-       Measurements of signals from 0 to 1 GHz in time and frequency.

-       Instrumentation: Digital and Analog oscilloscopes, logic analyzers, real-time digital storage oscilloscopes, spectrum analyzers, RF training system, DDS function generator, analog function generators, other signal sources, programmable linear DC power supply, programmable switched DC power supply, AC power supply, DC electronic load, LCR multimeter, digital multimeter, electrical safety tester, special application instruments.

-       Workbenches for people to use the instruments and work in situ.

RF Testing Core Facility:

-       RF Anechoic Chamber and associated measuring instrumentation.

-       Dry space with heavy electromagnetic shielding and vibrations requirements.

Programmable Hardware Core Facility:

-       Field-programmable Gate Arrays (FPGAs), Field-programmable Analog Arrays (FPAAs), Complex Programmable Logic Devices (CPLDs), Programmable System-on-Chip (PSoC), etc.

Impact Metrics: