University of California Santa Barbara Catalog

Department of Electrical and Computer Engineering - Building 380, Room 101
Telephone: (805) 893-2269 or (805) 893-8292
Web site: www.ece.ucsb.edu
Department Chair: Luke Theogarajan
Vice Chair of Graduate Studies: To be determined
Vice Chairs of Undergraduate Studies: Shiv Chandrasekaran (EE), Yogananda Isukapalli (CE)

Overview

Electrical and Computer Engineering is a broad field encompassing many diverse areas such as computers and digital systems, control, communications, computer engineering, electronics, signal processing, electromagnetics, electro-optics, physics and fabrication of electronic and photonic devices. As in most areas of engineering, knowledge of mathematics and the natural sciences is combined with engineering fundamentals and applied to the theory, design, analysis, and implementation of devices and systems for the benefit of society.

The Department of Electrical and Computer Engineering offers programs leading to the degrees of bachelor of science in electrical engineering or bachelor of science in computer engineering. (Please see the “Computer Engineering” section for further information.) The undergraduate curriculum in electrical engineering is designed to provide students with a solid background in mathematics, physical sciences, and traditional electrical engineering topics as presented above. A wide range of program options, including computer engineering; microwaves; communications, control, and signal processing; and semiconductor devices and applications, is offered. The department’s Electrical Engineering undergraduate program is accredited by the Engineering Accreditation Commission of ABET, http://www.abet.org. It is one of the degrees recognized in all fifty states as leading to eligibility for registration as a professional engineer.

Graduate studies leading to the M.S. and Ph.D. degrees in Electrical and Computer Engineering are offered in three major areas of specialization: computer engineering; communications, control, and signal processing; and electronics and photonics.
The undergraduate major in Electrical Engineering prepares students for a wide range of positions in business, government, and private industrial research, development, and manufacturing organizations. The graduate programs offer educational opportunities at an advanced level, leading at the M.S. level to increased career opportunities in the foregoing positions, and at the Ph.D. level to careers in research and teaching and positions of professional leadership.

Students who complete a major in electrical engineering may be eligible to pursue a California teaching credential. Interested students should consult the credential advisor in the Graduate School of Education.

Under the direction of the Associate Dean for Undergraduate Studies, academic advising services are jointly provided by advisors in the College of Engineering, as well as advisors in the department. Students who plan to change to a major in the department should consult the ECE student office. Departmental faculty advisors are assigned to students to assist them in choosing senior elective courses.

Counseling is provided to graduate students through the ECE graduate advisor. Individual faculty members are also available for help in academic planning.

Mission Statement

The Department of Electrical and Computer Engineering seeks to provide a comprehensive, rigorous and accredited educational program for the graduates of California’s high schools and for postgraduate students, both domestic and international. The department has a dual mission:

Education. We will develop and produce excellent electrical and computer engineers who will support the high-tech economy of California and the nation. This mission requires that we offer a balanced and timely education that includes not only strength in the fundamental principles but also experience with the practical skills that are needed to contribute to the complex technological infrastructure of our society. This approach will enable each of our graduates to continue learning throughout an extended career.
Research: We will develop relevant and innovative science and technology through our research that addresses the needs of industry, government and the scientific community. This technology can be transferred through our graduates, through industrial affiliations, and through publications and presentations.

We provide a faculty that is committed to education and research, is accessible to students, and is highly qualified in their areas of expertise.

Educational Objectives

The educational objectives of the Electrical Engineering Program identify what we hope that our graduates will accomplish within a few years after graduation.

We expect our graduates to make positive contributions to society in fields including, but not limited to, engineering.
We expect our graduates to have acquired the ability to be flexible and adaptable, showing that their educational background has given them the foundation needed to remain effective, take on new responsibilities and assume leadership roles.
We expect some of our graduates to pursue their formal education further, including graduate study for master’s and doctoral degrees.

Program Outcomes

The EE program expects our students upon graduation to have:

Acquired strong basic knowledge and skills in those fundamental areas of mathematics, science, and electrical engineering that are required to support specialized professional training at the advanced level and to provide necessary breadth to the student’s overall program of studies. This provides the basis for lifelong learning.
Experienced in-depth training in state-of-the-art specialty areas in electrical engineering. This is implemented through our senior electives. Students are required to take two sequences of at least two courses each at the senior level.
Benefited from imaginative and highly supportive laboratory experiences where appropriate throughout the program. The laboratory experience will be closely integrated with coursework and will make use of up-to-date instrumentation and computing facilities. Students should experience both hardware-oriented and simulation-oriented exercises.
Experienced design-oriented challenges that exercise and integrate skills and knowledge acquired in several courses. These may include design of components or subsystems with performance specifications. Graduates should be able to demonstrate an ability to design and conduct experiments as well as analyze the results.
Learned to function well in teams. Also, students must develop communication skills, written and oral, both through team and classroom experiences. Skills including written reports, webpage preparation, and public presentations are required.
Completed a well-rounded and balanced education through required studies in selected areas of fine arts, humanities, and social sciences. This provides for the ability to understand the impact of engineering solutions in a global and societal context. A course in engineering ethics is also required of all undergraduates.

Laboratory Facilities

In addition to formal classroom lectures and studies, the department places strong emphasis on the inclusion of laboratory and computational experience in a student’s program of study. To support this experience, the department and the campus maintain an extensive complement of relevant laboratory and computational facilities. Instructional laboratory facilities are available to support undergraduate courses in circuits, electronics, digital systems, communications, control, signal and image processing, microwaves, and solid-state device fabrication. Students may access microcomputers and workstations in the Microcomputer Laboratory or the College of Engineering ECI and CAD Laboratories.

The Department also maintains modern well-equipped facilities for research in communications, control, signal processing, image processing, scientific computation, VLSI design and testing, computer architecture, fault-tolerant computing, microwaves, optoelectronics, and solid state microelectronics. All research laboratories include or have access to modern computer facilities. Workstations in the various research laboratories have access via a local area network to a wide range of computing resources. The solid state research facilities include laboratories for crystal growth by molecular beam epitaxy and metal-organic CVD, microfabrication and processing, analog and digital integrated circuit design, and compound-semiconductor optoelectronic device and materials research.

Faculty

Mahnoosh Alizadeh, PhD, UC Davis, Associate Professor
Specialization: Smart Power Grids, Demand Response and Renewable Energy Integration, Cyber-Physical Systems, Network Control

Kaustav Banerjee, PhD, UC Berkeley, Professor
Specialization: high performance VLSI and mixed signal system-on-chip designs and their design automation methods; single electron transistors; 3D and optoelectronic integration

Ilan Ben-Yaacov, PhD, UC Santa Barbara, Teaching Professor
Specialization: semiconductor device physics and electronic devices, power electronics, engineering education

Dan Blumenthal, PhD, University of Colorado, Professor
Specialization: fiber-optic networks, wavelength and subcarrier division multiplexing, photonic packet switching, signal processing in semiconductor optical devices, wavelength conversion, microwave photonics

Forrest Brewer, PhD, University of Illinois, Professor
Specialization: VLSI and computer system design automation, theory of design and design representations, symbolic techniques in high level synthesis

Jim Buckwalter, PhD, California Institute of Technology, Professor
Specialization: RF and millimeter-wave integrated circuits and systems, optoelectronic integrated circuits, energy-efficient circuits, CMOS and III-V integrated circuit processes

Katie Byl, PhD, Massachusetts Institute of Technology, Associate Professor
Specialization: robotics, autonomous systems, dynamics, control, manipulation, locomotion, machine learning

Kerem Camsari, PhD, Purdue University, Associate Professor
Specialization: Nanoelectronics, Spintronics, Emerging Technologies for Computing, Digital and Mixed-signal VLSI, Neuromorphic and Probabilistic Computing, Quantum Computing, Hardware Acceleration

Shivkumar Chandrasekaran, PhD, Yale University, Professor
Specialization: numerical analysis, numerical linear algebra; scientific computation

Steven Denbaars, PhD, University of Southern California, Professor
Specialization: metalorganic vapor phase epitaxy, optoelectronic materials, compound semiconductors, indium phosphide and gallium nitride, photonic devices
Joint Appointment: Materials

Joao Hespanha, PhD, Yale University, Professor
Specialization: hybrid and switched systems; multi-agent control systems; game theory; optimization; distributed control over communication networks also known as networked control systems; coordination and control of groups of unmanned air vehicles; the use of vision in feedback control; and network security

Yogananda Isukapalli, PhD, UC San Diego, Teaching Professor
Specialization: Low power hardware design, Multi-antenna wireless communications, Transmit beam forming, Vector quantization, Performance analysis of communication systems

Haewon Jeong, PhD, Carnegie Mellon University, Assistant Professor
Specialization: Machine Learning, Ethical AI, Responsible Computing, Information Theory, Large-scale Distributed Computing

Jonathan Klamkin, PhD, UC Santa Barbara, Professor
Specialization: Integrated Photonics, Silicon Photonics, Optical Communications, Nanophotonics, Microwave Photonics, Compound Semiconductors, Photonic Integration Techniques, Electronic-photonic Integration

Hua Lee, PhD, UC Santa Barbara, Professor
Specialization: image system optimization, high-performance image formation algorithms, synthetic-aperture radar and sonar systems, acoustic microscopy, microwave nondestructive evaluation, dynamic vision systems

Peng Li, PhD, Carnegie Mellon University, Professor
Specialization: Integrated circuits and systems, learning algorithms and circuits for brain-inspired computing, electronic design automation, computational brain modeling, hardware machine learning systems

Upamanyu Madhow, PhD, University of Illinois, Urbana, Professor
Specialization: spread-spectrum and multiple-access communications, space-time coding, and internet protocols

B. S. Manjunath, PhD, University of Southern California, Professor
Specialization: image processing, computer vision, pattern recognition, neural networks, learning algorithms, content based search in multimedia databases

Tobia Marcucci, PhD, Massachusetts Institute of Technology, Assistant Professor
Specialization: Convex and Combinatorial Optimization, Robotics, Motion Planning

Jason Marden, PhD, UC Los Angeles, Professor
Specialization: Feedback Control and Systems Theory; Game Theoretic Methods for Coordination of Large Scale Distributed Systems; Application to Distributed Traffic Routing, Dynamic Resource Allocation, Queueing Systems, and Sensor Networks

Nina Miolane, PhD, INRIA/Stanford University, Assistant Professor
Specialization: Geometric Statistics, Geometric Deep Learning, Topological Deep Learning, Equivariant Deep Learning, Shape Analysis, Computational Medicine, Theoretical Neuroscience, Computational Neuroscience

Umesh Mishra, PhD, Cornell University, Professor
Specialization: high-speed transistors, semiconductor device physics, quantum electronics, wide band gap materials and devices, design and fabrication of millimeter-wave devices, in situ processing and integration techniques

Galan Moody, PhD, University of Colorado-Boulder, Associate Professor
Specialization: Quantum Photonics; Nanoscale Quantum Systems and Devices including Quantum Dots and 2D Materials; Quantum Light Generation, Manipulation, and Detection; Hybrid Quantum Systems; Valleytronics

Yasamin Mostofi, PhD, Stanford University, Professor
Specialization: RF sensing, robotics, wireless systems, multi-agent systems, mobile sensor networks

Chris Palmstrom, PhD, Leeds University, Professor
Specialization: atomic level control of interfacial phenomena, in-situ STM, surface and thin film analysis, metallization of semiconductors, dissimilar materials epitaxial growth, molecular beam and chemical beam epitaxial growth of metallic compounds
Joint Appointment: Materials

Behrooz Parhami, PhD, UC Los Angeles, Professor
Specialization: parallel architectures and algorithms, computer arithmetic, computer design, dependable and fault-tolerant computing

Ramtin Pedarsani, PhD, UC Berkeley, Associate Professor
Specialization: information and coding theory, machine learning, applied probability, network control, transportation systems, game theory

Yao Qin, PhD, UC San Diego, Assistant Professor
Specialization: Machine Learning, Computer Vision, Multi-modality Modeling, Robustness in Healthcare

Lawrence R. Rabiner, PhD, Massachusetts Institute of Technology, Professor
Specialization: digital signal processing, intelligent human-machine interaction, speech processing and recognition, telecommunications

Mark Rodwell, PhD, Stanford University, Professor
Specialization: heterojunction bipolar transistors, high frequency integrated circuit design, electronics beyond 100 GHz

Kenneth Rose, PhD, California Institute of Technology, Professor
Specialization: information theory, source and channel coding, image coding, communications, pattern recognition

Loai Salem, PhD, UC San Diego, Assistant Professor
Specialization: power management integrated circuits, power electronics using new devices/passives, low-power mixed-signal circuits

Clint Schow, PhD, University of Texas, Professor
Specialization: Optoelectronic/Electronic Co-Design and Integration, Equalization Techniques for High-Speed Optical Links, Photonic Switching, Optoelectronic Devices, Integrated Transceiver Packaging

Jon Schuller, PhD, Stanford University, Professor
Specialization: nanophotonics, organic optoelectronics, plasmonics, metamaterials

Pradeep Sen, PhD, Stanford University, Professor
Specialization: computer graphics and imaging

Spencer Smith, PhD, UC Los Angeles, Professor
Specialization: neuroengineering, neuroscience, optics, imaging, visual processing, neuronal circuitry

Dmitri Strukov, PhD, Stony Brook University, Professor
Specialization: hybrid circuits, nanoelectronics, resistance switching devices, memristors, digital memories, programmable circuits, bio-inspired computing

Andrew Teel, PhD, UC Berkeley, Professor
Specialization: control design and analysis for nonlinear dynamical systems, input-output methods, actuator nonlinearities, applications to aerospace problems

Luke Theogarajan, PhD, Massachusetts Institute of Technology, Professor
Specialization: low-power analog VLSI, biomimetic nanosystems, neural prostheses, biosensors, block co-polymer synthesis, self-assembly, and microfabrication

Niels Volkmann, PhD, Max-Planck Institute & University of Hamburg, Professor
Specialization: development and application of innovative New Computational, Artificial Intelligence, and Data Science Tools to bridge information between the Atomic and Cellular Scales, covering more than six orders of magnitude from Ångstroms to tens of microns
Joint Appointment: Interdisciplinary Program in Quantitative Biosciences; Biological Engineering

Li-C. Wang, PhD, University of Texas, Austin, Professor
Specialization: design verification, testing, computer-aided design of microprocessors

Qian Yu, PhD, University of Southern California, Assistant Professor
Specialization: Information Theory, Machine Learning Theory, Distributed Computing

Zheng Zhang, PhD, Massachusetts Institute of Technology, Professor
Specialization: Photonic, Electronic, and MEMS Design Automation; Modeling and Verification of Robots & Autonomous Driving; High-Dimensional Data Analysis and Machine Learning; Magnetic Resonance Imaging (MRI)

Mahnoosh Alizadeh, PhD, UC Davis, Associate Professor
Specialization: Smart Power Grids, Demand Response and Renewable Energy Integration, Cyber-Physical Systems, Network Control

Ilan Ben-Yaacov, PhD, UC Santa Barbara, Teaching Professor
Specialization: semiconductor device physics and electronic devices, power electronics, engineering education

Emeriti Faculty

Rod Alferness, PhD, University of Michigan

John Bowers, PhD, Stanford University
Joint Appointment: Materials; Technology Management Program

Steve Butner, PhD, Stanford University

Kwang-Ting Cheng, PhD, UC Berkeley

Larry Coldren, PhD, Stanford University
Joint Appointment: Materials

Nadir Dagli, PhD, Massachusetts Institute of Technology

Jorge Fontana, PhD, Stanford University

Allen Gersho, PhD, Cornell University

Jerry Gibson, PhD, Southern Methodist University

Glenn Heidbreder, D Eng, Yale University

Evelyn Hu, PhD, Columbia University
Joint Appointment: Materials

Ronald Iltis, PhD, UC San Diego

Petar Kokotovic, PhD, USSR Academy of Sciences

Stephen Long, PhD, Cornell University

Malgorzata Marek-Sadowska, PhD, Warsaw University of Technology

Michael Melliar-Smith, PhD, University of London

Sanjit Mitra, PhD, UC Berkeley

Louise Moser, PhD, University of Wisconsin

Venkatesh Narayanamurti, PhD, Cornell University

Pierre Petroff, PhD, UC Berkeley
Joint Appointment: Materials

Lawrence Rabiner, PhD, Massachusetts Institute of Technology

Affiliated Faculty

Jonathan Balkind, PhD

Bassam Bamieh, PhD

Elizabeth Belding, PhD

Michael Beyeler, PhD

Francesco Bullo, PhD

Ranjit Deshmukh, PhD

Miguel Eckstein, PhD

Chandra Krintz, PhD

Eric McFarland, PhD

Shuji Nakamura, PhD

Timothy Sherwood, PhD

Misha Sra, PhD

Yon Visell, PhD

William Wang, PhD

Jonathan Balkind, PhD