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: Elaheh Ahmadi
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, 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

We expect our graduates to:

Possess a strong foundation in the fundamental theories, laboratory skills with industry-grade equipment, and tools related to electrical engineering, and be able to apply this knowledge to solve complex problems and create products.
Be able to work effectively in teams, manage tasks, contribute to group efforts, and effectively communicate technical information clearly and concisely.
Understand the social, business, technical, ethical, and human context of the world in which their engineering contributions will be utilized, and uphold the highest standards of ethics, integrity, and accountability.

Program Student Outcomes

Upon graduation, students in the Electrical Engineering B.S. degree program at UCSB are expected to have:

An ability to identify, formulate, and solve complex engineering problems by applying the principles of engineering, science, and mathematics
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.
An ability to communicate effectively with a range of audiences
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
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
An ability to develop and conduct appropriate experimentation, analyze, and interpret data, and use engineering judgment to draw conclusions
An ability to acquire and apply new knowledge as needed, using appropriate learning strategies

The undergraduate program in electrical engineering is accredited by the Engineering Accreditation Commission of ABET, under the commission’s General Criteria and Program Criteria for Electrical, Computer, Communications, Telecommunication(s), and Similarly Named Engineering Programs.

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

Elaheh Ahmadi, PhD, UC Santa Barbara, Associate Professor
Specialization: Design, Fabrication and Characterization of Novel (ultra)wide Bandgap Materials and Devices for High Power and High Frequency Applications, as well as Quantum Applications

Mahnoosh Alizadeh, PhD, UC Davis, Professor
Specialization: Cyber-Physical Systems, Learning, Optimization

Kaustav Banerjee, PhD, UC Berkeley, Professor
Specialization: Nanoelectronics; Physics, Technology, and Applications of Low-Dimensional Nanomaterials; 2D Materials and their Heterostructures; Bioelectronics; Quantum Electronics; Ultra-Low Power Devices, Circuits and Sensors

Ilan Ben-Yaacov, PhD, UC Santa Barbara, Teaching Professor
Specialization: Semiconductor devices and fabrication, electricity and magnetism, freshman design projects, implementation of novel curriculum and teaching methodologies in STEM fields, product design and project management, embedded systems, power electronics, and intellectual property (patents and trademarks/branding). Runs the Electrical Engineering Senior Capstone Projects Program.

Erez Berg, PhD, Stanford University, Professor
Joint Appointment: Materials

Dan Blumenthal, PhD, University of Colorado, Professor
Specialization: Optical Communications and Networks, Optical Packet Switching, Ultra-Low Linewidth Lasers, Ultra Low Loss Waveguide (ULLW) Platform and Devices, Photonics for Atomic and Quantum Systems, Integrated Optical Gyros, Ultrafast Optical Signal Processing, Photonic Integration in InP, SiPh/InP and Silicon Photonic and Nano-photonic Device Technologies

Jim Buckwalter, PhD, California Institute of Technology, Professor
Specialization: High-speed Mixed-signal Circuits, RF and Millimeter-wave Integrated Circuits and Systems, Photonics, Optoelectronic Interfaces, CMOS and III-V ICs

Katie Byl, PhD, Massachusetts Institute of Technology, Associate Professor
Specialization: Robot Locomotion and Manipulation, Machine Learning, Human-Robot Collaboration, Autonomous Systems, Dynamics and Control

Kerem Camsari, PhD, Purdue University, 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: Fast Algorithms for Partial Differential Equations, Signal and Image Processing

Steven Denbaars, PhD, University of Southern California, Professor
Specialization: Wide Bandgap Semiconductor Optoelectronics and Electronics
Joint Appointment: Materials

Joao Hespanha, PhD, Yale University, Professor
Specialization: Hybrid and Switched Systems; the Modeling and Control of Communication Networks; Distributed Control over Communication Networks (also known as networked control systems); the Use of Vision in Feedback Control; Game Theory; and Stochastic Modeling in Biology

Yogananda Isukapalli, PhD, UC San Diego, Teaching Professor
Specialization: Low power hardware design, Multi-antenna wireless communications, Transmit beam forming, Vector quantization, Performance analysis, Mobile embedded systems. Runs the Computer Engineering Senior Capstone Projects Program.

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: High-Resolution Imaging Techniques; Microwave, Acoustic, and Ultrasound Imaging Systems; Medical Imaging Devices; Distributed Sensing and Imaging Networks

Peng Li, PhD, Carnegie Mellon University, Professor
Specialization: Brain-Inspired Computing, Applied Machine Learning, Hardware Machine Learning Systems, Machine Learning Enabled Electronic Design Automation, Circuits & Systems

Upamanyu Madhow, PhD, University of Illinois, Urbana, Professor
Specialization: Next-generation Communication, Sensing and Inference Infrastructures centered around Millimeter Wave Systems; Signal Processing Algorithms; Robust Machine Learning

B. S. Manjunath, PhD, University of Southern California, Professor
Specialization: Image Informatics

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

Jason Marden, PhD, UC Los Angeles, Professor
Specialization: Game Theoretic Methods for Coordination of Large Scale Distributed Systems

Nina Miolane, PhD, Universite Cote d'Azur, Assistant Professor
Specialization: Geometric Statistics, Geometric Deep Learning, Topological Deep Learning, Equivariant Deep Learning, Shape Analysis, Computational Medicine, Theoretical Neuroscience, Computational Neuroscience

Richard Mirin, PhD, UC Santa Barbara, Professor
Specialization: III-V Semiconductor Epitaxy and Devices; Heterogeneous Materials Integration; Semiconductor Lasers; Chip-scale Nonlinear Optics; Quantum Dots; Molecular Beam Epitaxy, Single-Photon Sources and Detectors

Umesh Mishra, PhD, Cornell University, Professor
Specialization: Physics and Technology of Devices Based on Wide Bandgap Materials. Applications: Engineering materials properties, Microwave Electronics, Power Electronics, Opto-electronics and Sensing

Galan Moody, PhD, University of Colorado-Boulder, Professor
Specialization: Quantum Photonics and Optoelectronics; Integrated Photonics; Quantum Computing, Communications, and Networks; Hybrid Quantum Systems; Quantum Dots; 2D Materials

Yasamin Mostofi, PhD, Stanford University, Professor
Specialization: RF Sensing and Learning, Communication-Aware Robotics, Next-generation Communication, Vision, Robotics

Chris Palmstrom, PhD, Leeds University, Professor
Specialization: Quantum and Topological Materials, Materials for Quantum Information Systems, Spintronics, Metallization of Semiconductors, Thin Film Analysis, Dissimilar Materials Epitaxial Growth, and Molecular Beam and Chemical Beam Epitaxial Growth of Metallic Compounds, Heusler Compounds, Functional Materials, Magnetic Materials and Compound Semiconductors
Joint Appointment: Materials

Ramtin Pedarsani, PhD, UC Berkeley, Professor
Specialization: Machine Learning, Information Theory, Human-Cyber-Physical Systems, Stochastic Networks

Yao Qin, PhD, UC San Diego, Associate 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: nm and THz electronics: THz Transistors, nm VLSI Transistors VLSI, 100-1000GHz RF/Wireless ICs, beyond-5G-wireless, ICs for fast Optical Fiber Communication

Loai Salem, PhD, UC San Diego, Assistant Professor
Specialization: Power Management Integrated Circuits including Energy Harvesters and RF Supply Modulators, RF Power Amplifiers, Low-power Mixed-signal Circuits with focus on New Architectures for Analog/Digital Circuits

Clint Schow, Ph.D., University of Texas, Professor
Specialization: Optoelectronic/Electronic Integration and Co-design, Photonic Switching, Equalization Techniques for High-speed Optical Links, Optoelectronic Devices, Integrated Transceiver Packaging

Jon Schuller, PhD, Stanford University, Professor
Specialization: Nanophotonics, Plasmonics, Metamaterials, Photovoltaics, Organic Semiconductors, and IR Spectroscopy

Pradeep Sen, PhD, Stanford University, Professor
Specialization: Computer Graphics, Imaging, Computer Vision

Spencer Smith, PhD, UC Los Angeles, Professor
Specialization: Optics, Imaging, Neural Circuitry, Machine Learning, Optical Computing

Dmitri Strukov, PhD, Stony Brook University, Professor
Specialization: Solid-State Nanoionics, Emerging Electron Devices and Circuits, Non-Volatile Memories, Neuromorphic Computing

Andrew Teel, PhD, UC Berkeley, Professor
Specialization: Development of Feedback Control Algorithms for Nonlinear and Hybrid Dynamical Systems

Luke Theogarajan, PhD, Massachusetts Institute of Technology, Professor
Specialization: Low-Power Analog VLSI, High Speed Electronics for Photonics, Biomimetic Nanosystems, Neural Prostheses, Biosensors, Block 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. Central to this effort is the analysis and interpretation of data from electron cryo-microscopy and cellular electron cryo-tomography.
Joint Appointment: Interdisciplinary Program in Quantitative Biosciences; Biological Engineering

Li-C. Wang, PhD, University of Texas, Professor
Specialization: Artificial Intelligence for Design and Test, Data Analysis, Machine Learning

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: Electronic and Photonic Design Automation; Mathematical Data Science; Uncertainty quantification: Tensor-based Machine Learning and Hardware

Elaheh Ahmadi, PhD, UC Santa Barbara, Associate Professor
Specialization: Design, Fabrication and Characterization of Novel (ultra)wide Bandgap Materials and Devices for High Power and High Frequency Applications, as well as Quantum Applications

Mahnoosh Alizadeh, PhD, UC Davis, Professor
Specialization: Cyber-Physical Systems, Learning, Optimization

Kaustav Banerjee, PhD, UC Berkeley, Professor
Specialization: Nanoelectronics; Physics, Technology, and Applications of Low-Dimensional Nanomaterials; 2D Materials and their Heterostructures; Bioelectronics; Quantum Electronics; Ultra-Low Power Devices, Circuits and Sensors

Emeriti Faculty

Rod Alferness, PhD, University of Michigan

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

Forrest Brewer, PhD, University of Illinois

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

Behrooz Parhami, PhD, UC Los Angeles

Affiliated Faculty

Jonathan Balkind, PhD

Bassam Bamieh, PH.D.

Elizabeth Belding, PH.D.

Michael Beyeler, PhD

Francesco Bullo, PH.D.

Ranjit Deshmukh, PhD

Miguel Eckstein, PH.D.

Chandra Krintz, PH.D.

Eric McFarland, PH.D.

Shuji Nakamura, PH.D.

James Preiss, PhD

Timothy Sherwood, PH.D.

Misha Sra, PhD

Yon Visell, Ph.D.

William Wang, Ph.D.