Research Overview

Prof. Heather Zheng at the white board

Computer Engineering Research at UCSB

CE research lies not only at the interface of computer science and electrical engineering, but increasingly ties computing together with biology, medicine, chemistry, physics, mechanical engineering, and even environmental engineering.

Our research is ideally positioned to help solve societal problems through the construction of practical systems composed of emerging technologies. We live in a time of both opportunity and crisis. Rising carbon emissions and energy costs are a global problem. Aging populations increasingly strain healthcare resources. Computing technologies are at the heart of many potential solutions to these problems. Emerging technologies in nanoscale and bio-compatible materials hold the promise to increase energy-efficiency and revolutionize healthcare. We also see opportunities in massive information gathering and large-scale computing resources to exploit that information.

We must also address, however, increasing challenges to continued scaling of conventional silicon and to maintaining the dramatic performance growth of past computing systems.

CE Areas of Research

  • Bioinspired Computing
  • Circuit and System Design
  • Computer Architecture
  • Electronic Design Automation & Testing
  • Emerging Technologies for Computing

  • Energy-efficient Computing
  • Nanotechnology
  • Networking
  • Operating and Distributed Systems
  • Software and Language

Faculty Lab Spotlight

Test and Verification Lab
Professor Li-C. Wang

test and verfication lab research graph

The Test and Verification Lab leverages machine learning algorithms to assist in the process of knowledge discovery during the design and manufacturing process.

The application of our research lies in  two fronts:

Test:  During the test process, numerous measurements are performed on each chip to ensure that each chip meets its design specifications and is working properly.  We examine ways to leverage this data to reveal new insights into the manufacturing process that can then be used to create positive outcomes for the company.  So examples of these outcomes from previous projects include but are not limited to:

  • Improving Quality: Using statistical methodologies to complement existing testing for the purpose of screening future in-field failures for high-reliability products;
  • Improving Yield: Identifying the key process parameters that are contributing to abnormal yield fluctuations.
  • Reducing Cost: Identifying redundant tests by constructing predictive models based on remaining tests.

Verification: Functional verification is an iterative process since the design changes over time. Tons of machine hours are spent on simulating the tests in hope of covering all corners of the design and capturing functional bugs. Valuable knowledge is embedded in the simulation data and regression tests accumulated along the verification process. Data mining techniques can be applied to extract the knowledge and leverage them to improve the verification efficiency. Here are two example applications from previous projects:

  • Reducing simulation cost: Building statistical models to filter out ineffective tests for cutting down the cost of simulation time and licenses.
  • Improving testbench: Extracting rules from novel tests to present to the verification engineers so that they can improve the test generation.

Research News

Professor Melliar-Smith awarded J-C Laprie Award

Photo of Michael Melliar-SmithProfessor Melliar-Smith and colleagues at SRI International were given the prestigious 2014 Jean-Claude Laprie Award for their Software-Implemented Fault-Tolerant (SIFT) computer for aircraft flight control.

Professor Ben Zhao in UCSB article about Bitcoins

Photo of Ben Zhao Bitcoin “cryptocurrency” is either close extinction or may give central banking a run for its money. According to Zhao,, “It is a potentially world- changing disruptive technology.

Faculty Research Profile: Dr. Tim Cheng

photo of Tim Cheng

Tell Us About Your Research:
My research encompasses two major areas: (1) Design automation and test for electronic systems and (2) Mobile computer vision and embedded systems. In the first area, the research addresses challenges of ensuring correctness and reliability of complex integrated systems. Throughout my career, I've developed a number of techniques that have led to the availability of low-cost and high-quality solutions for validation and testing of high-performance and robust silicon integrated circuits as well as of flexible electronics. In the second area, my group developed a number of solutions for fast and accurate content analysis in images and videos, with an increasing focus on mobile applications that have limited hardware and energy resources.

How and Why Did You Get Into Your Area of Research and Why UCSB? Electronic design automation (EDA) and test are critical areas for the semiconductor industry and their research involves hardware and software, as well as algorithms and methodologies, and has strong "systems" components. These attributes are very attractive to me and thus helped provide me a long-lasting research career in this field. Mobile embedded systems, which have a broad spectrum of applications and are technically sophisticated, is multidisciplinary in nature and also interests me.

Why UCSB?: UCSB has a great reputation for nurturing multidisciplinary research which was the main reason I chose to leave Bell Labs. Over the past 20 years, UCSB's research culture and environment have helped me tremendously by expanding my research to cover a spectrum of topics - such as devices, systems, software, and applications - while still enabling me to have a great amount of depth for each research project.

(More about Professor Cheng and other faculty's research...)