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.
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:
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:
Kaustav Banerjee is spending the winter quarter of 2014 in Japan on an Invitation Fellowship from the Japan Society for the Promotion of Science.
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.
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.