Ph.D., Princeton University, 1982
I was born and raised in Taiwan. I went to National Taiwan University and received my B.S. degree in Electrical Engineering in 1976. After graduation, I worked for RCA Taiwan Ltd. for one year as a quality control engineer in its TV production plant. In August 1977, I came to the United State and enrolled in the graduate program at the University of Notre Dame from which I received my M.S.E.E. degree in January 1980. I started my pursuit of a Ph.D. degree in September 1979 at Princeton University and received my Ph.D. degree from Princeton in October 1982. I joined the faculty of Electrical Engineering at Notre Dame in August 1982 and have been here since then. From July 1998 to June 2006, I had the distinct privilege and pleasure to serve as Chair of the Department of Electrical Engineering. Through my career, I have been blessed by good educators and mentors that genuinely care for other people and delight in their successes. My MS thesis advisor, Dr. Eli Fogel, and Ph.D. dissertation advisor, Dr. John B. Thomas, have been most encouraging and helpful in the early stages of my career. They continue to be good role models that I aspire to be. I have met and worked with colleagues that are competitive yet collegial. I have spent my sabbaticals in Japan, Germany and Finland, complementing work with the pleasure of experiencing other cultures and visiting interesting places. I also have had the pleasure of working with intelligent and hardworking students who have produced good quality research results and who have become life-long friends.
Summary of Activities/Interests
Research Interests: My research interests focus on theory and applications of detection and estimation. The conventional approaches to solving the problems of detection and estimation are typically based on the principles of mathematical statistics. When those problems arise within the context of signal processing or communications, they are referred to as statistical signal processing or statistical communications, respectively. The underpinning statistical principles are, however, applicable to a wide range of problems that include bio-related engineering problems and financial data analysis. Our current projects involve us in the statistical signal processing problems that arise in interference mitigation and management for wireless communications, in distributed sensor networks, as well as those in the development of smart electric power grid technologies. One of the more interesting projects of my research is concerned with Set-Membership Adaptive Filtering (SMAF), which features discerning use of input data and selective update of filter coefficients. For nearly three decades, collaborating with my students and colleagues, my research group has developed a number of SMAF algorithms noted in the research community. Those algorithms are viable alternatives to conventional adaptive algorithms such as recursive least-squares (RLS) and least-mean-squares (LMS). Due to the selective update feature, our SMAF algorithms result in a modular adaptive filter architecture that forms the basis of event-triggered adaptation and that may lead to more resource-efficient distributed sensor networks.
Courses: Electric Circuits , Nonresident Disseration R , Communication Systems
July 26, 2013
December 14, 2012