EE 290 Graduate Seminar: Event-Triggered Sensing, Information Processing and Estimation for Internet of Things

pic of Professor Huang
pic of Professor Huang
Speaker Name: 
Yih-Fang Huang
Speaker Title: 
Professor of Electrical Engineering and Senior Associate Dean
Speaker Organization: 
College of Engineering at the University of Notre Dame
Start Time: 
Monday, April 16, 2018 - 10:40am
End Time: 
Monday, April 16, 2018 - 11:40am
Yu Zhang

Abstract: This talk will present opportunities and challenges in developing sensors that are more “intelligent” in their actions, and that may be more appealing in the development of “Internet of Things” (IoT). We shall show that event-triggered sensing, processing and estimation is a viable approach to designing intelligent sensors. Sensor technologies are at the forefront of IoT, for sensors are the “things” that collect physical measurements and convert them into data from which information and intelligence are extracted and learned. With the continued evolution of device and communication technologies, sensors can be made more autonomous – they can be more discerning in their actions of taking measurements, processing data, transmitting information and fusion. Such sensors would be more effective in separating irrelevant data from relevant data, facilitating timely and more reliable actions. More importantly, such sensors can be more energy-savvy due to their more discerning actions. To illustrate the benefits and potentials of such sensors, we will consider an example of distributed adaptive signal processing that implements event-triggered sensing, information processing and fusion. In particular, we shall show an event-triggered diffusion distributed adaptive estimation paradigm that can save on the overhead of communication and signal processing without significantly compromising the overall performance. Sensors designed according to such principles can clearly use the saved energy to perform other functions and/or render longer-lasting and more dependable network.

Bio: Yih-Fang Huang is Professor of Electrical Engineering and Senior Associate Dean of College of Engineering at the University of Notre Dame. Dr. Huang received his BSEE degree from National Taiwan University, MSEE degree from University of Notre Dame and MA and Ph.D. from Princeton University. He served as chair of the Electrical Engineering Department at the University of Notre Dame from 1998 to 2006. Dr. Huang’s research work employs principles in mathematical statistics to solve detection and estimation problems that arise in various applications, including wireless communications, distributed sensor networks, smart electric power grid, etc. He has published more than 200 papers in archival journals and conference proceedings in those areas. In Spring 1993, Dr. Huang received the Toshiba Fellowship and was Toshiba Visiting Professor at Waseda University, Tokyo, Japan. From April to July 2007, he was a visiting professor at the Munich University of Technology, Germany. In Fall 2007, Dr. Huang was awarded the Fulbright-Nokia Scholarship for lectures/research at Helsinki University of Technology in Finland (which subsequently became Aalto University). In 2014, Dr. Huang was appointed Honorary Professor in the College of Electrical Engineering and Computer Science at National Chiao-Tung University, Hsinchu, Taiwan.

Dr. Huang has served in various positions for the IEEE Circuits and Systems Society, including Vice President for Publications in 1997-98, and Distinguished Lecturer for the same society in 2000-2001. He received the Golden Jubilee Medal of that Society in 1999. At the University of Notre Dame, he received Presidential Award in 2003, the Electrical Engineering department’s Outstanding Teacher Award in 1994 and in 2011, the Rev. Edmund P. Joyce, CSC, Award for Excellence in Undergraduate Teaching in 2011, and the College of Engineering’s Teacher of the Year Award in 2013. Dr. Huang is a Fellow of the IEEE.

Research: Dr. Huang's primary research interests are in the general areas of statistical communications and signal processing. His areas of expertise includes signal detection and estimation, parameter estimation, adaptive signal processing, array signal processing, interference suppression for wireless communications, and set-membership filtering (SMF) and identification. Dr. Huang has made fundamental contributions to set-membership identification and filtering with applications to adaptive signal processing. His recent work focused on development of set-membership filtering with applications to adaptive equalization and interference suppression in multiuser communications and MIMO wireless communications. His research group at Notre Dame has developed a novel adaptive equalization paradigm, U-SHAPE (Updater-SHared Adaptive Parallel Equalization), and SMART (Set-Membership Adaptive Recursive Techniques), a toolbox for set-membership adaptive filtering. These techniques are viable alternatives to conventional algorithms, such as least-mean-squares (LMS) and recursive least squares (RLS), for interference suppression in multiuser wireless communications as they offer fast tracking at low computational costs. They also have developed novel MMSE parallel interference cancellation techniques for wireless communication systems, employing SMF for effective channel estimation. They are also developing SMF-based estimation and fusion algorithms for distributed sensor networks, featuring discerning cooperation and communications among sensor nodes. Dr. Huang received the Golden Jubilee Medal from the Circuits and Systems Society of the IEEE in 1999, and has served as a Distinguished Lecturer on Adaptive Signal Processing for Communications of the IEEE Circuits and Systems Society in 200-2001. Dr. Huang is a Fellow of the IEEE.

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