报 告 人：黄彪，加拿大工程院院士、阿尔伯塔大学化学与材料工程学院教授
报告题目：Bayesian Inference - Control Engineering Perspective
内容简介：Bayesian theory, due to its mathematical rigor and application flexibility, has attracted great interests from both academia and practitioners. The original Bayesian rule, as a single formula, can evolve into pages of long mathematical derivations. Yet the end result provides very meaningful solutions to the practical problems. Although the control community may not be very familiar with the term “Bayesian”, it has been adopted by control scientists as early as the start of modern control. The most well known application of Bayesian theory in control engineering is Kalman filter which has been widely adopted by the control community. It is now commonly recognized that many control related problems can be formulated under Bayesian framework and readily solved. Bayesian inference is getting even more popular due to the growing interest in Big Data and Data Analytics. This presentation will give a historical overview of Bayesian methods in control engineering, current activities, and future trends. These will include Bayesian methods for modeling, estimation, fault detection & isolation, causality analysis, control performance monitoring, and soft sensors development.
报告人简介：Biao Huang received his PhD degree in Process Control from the University of Alberta, Canada, in 1997. He held MSc degree (1986) and BSc degree (1983) in Automatic Control from the Beijing University of Aeronautics and Astronautics. He joined the University of Alberta in 1997 as an Assistant Professor in the Department of Chemical and Materials Engineering, and is currently a Full Professor, NSERC Senior Industrial Research Chair in Control of Oil Sands Processes, and Alberta Innovates Industry Chair in Process Control. He is an IEEE Fellow, Fellow of the Canadian Academy of Engineering, and Fellow of the Chemical Institute of Canada. He is a recipient of a number of awards including Changjiang Scholar from Education Ministry of China, Alexander von Humboldt Research Fellowship from Germany, Best Paper award from IFAC Journal of Process Control, APEGA Summit Award in Research Excellence, and Bantrel Award in Design and Industrial Practice, etc. He has published 5 books and over 330 peer-reviewed journal papers. His research interests include: process control, data analytics, Bayesian inference, system identification, control performance assessment, fault detection and isolation, and soft sensors. He has applied his expertise extensively in industrial practice.
He is currently the Editor-in-Chief for IFAC Journal Control Engineering Practice, Subject Editor for Journal of the Franklin Institute, and Associate Editor for Journal of Process Control.