inary Bayes Classifier and Its Applications

报告人：Professor Hongying Meng

Brunel University of London

时间：2025年7月14日上午10：30 - 12：00

地点：数学楼2-3会议室

摘要：

The Bayes classifier is a probabilistic machine learning model based on Bayes' theorem, which calculates the likelihood that a data point belongs to a particular class. It uses prior knowledge of the class distributions and the probability of features given each class to compute the posterior probability—that is, the probability that the data point is in a specific class after observing the features. The classifier then assigns the data point to the class with the highest posterior probability. This approach is widely used due to its simplicity, efficiency, and effectiveness, especially in scenarios with well-understood probability distributions or high-dimensional data. In this talk, a specific binary Bayes classifier will be introduced including its framework as well as its fast implementation. Further, its applications in visual object recognition and seizure prediction will be presented. In the end, some future applications will be discussed.

报告人简介：

Hongying Meng is a full professor in the Department of Electronic and Electrical Engineering at Brunel University of London. He received his BSc, MSc and Ph.D. degree all from Xi’an Jiaotong University, Xi'an, China. After that, he worked as a postdoc researcher and then a lecturer at Electronic Engineering Department of Tsinghua University, China before moving to UK. His research area includes signal processing, artificial intelligence, computer vision, affective computing, neuromorphic computing and Internet of Things. He has published more than 200 academic papers with more than 8000 citations (Google Scholar h-index 41). He has developed 2 different emotion recognition systems that won AVEC2011 and AVEC2013 international challenge competitions respectively. He is an IEEE Senior Member since 2017 and an associate editor for IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) and IEEE Transactions on Cognitive and Developmental Systems (TCDS). He is also an associate Editors-in-Chief for Digital Twins and Applications (IET). He was recognized as one of the AI 2000 Most Influential Scholars by Aminer in 2022 and Top Scholar (within the top 0.5% of all scholars worldwide) by ScholarGPS in 2024. He was also listed as a Top 2% Scientist of the World (Stanford/Elsevier, single-year data sets) in 2023 and 2024 and one of the World's Best Computer Science Scientists by Research.com in 2025.