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活动名称：加拿大Regina大学教授学术报告

时间：2026年4月7日（星期二）10点

地点；重庆师范大学（大学城校区）致用楼102

主讲人：JingTao Yao

主办单位：计算机与信息科学学院

主讲人简介：

Dr. JingTao Yao received a Ph.D. degree from the National University of Singapore. He is currently a Professor with the Department of Computer Science, University of Regina, Canada.

Dr. Yao serves as an Area Editor of International Journal of Approximate Reasoning, Special Section Editor of Cognitive Computation, and a member of Editorial Boards of various international journals. He is currently the Steering Committee Chair, a Fellow, and past President of the International Rough Set Society. He was a member of Canada NSERC Discovery Grant Selection Committees and Evaluation Groups: Computer Science from 2017 to 2020, and 2026. He has been a Chair or a member of the Program Committee of numerous international conferences and has edited many volumes of conference proceedings.

Dr. Yao’s research interests include machine learning, deep learning, federated learning, rough sets, data science, three-way decision, and Web-based support systems. He has over 180 refereed journal articles and conference papers published in these areas and has received about8,000 citations according to Google Scholar. He has three highly cited papers (top 1%) and one hot paper (top 0.1%) according to Web of Science. Dr. Yao has been recognized as a top 90,000 (top 0.77%) scientist across all scientific fields over half century based a new standardized citation metrics developed by scientists led by Stanford University.

活动简介

讲座题目：Robust Federated Learning: Security and Stability in Dynamic Systems

讲座内容：Federated Learning (FL) enables privacy-preserving, decentralized model training by keeping data local. However, its real-world adoption is limited by security risks, non-IID data, and the need for continual adaptation. We will present an introduction of FL and research solutions that improve security, robustness to heterogeneity, and continual learning in FL systems.