Speakers
Prof. Irwin King, IEEE Fellow, INNS Fellow, AAIA Fellow, ACM Distinguished MemberThe Chinese University of Hong Kong, ChinaBIO: Professor Irwin King is a distinguished professor at the Department of Computer Science & Engineering, The Chinese University of Hong Kong. His research interests span various areas, including machine learning, social computing, AI, and data mining. Professor King has a significant publication record in top venues and serves as an editorial board member for numerous international publishers. He is an IEEE, INNS, AAIA and HKIE Fellow and ACM Distinguished Member. Throughout his career, Professor King has held leadership roles in prominent conferences and societies. He has served as the President of the International Neural Network Society (INNS) and has taken on key positions, such as General Co-chair, for many premier international conferences. Additionally, he is the Director of the Machine Intelligence and Social Computing Lab and the Trustworthy Machine Intelligent Joint Lab. Professor King obtained his B.Sc. from Caltech and his M.Sc. and Ph.D. degrees in Computer Science from USC. Speech Title: Trustworthy Artificial Intelligence with Federated Learning Abstract: Artificial intelligence (AI) has quickly become an integral part of our daily lives, appearing in virtual assistants and autonomous vehicles. However, the widespread use of AI necessitates the establishment of trustworthy AI (TAI) systems. TAI systems need to be secure, robust, explainable, and unbiased. But how can we ensure these qualities in AI systems? One approach is through Federated Learning (FL). FL is a distributed learning approach that prioritizes privacy by training AI models on decentralized data sources, eliminating the need for centralized data collection. This approach maintains privacy protection while enhancing the accuracy of local AI models. However, Federated Learning is not impervious to attacks. In this presentation, we will explore the concept of TAI and the significance of FL in constructing such systems. We will discuss various attack techniques, including model poisoning and inference attacks, that can compromise the security of FL systems. Additionally, we will present defense techniques such as differential privacy and secure multi-party computation, which can help mitigate these attacks and enhance the trustworthiness of FL. Lastly, we will address the challenges we face in achieving this objective. |
Prof. Haijun Zhang, IEEE FellowUniversity of Science &Technology Beijing, ChinaBIO: Haijun Zhang is currently a full professor and associate dean in the School of Computer and Communications Engineering at the University of Science and Technology Beijing, China. He was a postdoctoral research fellow in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC), Canada. He serves as Track Co-Chair of VTC Fall 2022 and WCNC 2020/2021, Symposium Chair of Globecom'19, TPC Co-Chair of INFOCOM 2018 Workshop on Integrating Edge Computing, Caching, and Offloading in Next Generation Networks, and General Co-Chair of GameNets'16. He serves as an editor for IEEE Transactions on Communications and IEEE Transactions on Network Science and Engineering. He received the IEEE CSIM Technical Committee Best Journal Paper Award in 2018, the IEEE ComSoc Young Author Best Paper Award in 2017, the IEEE ComSoc Asia-Pacific Best Young Researcher Award in 2019, and the and the IEEE ComSoc Distinguished Lecturer Award in 2019. He is a Fellow of the IEEE. |
Prof. Qinmin Yang, IEEE Senior MemberZhejiang University, ChinaBIO: Qinmin Yang received the Bachelor's degree in Electrical Engineering from the Civil Aviation University of China, Tianjin, China, in 2001; the Master of Science Degree in Control Science and Engineering from the Institute of Automation, Chinese Academy of Sciences, Beijing, China, in 2004; and the Ph.D. degree in Electrical Engineering from the University of Missouri-Rolla, MO, USA, in 2007. From 2007 to 2008, he was a postdoctoral research associate at the University of Missouri-Rolla. From 2008 to 2009, he was a system engineer with Caterpillar, Inc. From 2009 to 2010, he was a post-doctoral research associate at the University of Connecticut. Since 2010, he has been with the State Key Laboratory of Industrial Control Technology, the College of Control Science and Engineering, Zhejiang University, China, where he is currently a professor. He has also held visiting positions at the University of Toronto and Lehigh University. |
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2024 6th International Conference on Artificial Intelligence Technologies and Applications (ICAITA 2024) http://www.ic-aita.org/