Dealing with Data Silos and Privacy in Artificial Intelligence – Advances in Transfer Learning and Federated Learning

Wednesday, December 11, 2019, 11:00 am - 12:00 pm PDTiCal
Conf Rm # 1016
This event is open to the public.
AI Seminar
Qiang Yang, HKUST
Video Recording:


Despite its great progress so far, artificial intelligence (AI) is facing a serious challenge in the availability of high-quality Big Data. In many practical applications, data are in the form of isolated islands. Efforts to integrate the data are increasingly difficult partly due to serious concerns over user privacy and data security. The problem is exacerbated by strict government regulations such as Europe’s General Data Privacy Regulations (GDPR). In this talk, I will review these challenges and describe possible technical solutions to address them. In particular, I will give an overview of recent advances in transfer learning and show how it can alleviate the problems of data shortage. I will also give an overview of recent efforts in federated learning and transfer learning, which aims to bridge data repositories without compromising data security and privacy.


Qiang Yang is the head of AI in WeBank and a chair professor at Computer Science and Engineering Department at Hong Kong University of Science and Technology (HKUST). His research interests include artificial intelligence, machine learning, especially transfer learning and federated learning. He is a fellow of AAAI, ACM, IEEE, AAAS, and the founding Editor in Chief of the ACM Transactions on Intelligent Systems and Technology (ACM TIST) and the founding Editor in Chief of IEEE Transactions on Big Data (IEEE TBD). He received his PhD from the University of Maryland, College Park in 1989 and has taught at the University of Waterloo and Simon Fraser University. He was the PC Chair of IJCAI-2015, KDD-2010 and has received the ACM SIGKDD Distinguished Service Award in 2017 as well as several other awards. He is a past President of IJCAI (2017-2019) and an executive council member of AAAI.


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