Speaker: Jian Pei, Duke University
Location: DC 1302 and over Zoom (register here)
Data and AI model sharing has been a long-time bottleneck for AI and data economies. In this talk, I will argue that data and AI model discovery and integration are foundations for effective sharing. I will also revisit why sharing remains a big challenge and why many existing approaches like data warehouses, data lakes, federated databases, and federated learning are still far from enough to solve the problem, particularly for sharing among organizations. Then, I will advocate data and AI markets as a potential grand opportunity for data and AI model sharing at scale, particularly for inter-organization sharing. Using some recent studies, I will demonstrate some exciting technical problems in data and AI model markets for the database and data science communities. I will also offer my humble views on the future directions on data and AI model markets.
Bio: Jian Pei is a Professor at Duke University. His research focuses on data science, data mining, database systems, machine learning, and information retrieval. With his expertise in developing data science principles and techniques for novel data-driven and data-intensive applications and transferring them to products and business practice, he has been recognized as a Fellow of the Royal Society of Canada, the Canadian Academy of Engineering, ACM, and IEEE. He received several prestigious awards, such as the 2017 ACM SIGKDD Innovation Award, the 2015 ACM SIGKDD Service Award, and the 2014 IEEE ICDM Research Contributions Award. He has previously served as the chair of ACM SIGKDD and as the Editor-in-Chief of IEEE TKDE.
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