Michael I Jordan, Pehong Chen Distinguished Professor, University of California, Berkeley
– 4 July 2023
Talk summary: Statistical decisions are often given meaning in the context of other decisions, particularly when there are scarce resources to be shared. Managing such sharing is one of the classical goals of microeconomics, and it is given new relevance in the modern setting of large, human-focused datasets and in data-analytic contexts such as classifiers and recommendation systems. Michael I Jordan discussed several recent projects that aimed to explore the interface between machine learning and microeconomics, including leader/follower dynamics in strategic classification, a Lyapunov theory for matching markets with transfers, and the use of contract theory as a way to design mechanisms that perform statistical inference.
Speaker bio: Michael I Jordan is the Pehong Chen Distinguished Professor at the University of California, Berkeley. His research interests bridge the computational, statistical, cognitive, biological, and social sciences. Jordan is a member of the National Academy of Sciences, a member of the National Academy of Engineering, a member of the American Academy of Arts and Sciences, and a Foreign Member of the Royal Society. He is a Fellow of the American Association for the Advancement of Science. He was the inaugural winner of the World Laureates Association (WLA) Prize in 2022. He was a Plenary Lecturer at the International Congress of Mathematicians in 2018. He has received the Ulf Grenander Prize from the American Mathematical Society, the IEEE John von Neumann Medal, the IJCAI Research Excellence Award, the David E Rumelhart Prize, and the ACM/AAAI Allen Newell Award. In 2016, Jordan was named the ‘most influential computer scientist’ worldwide in an article in Science, based on rankings from the Semantic Scholar search engine.
[Talk organised in collaboration with the Department of Computer Science and Automation]