Distinguished Theme Seminar Series 2021

Each year we plan to introduce a timely and important research topic to our faculty and students. It will begin with a tutorial-style lecture to provide some background knowledge, followed by lectures from leading researchers who have made tremendous contributions to the recent advances of the topic. The five-week series is structured to provide ample time to digest the pertinent information. I hope this series will be informative and encourage you to research the topic in the future. At minimum, it will be enjoyable! 

This year the topic of our distinguished theme seminar series is Causal Inference. Causal inference is an important and expanding field which is widely studied across all sciences and has received a great deal of recent attention from the machine learning and statistics communities. From our diverse set of speakers, we will learn about many different approaches and applications of causal inference.

Many thanks to Professors Elias Bareinboim, Peter Bühlmann, Judea Pearl, James Robins, and Donald Rubin for agreeing to share their insights and wisdom with us. Thanks also to Professor Arman Sabbaghi for agreeing to present an introduction to the field. Please check the program website for more information and details about our distinguished speakers. The talks will be publicly available via YouTube livestream.

Thanks to Michael Zhu and his team, Jordan Awan, Anindya Bhadra, Chuanhai Liu, Vinayak Rao, Arman Sabbaghi, and Xiao Wang, to make such a wonderful program possible.

I am thrilled about the program -- please make your best effort to participate!

Dennis K.J. Lin
Distinguished Professor and Head of Statistics