Cambridge BSU Lecture in Biomedical Data Science – Prof Xiao-Li Meng

The MRC Biostatistics Unit are delighted to introduce our new flagship lecture series on biomedical data science

Our first inaugural speaker will be Prof Xiao-Li Meng from Harvard University

Title: “Personalized Treatments: Sounds heavenly, but where on Earth did they find my guinea pigs?”

Abstract: Are you kidding me? Surely no one should take personalized literally. Fair enough, but then how un-personalized is personalized? That is, how fuzzy should “me” become before there are enough qualified “me”s to serve as my guinea pigs? Wavelet-inspired Multi-resolution (MR) inference (Meng, 2014, COPSS 50th Anniversary Volume) allows us to theoretically frame such a question, where the primary resolution level defines the appropriate fuzziness — very much like identifying the best viewing resolution when taking a photo. Statistically, the search for the appropriate primary resolution level is a quest for a sensible bias-variance trade-off: estimating more precisely a less relevant treatment effect verses estimating less precisely but a more relevant treatment effect for “me.” Theoretically, the MR framework provides a statistical foundation for transitional inference, an empiricism concept, rooted and practiced in clinical medicine since ancient Greece. Unexpectedly, the MR framework also reveals a world without the bias-variance trade-off, where the personal outcome is governed deterministically by potentially infinitely many personal attributes. This world without variance apparently prefers overfitting in the lens of statistical prediction and estimation, a discovery that might provide a clue to some of the puzzling success of deep learning and the like (Li and Meng, 2021, JASA).

The lecture series is being chaired by Sach Mukherjee and Sylvia Richardson at the MRC Biostatistics Unit.

TICKETS

https://www.eventbrite.co.uk/e/cambridge-bsu-lecture-in-biomedical-data-science-prof-xiao-li-meng-tickets-155917975863?aff=eand

Date

Jun 03 2021
Expired!

Time

10:00 am - 12:00 pm
QR Code

Leave A Reply

Your email address will not be published. Required fields are marked *