JSM 2021 to Be Held Virtually
Long List of Featured Speakers, Lectures Just One Highlight
JSM 2021 will be delivered online through a custom platform. The platform will provide easy access to sessions and virtual opportunities to network and engage throughout the meeting. Synchronous participation will help you get the most out of your virtual experience—including sessions with live chat, polling, and other features. However, to accommodate all schedules, most sessions will be recorded and available on demand through the end of August.
Visit the JSM website to learn more and view the online program. Register by June 15 for early bird rates. Also, follow #JSM2021 for updates and tag @AmstatNews when you post.
FEATURED SPEAKERS
ASA President’s Invited Address
Vivienne Ming, Socos Labs
Messy Human Problems
Monday, August 9, 3:30 p.m.
Deming Lecture
Ivan S.F Chan, AbbVie
Deming Spirit in Action: Quality, Statistics, and Innovation in Vaccine Development
Tuesday, August 10, 3:30 p.m.
ASA President’s Address
Robert Santos, Urban Institute
Thoughts on the Role of ‘Self’ in a Statistics Career
Tuesday, August 10, 5:15 p.m.
COPSS Distinguished Achievement Award and Lectureship
Wing Hung Wong, Stanford University
Understanding Human Trait Variation from the Gene Regulatory Systems Perspective
Wednesday, August 11, 5:15 p.m.
F.N. David Award
Alicia Carriquiry, Iowa State University
Statistics in the Pursuit of Justice: A More Principled Strategy to Analyze Forensic Evidence
Thursday, August 12, 12:00 p.m.
LECTURES
IMS Presidential Address
Regina Liu, Rutgers University
Proactive and All-Encompassing Statistics
Monday, August 9, 5:15 p.m.
Lawrence D. Brown PhD Student Award Session
Wednesday, August 11, 10:00 a.m.
- Xin Bing, Cornell University
Inference in Interpretable Latent Factor Regression Models - Ilmun Kim, University of Cambridge
Minimax Optimality of Permutation Tests - Yichen Zhang, New York University Stern School of Business
First-Order Newton-Type Estimator for Distributed Estimation and Inference
Le Cam Lecture
Jianqing Fan, Princeton University
Understanding Spectral Embedding
Thursday, August 12, 10:00 a.m.
Medallion Lecture I
Philippe Rigollet, MIT
Statistical Optimal Transport
Monday, August 9, 1:30 p.m.
Medallion Lecture II
Robert Nowak, University of Wisconsin-Madison
Nonparametric Statistics and the Design of Experiments in Machine Learning
Tuesday, August 10, 1:30 p.m.
Medallion Lecture III
Nancy Zhang, University of Pennsylvania
Transfer Learning in Single-Cell Genomics
Thursday, August 12, 12:00 p.m.
Medallion Lecture IV
Axel Munk, University of Göttingen
Empirical Optimal Transport: Inference, Algorithms, Applications
Wednesday, August 11, 1:30 p.m.
Wald Lecture I and II
Jennifer Chayes, University of California, Berkeley
Modeling and Estimating Large Sparse Networks
Tuesday, August 10, 3:30 p.m.
Thursday, August 12, 4:00 p.m.
INTRODUCTORY OVERVIEW LECTURES
Julia for Statistics and Data Science
Cecile Ane, University of Wisconsin
Claudia Solis-Lemus, University of Wisconsin
Douglas Bates, University of Wisconsin
Advances in the Statistical Understanding of Random Forests and Related Methods and Their Use in Inference
Giles J. Hooker, Cornell
Lucas Mentch, University of Pittsburgh
Fairness in Machine Learning
Sherri Rose, Stanford University
Spatial Models for Massive Data Set
Sudipto Banerjee, University of California at Los Angeles
Professional Development short courses and workshops will be offered as distance learning presentations throughout the rest of this year and into 2022. Announcements will be sent when these are scheduled.