Registration is open for the 2025 Joint Statistical Meetings, the largest gathering of statisticians and data scientists from all corners of the globe—hailing from academia, industry, and government. Share groundbreaking ideas, forge collaborations, learn from the brightest minds in the field, expand your professional network, and fuel your growth in this evolving discipline. JSM is for everyone, whether a seasoned professional, early-career data scientist, or student.
Nashville, Tennessee, the host of JSM this year, is known as “Music City” and offers a blend of Southern charm and a thriving cultural scene. Attendees will experience world-class entertainment, from live music at iconic venues to renowned dining and cultural attractions.
This year’s gathering will cover a broad range of topics, including the following:
- Adaptive Design
- Artificial Intelligence
- Bayesian Computation
- Causal Inference
- Clinical Trial Design
- Data Science / Modeling
- Life Sciences and Medicine
- Machine Learning
- Spatio-Temporal Statistics
- Statistical Methodology
Additionally, attendees can look forward to a long list of well-known speakers.
Plenaries
ASA President’s Invited Address
Juan Lavista Ferres, AI for Good Lab at Microsoft
AI for Good in the Era of GPT
IMS Presidential Address
Tony Cai, University of Pennsylvania
Deming Lecture
Jianjun Shi, Georgia Institute of Technology
From Statistical Process Control to In-Process Quality Improvement
ASA President’s Address & Fellows and Founders Recognition
Ji-Hyun Lee, University of Florida
Statistics, Data Science, and AI Enriching Society
COPSS Distinguished Achievement Award and Lectureship
James Robins, Harvard School of Public Health
Causal Inference: History, Statistical Methods, Role in Public Health and Medicine, Controversies, and the Future
Named Lectures
IMS Medallion Award & Lecture I
Ery Arias-Castro, UC San Diego
Modal Clustering: Past and Present
Rietz Award & Lecture
Kathryn Roeder, Carnegie Mellon University
Genomic Inferences in the Era of Black Box Predictions
IMS Medallion Award & Lecture II
Sandrine Dudoit, University of California-Berkeley
Learning from Data in Single-Cell Transcriptomics
Neyman Award & Lecture
Regina Liu, Rutgers University
Fusion Learning: Combining Complex Inferences from Diverse Data Sources
IMS Medallion Award & Lecture III
Florentina Bunea, Cornell University
Learning Softmax Mixture Ensembles for AI Applications
Le Cam Award & Lecture
Peter Bickel, University of California at Berkeley
Local Asymptotic Analysis: A General Quantitative Tool
IMS Medallion Award & Lecture IV
Victor Panaretos, EPFL
Near the Diagonal
Breiman Award Lectures
Rahul Mazumder, Massachusetts Institute of Technology
Mladen Kolar
Wald Memorial Award & Lecture, Part I
Jianqing Fan, Princeton University
Neural Causality Learning from Multiple Environments
Wald Memorial Award & Lecture, Part II
Jianqing Fan, Princeton University
Improving Peer Reviews: Aggregation of Rankings from Crowds of Reviewers
IMS Grace Wahba Award and Lecture
Richard Samworth, University of Cambridge
Nonparametric Inference Under Shape Constraints: Past, Present, and Future
IMS Medallion Award & Lecture V
Boaz Nadler, Weizmann Institute of Science
Finding Structure in High-Dimensional Data: Statistical and Computational Challenges
Award Sessions
Florence Nightingale David Award Lecture
Katherine Ensor, Rice University
Brave New World: Fact or Fiction
David R. Cox Foundations of Statistics Award
Alexander Dawid, University of Cambridge
A Lifetime of Irrelevance
Noether Early Career Scholar Award
Song Mei
A Statistical Theory of Contrastive Pre-Training and Multimodal Generative AI
Noether Early Career Scholar Award
Yuting Wei, University of Pennsylvania
To Intrinsic Dimension and Beyond: Efficient Sampling in Diffusion Models
Noether Distinguished Scholar Award
He Xuming, Washington University in St. Louis
Taming the Tail with Expected Shortfall Regression
IMS Lawrence D. Brown PhD Student Award
Louis V. Cammarata
Ying Jin
George Stepaniants
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