In partnership with several leading statistical organizations and journals, the StatsUpAI Interest Group of the American Statistical Association is delighted to announce the first STAI-X conference on Statistics and Trustworthy AI for Cross (X)-Domain Acceleration (https://statsupai.org/STAIX2026/index.html) to be held at Harvard University on July 31-August 1, 2026. The STAI-X conference is co-hosted with the Department of Statistics and the Department of Biostatistics at Harvard University and will take place just before the 2026 Joint Statistical Meetings (JSM), which will be in Boston this year.
STAI-X aims to advance the integration of statistics and AI to accelerate trustworthy cross-domain discovery, innovation, spanning theory, methods, and applications, aiming for broad impact. STAI-X provides an opportunity to showcase cutting-edge research at the intersection of statistics and AI, facilitate connections and collaborations across research domains in AI, as well as hosting invited talks, platform talks selected from submitted papers, and offering short courses.
Partner organizations: The STAI-X conference is organized in partnership with several leading organizations, including the National Academies Committee on Applied and Theoretical Statistics (NASEM-CATS), Committee of Presidents of Statistical Societies (COPSS), American Statistical Association (ASA), Institute of Mathematical Statistics (IMS), East-Northern American Region (ENAR) and West-Northern American Region (WNAR) of International Biometrics Society, Statistical Society and Canada (SSC), International Chinese Statistical Association (ICSA), and National Institute of Statistical Sciences (NISS).
We would like to invite paper and poster submissions on all topics at the interface of AI and statistics, as well as domain applications. Areas of interest include Foundations and Methods at the Interface of Statistics and AI, AI Agents and Benchmarks for Data-Driven Discovery, and AI x Statistics x Science and Society.
Integrated Conference-Journal Peer Review Model: In partnership with leading statistical and domain science journals, STAI-X introduces a novel peer review model designed to accelerate research dissemination by combining the speed and topical relevance of machine learning conferences with the rigor and editorial standards of journals.
Call for Papers and Partner Journals
The call for 8-page papers is now open (submission portal). Accepted peer-reviewed papers will be eligible for publication in the STAI-X proceedings, as well as consideration for platform presentations, and paper awards. Top-ranked accepted conference papers will be eligible for being invited to submit expanded versions for fast-track reviews by partner journals, including the Journal of the American Statistical Association, Annals of Applied Statistics, Harvard Data Science Review, ASA Discoveries, Canadian Journal of Statistics, Genetics, Genome Research, and ASA Data Science in Science.
Call for Posters
The call for 2-page abstracts is now open (submission portal). Accepted submissions will be eligible for poster presentations, lightning talks, and stellar abstract awards.
Call for Short Courses
We invite proposals for short courses held on July 31, 2026, focusing on cutting-edge topics at the interface of statistics and AI, including but not limited to foundation models, generative AI, agentic AI, and trustworthy machine learning.
Call for Sponsors
We are actively soliciting industry, government, and academic sponsorships. Please contact Prof. Peter Song (University of Michigan) for opportunities.
Key Dates and Deadlines:
● Paper/Abstract Submission Deadline (May 11, 2026)
● Poster Acceptance Notification (May 24, 2026)
● Paper Acceptance Notification (June 11, 2026)
● Early Bird Registration (June 1, 2026)
● Regular Registration (June 25, 2026)
● Short Courses (July 31, 2026)
● Conference (August 1, 2026)
Intention to Submit
To help with review planning, we would be grateful if you could fill out this short Google form if you are interested in submitting a paper or a poster. If you have any questions, please contact us at staix.contact@gmail.com.
The registration site will be open soon.
Join us and submit papers and posters!
STAI-X organizing committee co-chairs:
Edgar Dobriban, University of Pennsylvania
Xihong Lin, Harvard University
Wenyi Wang, The University of Texas MD Anderson Cancer Center
Linjun Zhang, Rutgers University
Tian Zheng, Columbia University
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Jackson Lautier, PhD, FSA
Assistant Professor
Bentley University
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