Jing Lei and Jun Yan
The American Statistical Association’s Section on Statistical Learning and Data Science will hold the 2026 SLDS Conference November 1–3 at the New York Marriott at the Brooklyn Bridge. As the section’s flagship meeting, the conference brings together researchers and practitioners from academia, industry, and government to exchange ideas at the forefront of statistical learning and artificial intelligence.
The conference will feature keynote presentations from David Banks of Duke University, Dean Foster of Amazon, David Rosenberg of Bloomberg, and Bin Yu of the University of California at Berkeley.
SLDS welcomes participation from the wider statistical learning and data science community. Session, short course, and poster proposals, as well as sponsorship inquiries, can be sent to the following people:
- Invited session proposals: Jiwei Zhao or Wen Zhou
- Short course proposals: Giles Hooker
- Student paper or poster judges: Nathaniel Sean O’Connell
- Sponsorship inquiries: Jaime Speiser
The local organizing committee, led by Yang Feng and Wen Zhou of New York University, will host the conference.
The conference theme—Inference and Intelligence—highlights the interplay between statistical reasoning and modern algorithmic developments. The program will span a wide range of topics, including the following:
- Artificial intelligence
- Big data analytics
- Causal inference
- Deep learning
- Graphical models
- High-dimensional statistics
- Learning theory
- Machine learning
- Model selection
- Network analysis
- Spatiotemporal modeling
- Text and image analytics
Applications will reflect ongoing work across the health, social, and engineering sciences, as well as data-driven challenges arising in technology, finance, pharmaceuticals, and sports.
Program updates and additional information about abstract submission and registration will be available on the conference website.
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