Conference: 2026 Statistical Learning and Data Science Conference
Ente: STATISTICS
Scadenza: 2027-09-30
Importo max: 25.000 EUR
Paese: US
Descrizione
This award will support the 2026 American Statistical Association Section on Statistical Learning and Data Science (SLDS) Conference, to be held November 1–3, 2026, in New York City. The conference theme, Inference and Intelligence, addresses a major challenge in today’s data-driven world: how to combine the power of artificial intelligence and machine learning with careful reasoning, reliability, and transparency. The meeting will bring together researchers and practitioners from academia, industry, and government through lectures, invited sessions, poster presentations, student paper competitions, panels, and short courses. The primary goal of this award is to reduce financial barriers to participation for students, postdoctoral researchers, and early-career investigators, thereby broadening access to training, scientific exchange, and professional development in this rapidly growing area. Conference materials and, when permitted, selected slides and recordings will be made available online to extend the impact of the meeting beyond in-person participants.
For the mathematical sciences community, SLDS 2026 will provide a focused venue for research exchange at the interface of statistics, machine learning, and data science. The scientific program will highlight emerging challenges and opportunities in statistical learning theory, high-dimensional statistics, causal inference, uncertainty quantification, robustness under distribution shift, fairness, privacy, scalable computation, deep learning and foundation models, network and graphical models, and domain-driven applications. By bringing together theoretical, methodological, computational, and applied perspectives, the conference will promote cross-fertilization across areas of modern statistics and help identify new problems motivated by rapidly evolving AI technologies. Frontier short courses, poster sessions, and student award activities will further support training and dissemination, encourage participation by junior researchers, and foster new collaborations across institutions and sectors. For more information, see the conference website at https://asa-slds.github.io/slds2026/.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Istituzione: New York University
Sede: NEW YORK, NY
PI: Wen Zhou
Settori: Mathematical & Physical Sciences
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