In-Person Workshop, 16 December 2023 @NeurIPS
This workshop aims to bring together researchers from academia and industry to discuss major challenges, outline recent advances, and highlight future directions pertaining to novel and existing real-world experimental design and active learning problems. In addition, we aim to highlight new and emerging research opportunities for the machine learning community that arise from the evolving needs to make experimental design and active learning procedures that are theoretically and practically relevant for practical applications. Examples include protein design, causal discovery, drug design, and materials design, to name a few.
- Mihaela van der Schaar, Cambridge University.
- Eytan Bakshy, Meta Platforms, Inc.
- Anna Goldie, Google DeepMind and Stanford University.
- Joel Paulson, The Ohio State University.
- Emma Brunskill, Stanford University.
- Nathan Kallus, Cornell University and Netflix.
- Erika DeBenedictis, Francis Crick Institute.
Information for Accepted Paper Authors
We are excited to see you at the workshop on December 16!
- Schedule: Please see the full workshop schedule on this page.
- Posters: All accepted papers are invited to present their work as a poster! We have few requirements for posters, except that each should be under 4 feet per side.
- Poster setup will take place on the morning of our workshop (8:00am-8:30am CT).
- Spotlight Talks: We have reached out to a small set of papers to give spotlight talks on the day of the workshop.
Call for Submissions & Important Dates
Please see the Call for papers for submission instructions.
- Submission deadline: 4 October 2023, 11:59 PM (AoE time)
- Notification of acceptance: 26-27 October 2023, 11:59 PM (AoE time)
Best Student Paper Award: A best student paper award, worth 1000 USD, will be awarded to the best paper selected by a reviewing committee.
- Ava Amini, Microsoft Research.
- Ilija Bogunovic, University College London.
- Stefano Ermon, Stanford University.
- Lalit Jain, University of Washington.
- Andreas Krause, ETH Zurich.
- Mojmir Mutny, ETH Zurich.
- Willie Neiswanger, Stanford University.
- Zi Wang, Google DeepMind.
Please reach out to the organizers via email: firstname.lastname@example.org