Welcome to the 2026 AI Winter School, hosted by the Center for the Fundamental Physics of the Universe, Brown University/Department of Physics
The Winter School has concluded. All modules are viewable here on Brown Physics Youtube. For access to module materials, please email cfpu@brown.edu.
This 4-day Winter School is open to interested graduate students, post-doctoral researchers and advanced undergraduates from any institution. Each module and following workshop are intended to stand alone; participants may sign up for as many modules as they choose.
All modules will take place virtually. There is no registration fee.
Recordings of each module will be available on the Brown Physics YouTube channel.
- View 2026 AI Winter School modules
- View 2025 AI Winter School modules
- View 2024 AI Winter School modules
AI Winter School Goals
The goal of this Winter School is to offer examples of the direct applications of machine learning methods to a range of problems inspired by the use of artificial intelligence in physics. We will provide hands-on experiences with machine learning tools to help reduce the barriers to engagement with these essential tools for physics research.
Hosted by the Brown Center for the Fundamental Physics of the Universe, this year's program will consist of six modules comprised of a lecture session delivered by Brown Physics faculty members and industry experts, followed by practice workshop sessions for participants with direction in the use of machine learning tools.
To learn more about the graduate programs in Physics at Brown, please visit the Physics Department website.
2026 AI Winter School Program
Roundtable discussion:
Featuring:
- Brenda Rubenstein, Brown University Professor of Chemistry and Physics and Director of the Brown Data Science Institute
- Michael Littman, Brown University Professor of Computer Science and Associate Provost for Artificial Intelligence
- Phiala Shanahan, MIT Associate Professor of Physics and IAIFI Interim Deputy Director
- Jamie Macbeth, Smith College Associate Professor of Computer Science
Link to Short Description of All Modules
- Module: Introductory Module
- Presenter: Shawn Dubey (Brown University)
- Module: Physics‑Informed Neural Networks: Teaching Models the Laws of Nature
- Presenters: Bryan Ostdiek ((Principal Data Scientist, Microsoft) and Darsh Kodwani
- Module: Applications of Optimal Transport in Collider Physics
- Presenter: Matt LeBlanc (Brown University)
- Module: Object Detection for Rare Event Searches
- Presenter: Jeff Schueler (University of New Mexico)
- Module: Denoising Electron Densities from Stochastic Simulations of Electronic Structure Using AI
- Presenter: Brenda Rubenstein (Brown University)
- Module: Training Simulations to Predict the First Stars and their Effect
- Presenter: Madhurima Choudhury (Birla Institute of Technology & Science Pilani), Jonathan Pober (Brown University)
- Module: Reinforcement Learning for Orbital Transfers
- Presenter: James Verbus (Senior Staff Software Engineer, Machine Learning, LinkedIn)
Register for access to all materials
Registration with a Gmail or Google-backed email account is required for full access to all AI Winter School materials including notebooks. Please note that we will use your registration email address to grant access to all materials. Full access to all materials will be available starting January 5. The AI School will make use of Google Colab for all the workbook examples (https://colab.research.google.com/).
If you do not have a Gmail or Google-backed account, you will need to register one. You can create an account just for this event or perhaps follow the directions at the following link to use an existing email.
NOTE: Module hands-on material will be on a Google shared drive. Access to this shared drive will be granted to those that have registered through this Indico site with their GMail or Google-backed email account. Due to the high level of interest this year, registrants will be granted this access via a dedicated Google group to which their registered email will be added. Access to the shared drive will not be given directly to any registrant's individual account. If you did not register with a GMail or Google-backed account, please modify or re-register through this site with a GMail or Google-backed account. If you just registered, please allow a little time for your registered email to be propagated to the Google group.
The Shared Google Drive will continue to be made available beyond the end of the School so there is no need to copy all the contents. Just your working notebook.
The time zone for the school will only be the US East Coast time zone.
