On behalf of the Learning Theory Alliance, we are pleased to share this invitation to the 4th Learning Theory Alliance Mentorship workshop in collaboration with FODSI, to be held virtually October 26–27, 2022. The workshop is free.

The workshop is intended for upper-level undergraduate and all-level graduate students, as well as postdoctoral researchers, who are interested in research on the mathematical foundations of machine learning. No prior research experience in the field is expected. There are several planned events, including:

• Two “how-to” talks: 
  • How to start your research journey (how to find your first research opportunity and navigate your first few research projects)
  • How to expand your research profile (how to decide what to work on, come up with a project, and develop a research vision)
• A panel that focuses on the evolution of a project, thesis, and career
• A social hour with mentoring tables

The speaker lineup includes: Hamsa Bastani, Sébastien Bubeck, Clément Canonne, Stefanie Jegelka, Jelani Nelson, Behnam Neyshabur, Emma Pierson, Chara Podimata, Jacob Steinhardt, and Vasilis Syrgkanis.

A short registration form is required to participate, with an application deadline of Thursday, October 20, 2022. Students with backgrounds that are underrepresented or underserved in related fields are especially encouraged to apply. We are trying our best to accommodate all time zones. More information (including the schedule) can be found on the event’s website: https://let-all.com/fall22.html.

This workshop is part of a broader community-building initiative called the Learning Theory Alliance (founded by Surbhi Goel, Nika Haghtalab, and Ellen Vitercik; advised by Peter Bartlett, Avrim Blum, Stefanie Jegelka, Po-Ling Loh, and Jenn Wortman Vaughan). Check out http://let-all.com/ for more details.