A specialized workshop bringing together computational methods and clinical expertise to advance understanding of mental health and psychiatric disorders.
The New York Computational Psychiatry Workshop (NYCPW) is an immersive, hands-on three-day workshop designed to provide trainees with the latest tools and knowledge in computational psychiatry. Our aim is to bridge the gap between computational methods and clinical applications.
The workshop will take place at the Mount Sinai Center for Computational Psychiatry (55 W 125th St, New York, NY 10027) on November 10-12, 2025.
Gain an understanding of computational cognitive models and their application to psychiatric research, focusing on the latest theories in decision-making, learning, and social cognition.
Engage in interactive, hands-on tutorials where participants learn to fit computational models to simulated and real data.
Explore how computational methods can be translated into clinical settings, bridging the gap between research and practice to improve patient outcomes in mental health.
(NOV 10) |
(NOV 11) |
(NOV 12) |
|
|---|---|---|---|
| 08:00 AM | BREAKFAST + REGISTRATION | BREAKFAST | BREAKFAST |
| 08:30 AM | |||
| 09:00 AM | OPENING REMARKS + LECTURE Introduction to Computational Psychiatry |
TUTORIAL 3 Shawn Rhoads Fitting Models to Behavioral Data |
LECTURE Laura Berner Clinically Relevant Computational Psychiatry |
| 09:30 AM | |||
| 10:00 AM | TUTORIAL 1 Angela Radulescu Reinforcement Learning |
TUTORIAL 6 LLMs for Psychiatry |
|
| 10:30 AM | TUTORIAL 4 Blair Shevlin Drift Diffusion Modeling |
||
| 11:00 AM | |||
| 11:30 AM | |||
| 12:00 PM | LUNCH | LUNCH | LUNCH |
| 12:30 PM | |||
| 01:00 PM | TUTORIAL 2 Vincenzo Fiore Bayesian Inference |
TUTORIAL 5 Study Design & Replicability |
BREAKOUT PROJECTS* |
| 01:30 PM | |||
| 02:00 PM | |||
| 02:30 PM | COFFEE BREAK | ||
| 03:00 PM | COFFEE BREAK | BREAKOUT PROJECTS* | COFFEE BREAK |
| 03:30 PM | BREAKOUT PROJECTS* | BREAKOUT PROJECTS* | |
| 04:00 PM | |||
| 04:30 PM | PROJECTS WRAP-UP* | ||
| 05:00 PM | SOCIAL EVENT* | ||
| 05:30 PM | |||
| 06:00 PM | DINNER On your own |
DINNER On your own |
Previous Years: [2024]
How much will it cost to participate?
Registration for in-person attendance will be $495 for trainees (e.g., graduate students, postdocs), $795 for faculty, and $1095 for industry. Registration for online-only attendance will be discounted at 60% of main rate (e.g., $297 for trainees).
Is housing provided?
We are not able to provide housing this year. Participants will need to coordinate their own housing arrangements.
Who should apply?
We welcome participants from all career stages interested in using computational modeling to study mental health. However, our workshop will be primarily geared towards trainees (e.g., students, postdocs). Applicants should have some experience with programming (e.g., Python, R, MATLAB) and have completed formal coursework in math and statistics.
When is the application deadline?
In-person applications are due on September 30, 2025.
When will applicants be notified of their acceptance?
In-person applicants will be notified of their acceptance by October 10, 2025. If you are selected to participate, you will be asked to please register for the workshop at your earliest convenience by October 30, 2025.
What is the workshop size?
We expect 25 participants for the in-person course.
What is the format of the course?
The workshop will be a mix of lectures and hands-on tutorials. In-person participants will have the opportunity to work in small groups on a project and participate in networking events.
What is the workshop schedule?
The workshop will run from 9:00 AM to 6:00 PM on November 10-12, 2025. A detailed schedule will be provided to accepted participants.
Where is the workshop location?
The workshop will take place at the Mount Sinai Center for Computational Psychiatry (55 W 125th St, New York, NY 10027).
Who can I contact for more information?
Please contact the workshop directors (Shawn Rhoads and Angela Radulescu) with any questions.
Please click the following link to apply.
Apply
