NYC Student Theory & ML Day
May 8, 2026 • NYU Tandon
May 8, 2026 • NYU Tandon
NYC Student Theory & ML Day is a one-day gathering of NYC-area students in theoretical computer science, machine learning, and related areas. The event features student talks, discussion time, and opportunities to connect across institutions.
Attendance is free, but registration is required.
Lunch will be provided.
The event will be held at NYU Tandon School of Engineering, 370 Jay Street, Floor 08, Room 825, Brooklyn, NY.
Friday, May 8, 2026, 11:00 AM – 4:20 PM (tentative)
Each talk is scheduled for 20 minutes (times below are end-to-end for that slot). We hold three morning talks, then lunch from about 12:10 PM to 1:30 PM, and afternoon talks begin at 1:30 PM.
| Time | Event |
|---|---|
| 11:00 am – 11:10 am | Opening Remarks |
| 11:10 am – 11:30 am | Talk 1: Arpon Basu (Princeton) – Sparsifying Sums of Positive Semi-Definite Matrices (SODA 2026) |
| 11:30 am – 11:50 am | Talk 2: Hantao Yu (Columbia) – On the Computational Hardness of Transformers (STOC 2026) |
| 11:50 am – 12:10 pm | Talk 3: Zhou Renfei (CMU) – Succinct Dynamic Rank/Select: Bypassing Tree-Structure Bottleneck (SODA 2026) |
| 12:10 pm – 1:30 pm | Lunch Break |
| 1:30 pm – 1:50 pm | Talk 4: Noah Amsel (NYU) – The Polar Express: Optimal Matrix Sign Methods and their Application to the Muon Algorithm (ICLR 2026) |
| 1:50 pm – 2:10 pm | Talk 5: Chengyuan Deng (Rutgers) – Property Testing of Correlation Clustering (ICLR 2026) |
| 2:10 pm – 2:30 pm | Talk 6: Weiqiang Zheng (Yale) – Proximal Regret and Proximal Correlated Equilibria: A New Tractable Solution Concept for Online Learning and Games (STOC 2026) |
| 2:30 pm – 2:50 pm | Talk 7: Yiqiao Bao (UPenn) – Testing Noisy Low-Degree Polynomials for Sparsity (STOC 2026) |
| 2:50 pm – 3:05 pm | Break |
| 3:05 pm – 3:25 pm | Talk 8: Jingwen Liu (Columbia) – Fast Attention Mechanisms: A Tale of Parallelism (NeurIPS 2025) |
| 3:25 pm – 3:45 pm | Talk 9: Conor Sheehan (Yale) – On the Low-Temperature MCMC Threshold: The Cases of Sparse Tensor PCA, Sparse Regression, and a Geometric Rule |
| 3:45 pm – 4:05 pm | Talk 10: Sikata Sengupta (UPenn) – Replicable Reinforcement Learning with Linear Function Approximation (ICLR 2026) (last talk; may be online) |
| 4:05 pm – 4:20 pm | Wrap-up / Networking |
For additional details or inquiries, please email: Akbar Rafiey <ar9530@nyu.edu> or Nairen Cao <nc1827@nyu.edu>.
Earlier NYC-area student theory days at NYU Tandon: