Ali Shehper

I am an AI Researcher at Essential AI, working on the science of language model pre-training.

Previously, I was a Research Scientist at Caltech, focusing on Reinforcement Learning for Math, and before that a Physicist studying supersymmetric and topological quantum field theories.

Research Blog

• A Features’ Perspective on Neural Scaling Laws

Media

• How an Unsolved Math Problem Could Train AI to Predict Crises Years in Advance, Scientific American. August, 2025.
• AI Program Plays the Long Game to Solve Decades-Old Math Problems, Caltech Media. February, 2025.

RL For Math

• What makes math problems hard for reinforcement learning: a case study, (Accepted at NeurIPS 2025)
  A. Shehper, A. M. Medina-Mardones, L. Fagan, B. Lewandowski, A. Gruen, Y. Qiu, P. Kucharski, Z. Wang, S. Gukov.

Code

• AC-Solver A Python library for tackling long-horizon, ultra-sparse-reward RL environments, designed to accompany our case study.

• Sparse-Dictionary-Learning An open-source implementation of Anthropic’s Towards Monosemanticity: Decomposing Language Models with Dictionary Learning.

• Neural Scaling Laws An implementation of Scaling Laws for Neural Language Models, along with results from An Empirical Model of Large-Batch Training.

• Language Model Feature Browser A visualizer for features learned by a 1-layer Language Model, with the GitHub Repository.

Physics and Math

• PhD Thesis: Aspects of Supersymmetric and Topological Quantum Field Theories.

• Nonabelian Twists of the D4 Theory J. Distler, B. Ergun, A. Shehper (equal contribution with B. Ergun, alphabetical order).

• Symmetries of 2d TQFTs and Equivariant Verlinde Formulae for General Groups S. Gukov, D. Pei, C. Reid, A. Shehper (lead contributor, alphabetical order).

• Distinguishing 4d N=2 SCFTs J. Distler, B. Ergun, A. Shehper (equal contribution with B. Ergun, alphabetical order).

• Deformations of surface defect moduli spaces A. Neitzke, A. Shehper (lead contributor, alphabetical order).

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