Anima Anandkumar
Bren Professor of Computing, Caltech | Former Senior Director of AI Research, NVIDIA
Verified Proof of Work Artifacts
2 items catalogedEach artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Anima Anandkumar. Every entry undergoes editorial source verification.
Eureka: Human-Level Reward Design via Coding Large Language Models
Created Eureka, an autonomous algorithm leveraging frontier coding LLMs to synthesize, evaluate, and iteratively refine complex reward algorithms for reinforcement learning, outperforming human expert-designed rewards across 29 dexterous robot manipulation tasks.
Requires fast GPU simulation environments to provide high-throughput performance feedback to the outer-loop LLM.
Fourier Neural Operator for Parametric Partial Differential Equations (FNO)
Pioneered the Fourier Neural Operator (FNO), formulating a deep learning architecture that directly learns mappings between infinite-dimensional function spaces via Fast Fourier Transforms, achieving mesh-independent zero-shot super-resolution on Navier-Stokes fluid turbulence 1,000x faster than standard numerical solvers.
Periodic boundary condition assumptions require specialized padding/coordinate embeddings for complex arbitrary 3D boundaries.