For an updated list of my research, see my Google Scholar page.
Preprints
George, Robert Joseph, Carson Eisenach, Udaya Ghai, Dean Foster and Anima Anandkumar. “BRIDGE: Building Representations In Domain Guided Program Verification.” under review, 2025. [Paper]
Jennifer Cruden, George, Robert Joseph, and Anima Anandkumar. “LeanNN: Towards Formal Verification of Neural Networks in Lean.” under review, 2025.
Kossaifi, Jean, George, Robert Joseph, Anima Anandkumar et al. “A library for learning neural operators.” under review, 2024. [Paper]
Conference Proceedings
George, Robert Joseph, Suozhi Huang, Anima Anandkumar et al. “ LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction”, TMLR, 2025. [Paper]
Kumarappan, Adarsh, George, Robert Joseph, Anima Anandkumar et al. “LeanAgent: Lifelong Learning for Formal Theorem Proving”, ICLR, 2025. [Paper]
Rahman, Md Ashiqur, George, Robert Joseph, Anima Anandkumar et al. “Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs.” NeurIPS, 2024. [Paper], [Codebase]
George, Robert Joseph, Jiawei Zhao, Jean Kossafii, Zongyi Li and Anima Anandkumar. “Incremental Spatial and Spectral Learning of Neural Operators for Solving Large-Scale PDEs”. TMLR, 2024. [Paper], [Codebase]
George, Robert Joseph. “EDCDE - Extended Discovery of Closed-Form Differential Equations”. ICLR Tiny Paper, 2023. [Paper], [Codebase]
Workshops
Valentin Duruisseaux, Robert M. Gray, George, Robert Joseph, Anima Anandkumar et al. “Fourier Neural Operators for Fast Simulation and Inverse Design of Second-Harmonic Generation in Nanophotonics”, NeurIPS Machine Learning and the Physical Sciences, 2025.
Ryan Hsiang, Will Adkisson, George, Robert Joseph, and Anima Anandkumar. “LeanDojo-v2: A Comprehensive Library for AI-Assisted Theorem Proving in Lean”, NeurIPS Mathematical Reasoning and AI, 2025.
Caroline Zhang, Aaron Zhao, George, Robert Joseph, Sergei Gukov and Anima Anandkumar. “Mathematical Discovery and Formalization Towards the AC Conjecture”, NeurIPS Mathematical Reasoning and AI, 2025.
George, Robert Joseph, David Pitt, Anima Anandkumar et al. “Tensor-GaLore: Memory-Efficient Training via Gradient Tensor Decomposition”, NeurIPS Optimization for Machine Learning, 2024. [Paper]
Jiawei Zhao, George, Robert Joseph, Yifei Zhang, Zongyi Li and Anima Anandkumar. “Incremental Fourier Neural Operator”. NeurIPS AI4Science, 2022. [Paper], [NeurIPS]
George, Robert Joseph, Martha White, Adam White and Samuel Neumann. “Making Reinforcement Learning Experiments More Reproducible and Computationally Efficient”. Reverse Expo, Alberta Machine Intelligence Institute, 2022. [Poster], [Codebase]
Undergraduate Honors Thesis
George, Robert Joseph, Noel Murasko and John Bowman. “Hybrid Dealiased Convolutions.” Joint Mathematics Meetings, 2023. [Paper], [Poster 1], [Poster 2], [Presentation], [JMM]
George, Robert Joseph, and Xinwei Yu. “Numerical Analysis for real-time Nonlinear Model Predictive Control of Ethanol Steam Reformers”. Canadian Undergraduate Mathematics Conference, 2022. [Presentation], [Paper]