Theo Bourdais
PhD Student in Computing and Mathematical Sciences
I am a PhD student at Caltech working with Houman Owhadi. I am also grateful to be supported by the Kortschak Scholar program.
I focus on Machine Learning for Scientific Discovery. In my research, I use
- Gaussian Processes
- Computer Vision, Natural Language Processing, and Reinforcement Learning
- Applied Mathematics, such as Random Matrix Theory and Partial Differential Equations
Latest News
Gave a talk on Non-linear Sensitivity Analysis for Interpretable Structure Discovery at SIAM AN26 (MS118).
New preprint: ISOMORPH, a supply-chain digital twin for simulation and forecasting benchmarks.
New preprint: Operator Learning at Machine Precision (CHONKNORIS).
Gave a talk on Model Aggregation at Mathematical and Computational Foundations of Digital Twins (CIRM, Marseille).
Posted Discovering Algorithms with Computational Language Processing on arXiv.
Patent application on co-discovering graphical structure and functional relationships within data published (US20250173388A1).
Presented a poster on Model Aggregation at ICLR 2025.
Our paper on Model Aggregation was accepted at ICLR 2025!
Our paper Codiscovering graphical structure and functional relationships within data was published in PNAS!
