Scholar
Théo Bourdais
Google Scholar ID: Vr_DMBoAAAAJ
California Institute of Technology
Citations & Impact
Citations
25
H-index
2
i10-index
2
Publications
6
Co-authors
11
list available
Publications
Resume (English only)
Academic Achievements
- 1. Paper on Pruning Deep Neural Networks via a Combination of the Marchenko-Pastur Distribution and Regularization posted on Arxiv
- 2. Gave a talk on Model aggregation at DTE AICOMAS in Paris
- 3. Paper on Model aggregation was accepted at ICLR 2025
- 4. Paper 'Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots' published in PNAS
- 5. Gave a talk on Computational Hypergraph Discovery at the SIAM UQ 2024 conference in Trieste
- 6. Paper 'Discovering Algorithms with Computational Language Processing' posted on arXiv
Research Experience
- 1. Research Associate, NASA Jet Propulsion Laboratory (JPL), 2024 - 2025, Investigated applying research to JPL’s aerospace applications in the context of Digital Twins
- 2. Junior Data Engineer, Doc.ai (ShareCare), 2021 - 2022, Worked on several research projects in Computer Vision for Healthcare, including AI-based symptoms tracking for Myasthenia Gravis and automatic medication label reader development
- 3. Research Intern, INRIA, Summer 2020, Research internship on robust optimisation methods and algorithms
Education
- 1. PhD in Applied and Computational Mathematics, California Institute of Technology, 2022 - Present, Advisor: Prof. Houman Owhadi
- 2. Master of Mathematics, University of Cambridge, 2020 - 2021
- 3. Master of Science (Engineering), École Polytechnique, 2017 - 2021, Specialized in applied mathematics and computational methods
Background
- PhD Student in Applied and Computational Mathematics at Caltech, focusing on Machine Learning for Scientific Discovery, particularly Gaussian Processes, Computer Vision, Natural Language Processing, and Reinforcement Learning. Advisor: Prof. Houman Owhadi.
Miscellany
- Supported by the Kortschak Scholar program
