Tristan Hoellinger
Biography
Observational cosmologist and applied mathematician interested in AI-assisted research.
Education
- PhD in Astronomy & Astrophysics, Institut d’Astrophysique de Paris, Sorbonne Université
- MSc in Applied Mathematics & MSc in Hybrid AI, INSA Toulouse & ENSEEIHT
Professional Experience
- 2026-Present JPL Postdoctoral Fellow, Jet Propulsion Laboratory
- 2023-2026 Doctoral Researcher, Institut d’Astrophysique de Paris
Community Service
- LOC for several workshops and conferences at the IAP
- Organizer of weekly meetings with invited colloquium speakers at the IAP
Research Interests
Stage-IV cosmology, implicit & field-level inference, numerical simulation, dark energy, machine learning
Selected Publications
- Diagnosing systematic effects using the inferred initial power spectrum, Hoellinger and Leclercq, A&A 699, A224 (2025); arXiv:2412.04443.
- A vorticity confinement correction for DG schemes applied to fluid flow problems, Hoellinger, Manueco, and Chapelier, IJNMHFF (2025), 10.1108/hff-11-2024-0854, [open-access]
- Enhancer/gene relationships: Need for more reliable genome-wide reference sets, Hoellinger et al., Frontiers in Bioinformatics 3 (2023), 10.3389/fbinf.2023.1092853.
- Data-Driven Simulation for Augmented Surgery, Mendizabal et al., Advanced Structured Materials 132 (Springer), 10.1007/978-3-030-50464-9_5.