Nhat-Minh Nguyen, PhD

Cosmologist, Kavli IPMU Fellow

Kavli Institute for Physics and Mathematics of the Universe, University of Tokyo

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Research Profile

Cosmologist working on growth of large-scale structure, new physics from galaxy surveys, and statistical methods for extracting information from cosmological data. Current research connects field-level inference, effective-field-theory likelihoods, multi-tracer analyses, and machine-learning methods for spectroscopic surveys. Publication record: 22 papers, including 16 outside large-collaboration author lists; h-index 17 on the current CV.

Selected Honors

Grants

Scientific Leadership

Mentoring and Teaching

• Co-mentored Carter Matties at the University of Michigan; now Physics Graduate Student at Syracuse.
• Co-mentored Andrja Kostić at the Max Planck Institute for Astrophysics; now Research Scientist at DeepL.
• Advised research projects for Baptiste Barthe-Gold, Eleni Tsaprazi, Andrew Hope, Kyle Lee, Disha Saxena, and Kasey Thai.
• Course instructor, Michigan Math and Science Scholars, “Climbing the Distance Ladder to the Big Bang: How astronomers survey the Universe,” Summer 2024.
• Guest lecturer, Michigan Math and Science Scholars, Summer 2023.

Positions

Education

Survey Collaborations

Research Themes

• Field-level and forward modeling for galaxy clustering, intrinsic alignment, and initial-condition inference.
• Effective-field-theory likelihoods for large-scale structure and consistency tests of physical data models.
• Multi-tracer and multi-survey calibration with PFS-DESI overlap.
• Growth-of-structure tests, modified-gravity parameterizations, and dark-sector phenomenology.
• Beyond-two-point galaxy clustering statistics, mock-data challenges, and survey-analysis validation.
• Machine-learning and statistical reconstruction of the local density field.

Selected Publications

1. Nguyen. “Physics Is All You Need? A Case Study in Physicist-Supervised AI Development of Scientific Software.” arXiv preprint. Accepted for ICML 2026 AI for Science Workshop.
2. Nguyen. “Multi-tracers, multi-surveys: a joint Fisher analysis of DESI+PFS.” arXiv preprint. Submitted to JCAP, 2026.
3. Nguyen, Akitsu, Taruya. “Galaxy sizes as complementary (zero-)bias tracers of local primordial non-Gaussianity.” arXiv preprint. Submitted to PRD, 2026.
4. Barthe-Gold, Nguyen, Thiele. “Reconstructing the local density field with combined convolutional and point cloud architecture.” arXiv preprint. Accepted for NeurIPS 2025 Machine Learning for Physical Science Workshop.
5. Beyond-2point Collaboration. “A parameter-masked mock data challenge for beyond-2pt galaxy clustering statistics.” ApJ 990, 99, 2025.
6. Nguyen, Schmidt, Tucci, Reinecke, Kostić. “How much information can be extracted from galaxy clustering at the field level?” Phys. Rev. Lett. 133, 221006, 2024.
7. Wen, Nguyen, Huterer. “Sweeping through Horndeski Canvas: a New Growth-Rate Parameterization for Modified-Gravity Theories.” JCAP 09, 028, 2023.
8. Nguyen, Huterer, Wen. “Evidence for suppression of structure growth in the concordance cosmological model.” Phys. Rev. Lett. 131, 111001, 2023. Editor’s Suggestion.
9. Kostić, Nguyen, Schmidt, Reinecke. “Consistency tests of field level inference with the EFT likelihood.” JCAP 07, 063, 2023.
10. Tsaprazi, Nguyen, et al. “Field-level inference of galaxy intrinsic alignment from the SDSS-III BOSS survey.” JCAP 08, 003, 2022.
11. Nguyen et al. “Impacts of the physical data model on the forward inference of initial conditions from biased tracers.” JCAP 03, 058, 2021.
12. Nguyen et al. “Taking measurements of the kinematic Sunyaev-Zel’dovich effect forward: including uncertainties from velocity reconstruction with forward modeling.” JCAP 12, 011, 2020.
13. DESI Collaboration. “DESI 2024 VII: Cosmological Constraints from the Full-Shape Modeling of Clustering Measurements.” JCAP 07, 028, 2025.
14. DESI Collaboration. “DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations.” JCAP 02, 021, 2025.
15. Schmidt et al. “A rigorous EFT-based forward model for large-scale structure.” JCAP 01, 042, 2019.

Selected Talks

Conference and workshop talks only; ordinary seminar talks are intentionally omitted.

Popular Science and Media

Professional Service

References