
About
Tri Nguyen is a Postdoctoral Fellow at CIERA, Northwestern University, focusing on Dark Matter's role in galaxy formation and advanced machine learning applications in astrophysics. His work bridges computational cosmology with data science.
Education:
- Ph.D. in Physics (Astrophysics Division), Massachusetts Institute of Technology (2024)
Research Interests center on Dark Matter density profiles, galaxy assembly histories, and generative models for cosmological simulations. He specializes in graph neural networks and simulation-based inference frameworks.
Scientific Trends from his publications show deep integration of machine learning (diffusion models, graph networks) with cosmological data analysis (Gaia DR3, FIRE simulations). Articles emphasize generative modeling for halo merger trees and kinematic studies of dwarf galaxies.
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