Hello hello! I'm a Ph.D. candidate at the MIT Kavli Institute for Astrophysics and Space Research. I'm also a Pre-Doctoral Researcher at the Center for Computational Astrophysics (CCA) at the Flatiron Institute. I'm interested in using machine learning to understand structure formation in the Universe.
I'm currently working with Prof. Lina Necib at MIT and Prof. Rachel Sommerville at CCA on various projects:
- Applying graph-based simulation-based inference to infer the dark matter density profiles of dwarf galaxies [1].
- Using kinematics of accreted stars to characterize the galaxy accretion history of the Milky Way.
- Constructing synthetic Gaia DR3 surveys from Milky Way-like galaxies in the FIRE simulation.
- Generating galaxy merger trees with flow-based generative models.
- JeansGNN: A simulation-based inference framework for Jeans modeling based on Nguyen et al. (2023) [1] and Chang & Necib (2021) [2]
- FLORAH: Generating galaxy merger trees using flow-based recurrent graph neural network. Repo coming soon!
Thanks for stopping by!
- [1] Tri Nguyen, Siddharth Mishra-Sharma, Reuel Williams, Lina Necib, "Uncovering dark matter density profiles in dwarf galaxies with graph neural networks", Physical Review D (PRD), vol. 107, no. 4, article no. 043015, Feb. 2023, https://doi.org/10.1103/PhysRevD.107.043015
- [2] Laura J Chang, Lina Necib, Dark matter density profiles in dwarf galaxies: linking Jeans modelling systematics and observation, Monthly Notices of the Royal Astronomical Society, Volume 507, Issue 4, November 2021, Pages 4715 4733, https://doi.org/10.1093/mnras/stab2440