Education & Professional Experience
Ph.D.: University of Toronto (Canada), Astronomy & Astrophysics (2004)
B.Sc.: University of British Columbia (Canada), Physics and Astronomy (1999)
Associate Professor, Carnegie Mellon University, 2016–
Assistant Professor, Carnegie Mellon University, 2010–16
Post-doctoral Research: Harvard University, 2007–10
Post-doctoral Research: Princeton University, 2004–07
Research Interests
I work on computational and theoretical cosmology and astrophysics. My research involves the development and application of numerical simulations to model and interpret the observable University. In cosmology, I work on complex problems involving the gas, stars, galaxies, quasars, and clusters of galaxies that provide information about the underlying dark matter and dark energy. In astrophysics, I am interested in the dynamics of stellar systems and the mergers of compact objects that produce gravitational waves. I also collaborate with computer scientists and statisticians to apply modern AI/ML approaches to improve multi-wavelength data analysis and numerical simulations. For example, we are applying Bayesian Deep Learning to map the dark matter in galaxy clusters. I am a member of the Atacama Cosmology Telescope (ACT) and Simons Observatory (SO) Collaborations.
Recent Publications
Dipto Mukherjee et al, Close encounters of the interstellar kind: exploring the capture of interstellar objects in near-Earth orbit, MNRAS, 908, 921
Dipto Mukherjee et al, Evolution of massive black hole binaries in collisionally relaxed nuclear star clusters - Impact of mass segregation, MNRAS, 518, 4801
Matthew Ho et al, The dynamical mass of the Coma cluster from deep learning, Nat Astron (2022)
Nianyi Chen et al, Patchy Kinetic Sunyaev-Zel'dovich Effect with Controlled Reionization History and Morphology, Astrophys. J., 943, 138
Hy Trac et al, AMBER: A Semi-numerical Abundance Matching Box for the Epoch of Reionization, Astrophys. J., 927, 186 (2022)
Yizhou He et al, A Hydro-particle-mesh Code for Efficient and Rapid Simulations of the Intracluster Medium, Astrophys. J., 925, 134 (2022)
Dipto Mukherjee et al, Fast Multipole Methods for N-body Simulations of Collisional Star Systems, Astrophys. J., 916, 9 (2021)
Matthew Ho et al, Approximate Bayesian Uncertainties on Deep Learning Dynamical Mass Estimates of Galaxy Clusters, Astrophys. J., 908, 204 (2021)
Matthew Ho et al, A Robust and Efficient Deep Learning Method for Dynamical Mass Measurements of Galaxy Clusters, Astrophys. J., 887, 25 (2019)
The Simons Observatory Collaboration, The Simons Observatory: Science goals and forecasts, JCAP 02, 056 (2019)
Hy Trac et al, SCORCH I: The Galaxy-Halo Connection in the First Billion Years, Astrophys. J., 813, 54 (2015)
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ORCID Researcher ID