I am a McWilliams postdoctoral research fellow at the McWilliams Center for Cosmology in Carnegie Mellon University. I received my Ph.D. in Physics and Scientific Computing from the University of Michigan - Ann Arbor, working with Prof. August Evrard on modeling the most massive gravitationally bound objects in our universe, clusters of galaxies. More specifically, I developed novel inference models and computational algorithms to study the constituents of our universe and demystify the small-scale astrophysics. I have extensive knowledge of and experience in computational inference algorithms, machine learning, and statistical modeling of large datasets. On this site, you can find some information about my research and extracurricular activities. I was a Schmidt Science Fellow finalist, recipient of the best student paper award in KDD’18, an awardee of the Michigan Institute for Computational Discovery and Engineering (MICDE) fellowship, and recipient >$50k grants. My current research includes studying the formation, evolution, and fate of galaxies and clusters of galaxies, applications of machine learning in astronomy, developing computational inference algorithms for truncated and biased data, and data science for social good.
I develop theoretical models, perform large-scale simulations, and utilize advanced and novel statistical models to discover the fundamental physics of our Universe. I am an active member of several international projects and collaborations, including the Dark Energy Survey(DES), the COsmostatistics INitiative (COIN), XMM-XXL Consortium, and a few more. Besides science, I am interested in implementing novel educational models to engage with students. With my colleagues at the University of Michigan, I built the first data science education platform which teaches practical data science skills. Within this framework, not only the students gain knowledge in-depth knowledge of data science, but also do they make a positive social impact on the local communities. Last but not least, I am an advocate for data science for social good.
Undergraduate/graduate students: I am continually looking for dedicated students (you) who are interested in taking part in data science with social impact or astronomy projects. These projects involve a balance of theoretical, methodological, and data analysis work. Experience in theoretical physics, astronomy, statistics, or computer science is a plus but not a requirement. If you are looking for a project feel free to email me.
General Research Interest
My general research interest goes beyond what I am doing for my Ph.D. and is not limited to Astronomy. Here is a non-exhaustive list of my research interest:
- Physics of Clusters of Galaxies,
- Galaxy Formation/Evolution,
- Cosmological Probes,
- Formation and Evolution of Large-Scale Structures.
- String Theory and Holographic Duality,
- Gravitational Collapse,
- General Theory of Relativity.
Beyond Linear Physics
- Chaos and Turbulence,
- Non-perturbative methods.
- Topological Properteis of Random Fields.
Data Science and AI
- Applied Machine Learning,
- Deep Learning,
- Hierarchical Bayesian Modeling.
Data Science for Social Good
- Data Driven Public Policy and Decision Making,
- Application of Data Science and Machine Learning to Social Problems.
- Network Theory and its application,
- Education and Public Outreach.