My research focused on cosmology and its intersection with fundamental physics. To study the constituents of our universe and demystify small-scale astrophysics, I developed novel inference models and computational algorithms. As an astronomer, I employed the most massive gravitationally bound objects in the Universe—i.e., galaxy clusters—to study the nature of dark matter and dark energy. I was also an advocate for applications of data science to problems with societal impact. When I was not doing astronomy, I engaged with policy- and decision-makers and enabled them with data-informed decision making by providing novel data-driven tools.
I was an active member of several international projects and collaborations, including the Dark Energy Survey (DES), the COsmostatistics INitiative (COIN), and the XMM-XXL Consortium, among others. I was a McWilliams Postdoctoral Fellow at CMU, a recipient of the best student paper award in KDD’18, an awardee of the Michigan Institute for Computational Discovery and Engineering (MICDE) fellowship, and a recipient of more than $50k in grants.
Undergraduate/graduate students: I continually looked for dedicated undergraduate and graduate students (you) who wanted to expand their portfolio and take part in data science with social impact or astronomy projects. These projects involved a balance of theoretical, methodological, and data analysis work. If you were looking for a project, you could have emailed me.
World Economic Forum Report: I contributed to a report from the World Economic Forum featuring a data science project co-funded by MIDAS, the U-M Transportation Research Institute (UMTRI), the U-M College of Engineering, and The Knight Foundation. The project was part of a larger Seamless Integrated Mobility effort that aimed to transform mobility systems in Detroit, Ann Arbor, and Windsor. The project was one example of how data science could make a significant impact on policy making.