Niharika "Ari" Sravan
Time-domain Astronomy, Statistical Inference, Machine Learning, Experiment Design, Dynamic Optimal Resource Allocation
I am interested in using data science to envision and design novel systems for closing gaps, improving efficiency/accuracy, or fundamentally redesigning protocols for conducting astronomy. I am particularly motivated by ever more sophisticated all-sky surveys, the opportunities they offer for time-domain astronomy, and needs for the future of data-driven astronomy. To this end, I have designed AI systems that strategize real-time follow-up for optimal science gain for core-collapse supernovae, cosmology, and gravitational-wave counterparts.
I was previously a postdoctoral researcher in the Time-Domain Astronomy group at Caltech and before that in the Time-Domain Astrophysics group at Purdue University. I received my Ph.D. in Physics and Astronomy from Northwestern University in 2018 advised by Prof. Kalogera. I was also awarded a graduate certificate in Integrated Data Science from Northwestern University.