Brief Description:

Research scientist with extensive experience in reverse-engineering complex systems using advanced data science and statistical methods. Proven track record of developing interpretable models from observational data, leading collaborative research teams, and building robust experimental frameworks. Expert in Python-based analysis, statistical inference, and designing experiments that bridge theoretical models with empirical observations. Extensive experience mentoring researchers and communicating complex findings to diverse audiences.

Technical Description:

NPP fellow at NASA GSFC: My current work levergaes the use of AItechniques to solve problems faced by high energy astrophysists. This includes the use of archival data and predicitve techniques for future measurements.  I have also worked on multi-messenger + multi-wavelength astronomy to explain processes happening inside an AGN at NASA GSFC as a NPP fellow. This is done by extending observations from NASA missions, NICER+NUSTAR+Fermi-LAT with IceCube. I have not given up on Galactic neutrino signals too and plan to extend my simulation study to both high and low energy neutrinos. 

I am also working on increasing the science outcomes that can be achieved from collaborations and new research. This can help lead to additional collaborations between particle physicists, astrophysicists and data scientists, leading to new ideas and improved methods. To work on this,  I hosted two splinter session at the AAS meetings. I have also served in multiple review panels, which allows me to provide my research experience as needed and also helps me understand the processes that make sure new and interesting science cases are prioritized, and all research is judged fairly.

Postdoc at UW Madison: In 2019 I secured the John Bahcall fellowship at University of Wisconsin-Madison (WIPAC) to study the possibility of AGN being sources of astrophysical neutrinos seen by the IceCube detector. I worked on understanding the radio-neutrino correlation in AGN. I also worked on simulating the Galactic neutrino signal using a simulation package we developed named SNuGGY (also on Github). In addition to this scientific work, I also participated in outreach events like summer school, hosted at WIPAC

 PHD Work: I received my PhD in 2019 from Clemson University, South Carolina. During my PhD years, I worked on studying the diffuse background which is composed of all the light observed in the universe in the UV to IR regime, dubbed extragalactic background light (EBL). This was done using the spectra observed using the NASA mission, Fermi-LAT, of observed active galactic nuclei (AGN) and gamma-ray bursts. During my PhD, I also worked as an instructor of astronomy for a summer school at Johns Hopkins University, Center for Talented Youth.