About Me

I am a dual Ph.D. student in Astrophysics and Astrobiology at the University of Washington, specializing in data-driven approaches to astronomy. My research applies machine learning, statistical modeling, and large-scale simulations to explore cosmic phenomena—from probing dark matter with stellar streams to detecting asteroids and identifying compact binaries in massive datasets.

My projects span diverse domains: building high-performance pipelines for asteroid orbit integrations, using simulation-based inference with normalizing flows to constrain dark matter subhalo properties, and applying advanced period-finding algorithms to analyze Jupiter Trojan lightcurves. Through these efforts, I have honed expertise in time-series modeling, Bayesian inference, deep learning architectures, and large-scale computation.

Beyond research, I have served in leadership roles within academic societies, including as President and Co-Founder of the Data Science Society at UW, and previously as President of The Astronomical Society at UCLA and The Society of Sigma Gamma Epsilon. These experiences have strengthened my ability to lead teams, communicate complex concepts to diverse audiences, and foster collaborative environments.

I am passionate about pushing the boundaries of our understanding of the universe while exploring the intersections of astrophysics, machine learning, and data science. Outside of research, I am an avid astrophotographer and traveler, always seeking fresh perspectives and inspiration.

With a robust foundation in astrophysics, machine learning, and data science, I am eager to apply my skills toward solving complex problems and contributing to groundbreaking discoveries in astronomy.