As a dual Ph.D. student in Astrophysics and Astrobiology at the University of Washington, I am deeply engaged in exploring the cosmos through advanced data analysis, machine learning, and statistical modeling. My academic journey began with a dual B.S. in Astrophysics and Geophysics from UCLA, where I graduated with the highest honors, setting the stage for my current research pursuits.
My work primarily focuses on leveraging machine learning techniques to unravel the mysteries of the universe, from detecting faint asteroids in vast datasets to estimating the rotation periods of Jupiter Trojans. I am also probing the nature of dark matter by using convolutional neural networks (CNN) and simulation-based inference to study the interactions between dark matter subhalos and stellar streams. I have a strong background in time-series analysis, deep learning, and pattern recognition, skills that I continuously refine through projects involving the Zwicky Transient Facility and the upcoming Rubin Observatory.
Beyond my research, I have held leadership roles in several academic societies, including serving as President of both The Astronomical Society at UCLA and The Society of Sigma Gamma Epsilon. These experiences have honed my ability to lead teams, communicate complex ideas to diverse audiences, and foster a collaborative environment.
I am passionate about pushing the boundaries of our understanding of the universe, while also exploring the intersection of astrophysics, machine learning, and data science. In addition to my scientific endeavors, I am an avid astrophotographer and traveler, constantly seeking new perspectives and inspirations.
With a robust foundation in astrophysics, machine learning, and data science, I am excited to apply my skills to solve complex problems and contribute to groundbreaking discoveries in the field of astronomy.