Hi! I'm a PhD student in Computing and Mathematical Sciences at Caltech, advised by Pietro Perona. Driven by a passion for ecology and a curiosity for CVML, I aim to advance self-supervised and unsupervised methods in low-SNR video and audio data.

My research involves developing robust computer vision methods applicable to biodiversity and environmental monitoring across data modalities. I aim to ensure that my research is adaptable to new environments with limited resources, while dealing with challenges such as domain shifts, noisy data, and long-tailed distributions, inherent in all fine-grained problems.

Previously, I worked as a C++ developer at Amazon Music and a C++/python developer at NASA's Jet Propulsion Laboratory. I have always been drawn to work that has broad scientific, societal, and environmental impacts.

In line with my personal beliefs, I firmly uphold that the fields of Science, Technology, Engineering, and Mathematics (STEM) should be universally accessible, irrespective of one's background, gender, race, nationality, sex, age, or religion. My experience as a History major and a nontraditional graduate student have taught me lifelong skills and shaped my perspectives. I value the synergy of interdisciplinary perspectives and understand the significant impact that precise computational techniques can have on the world around us.