I believe the brain is the embodiment of the most beautiful algorithms ever written. Inspired by the brain's elegant efficiency, my research lies at the intersection of biological and artificial intelligence. I believe a complete unification of theoretical and experimental neuroscience will be required to reveal the neural correlates of intelligence and a general theory of brain plasticity that underlies it. In this effort, I experimentally explore the structure of neural circuits and test theoretical predictions for plasticity in the auditory cortex of mice using optical measurement and stimulation technologies. In concert, I derive normative, biologically-plausible learning algorithms and build physics-based models of the neural plasticity mechanisms that are engaged by them. I am currently a PhD student in Speech & Hearing Bioscience & Technology (SHBT) at Harvard Medical School and a Howard Brain Sciences Foundation fellow. I hold a bachelor's degree in Electrical Engineering & Computer Science from UC Berkeley (2014) and I have also obtained my master's degree in Music, Science & Technology from Stanford University (2017).