I studied biomedical engineering, applied math, and computer science at Washington University in St. Louis. After that, I joined Koniku in Berkeley and designed neural wetware chips to "digitize olfaction". Since then, I've continued studying neural representations of natural signals through my master's degree in Mathematics and Systems Science at WashU and my current research position in the Redwood Center for Theoretical Neuroscience. In between, I've lived and worked in London, Beijing, and Austin.
I wanted to embed myself in a curious, collaborative environment with strength in mathematics, theoretical neuroscience, and empirical vision research. Berkeley's Vision Science faculty and students, along with the broader university community, are a perfect fit for this. I look forward to learning and working with my incredible peers and engaging with the broader Bay Area community.
How does the visual system build invariant and equivariant representations of objects undergoing transformations in the world? How do we disentangle the many factors of variation in objects---shape, position, pose, color, lighting, etc.? Overall, I want to build an understanding of how information from the world can be represented and transformed in the brain using tools from Lie theory, differential geometry, and information theory. In parallel, I'm exploring applications of these ideas in machine learning.
I believe that the brain has much more to teach us about fundamental computational principles. I want to empower myself to contribute meaningfully to our formal understanding of neural representations and their implications on artificial intelligence and brain-computer interfaces. I look forward to working together with researchers in academia and industry in one form or another to push this work forward!
I experiment with sound and music (piano, python, ableton, circuits). I feel grounded when on my bike exploring cities and the land between them, especially with friends. I love getting people together climb, cook, and share treasured ideas.