Incoming Assistant Professor, University of Toronto (starting January 2027)
I am currently a postdoctoral researcher at Princeton University, mentored by Dr. Jonathan Pillow. I completed my PhD in Applied Mathematics at the University of Washington, advised by Dr. Eric Shea-Brown. I have also held visiting research roles at Mila – AI Institute (with Dr. Guillaume Lajoie), MIT (with Drs. Robert Yang and Chris Cueva), and the Allen Institute (with Drs. Uygar Sümbül, Stefan Mihalas, and Stephen Smith).
I study learning in brains and machines, bridging AI/ML theory and neuroscience. My work develops theory-driven and data-driven models that connect neural and behavioral data to uncover how the brain learns and makes choices. More broadly, my vision is to advance AI/ML, psychology, and neuroscience by identifying general principles of efficient and robust learning, with impact for technology and health.
Keywords: NeuroAI, AI4Science, computational neuroscience, deep learning theory, decision-making, learning dynamics
I was named a 2024 Rising Star in EECS (area: AI for Healthcare and Life Sciences) and a 2024 Rising Star in Computational and Data Sciences. I have published as the first author in NeurIPS, ICLR, ICML, PNAS, and IEEE, and my work has been supported by fellowships such as the NSERC PGS-D, FRQNT B2X, Pearson, and NSF AccelNet IN-BIC. I have also taught and mentored extensively, earning a departmental teaching award.