I am a postdoctoral researcher at Princeton University, mentored by Dr. Jonathan Pillow. I completed my PhD in Applied Mathematics at the University of Washington in 2024, advised by Dr. Eric Shea-Brown. I have also held visiting research roles at the Mila – AI Institute (worked with Dr. Guillaume Lajoie), MIT (worked with Drs. Robert Yang and Chris Cueva), and the Allen Institute (worked with Drs. Uygar Sümbül, Stefan Mihalas, and Stephen Smith).
My research focuses on learning in intelligent systems, particularly brain learning, driven by the growing availability of brain data and rapid advancements in AI. I leverage deep learning to both model biological systems—drawing insights from theoretical deep learning frameworks to explain how biological neural circuits learn—and analyze neural data to uncover the principles of brain learning.
I was named a 2024 Rising Star in EECS (area: AI for Healthcare and Life Sciences) as well as a 2024 Rising Star in Computational and Data Sciences. I have published as the lead author in NeurIPS, ICLR, 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.