Hi!

I am Jun Yang (杨骏), a PhD student in the Quantitative Biosciences Program at Georgia Tech. I am interested in theoretical and computational neuroscience (/≧▽≦)/.

I’m advised by Dr. Hannah Choi. Currently, I am working on two projects: one focusing on dynamic mean-field theory for recurrent neural networks, and the other on building a circuit model for active vibrissal sensing.

Before starting my PhD, I studied at Tsinghua University, where I earned dual Bachelor’s degrees in Mathematics and Physics + Electrical Engineering ¹. During my undergrad years, I had the opportunity to explore neuroscience through research with Dr. Sukbin Lim at NYU Shanghai (continuous attractor models) and Dr. Mayank Mehta at UCLA (analyzing electrophysiological data from the Allen Institute Visual Coding – Neuropixels dataset). Prior to these experiences, I worked on a project investigating synchronization and information decomposition with Dr. Yang Tian for a few months and learned a lot from him and his works.