Bio

Andrew completed his PhD in Machine Learning at Georgia Tech. His thesis research, entitled “General and interpretable models for inferring dynamical computation in biological neural networks”, focused on developing novel approaches to improve the performance and interpretability of latent variable models of neural population dynamics. After a brief postdoctoral period in the lab, he began his next position as a Data Scientist at AE Studio.