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Stannis has broad research interests in the field of probabilistic generative models. He completed his PhD in Applied Mathematics with Dr. Stuart Geman at Brown University demonstrating the importance of kinetics in polymer folding, and developing theory and algorithms to overcome entropic barriers in stochastic dynamics.

During his PhD Stannis interned at Amazon Lab126, where he worked on multi-scale optimization for efficient training of deep neural networks. Stannis also has extensive experience consulting for quantitative finance firms.

He received his Bachelor’s in Mathematical Statistics and Probability from Peking University in China.