Modern datasets are massive, and the models we apply to them are complex and difficult to decipher. Simple, principled theories are not things of the past, but more important than ever.
Dr. Sacha Sokoloski
Dr. Sacha Sokoloski is a group leader for Neuronal Modeling in the Department of Data Science at the Hertie Institute for AI in Brain Health at the University of Tübingen where he works on methods and models for understanding biological neural circuits. He takes a two-pronged approach: on one hand, he develops rigorous, probabilistic models of data and neural computation, and on the other, he develops large-scale machine learning methods to both simulate and analyze neural systems. One of his current projects involves applying deep reinforcement learning techniques to understand how animal visual systems adapt to their ecological niches.
Modern datasets are massive, and the models we apply to them are complex and difficult to decipher. Simple, principled theories are not things of the past, but more important than ever.