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.
Present Positions And Title
Group Leader
Research Group
Email Address
Career
| Period | Institution | Role |
|---|---|---|
| Since 2021 | University of Tübingen | Postdoc |
| 2019 - 2021 | Albert Einstein College of Medicine, New York | Postdoc |
| 2017 - 2019 | Albert Einstein College of Medicine, New York | Research Trainee |
| 2013 - 2019 | Max Planck Institute for Mathematics in the Sciences, Leipzig | PhD student |
Academic Education
| Year | Degree | Institution | Field of Study |
|---|---|---|---|
| 2019 | PhD | MPI for Mathematics in tde Sciences, Leipzig | Informatics |
| 2013 | Master’s | Bernstein Centre for Computational Neuroscience, Berlin | Computational Neuroscience |
| 2009 | Bachelor’s Degree | University of Toronto | Cog Sci & AI, Philosophy, Statistics |