Education
PhD in Informatics | June 2013 to May 2019 |
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Max Planck Institute for Mathematics in the Sciences | Leipzig, Germany |
- Supervisor: Professor Nihat Ay
- Dissertation Submitted: October 2017
- Dissertation Defended: May 2019
- Paternity leave: During my PhD I had my first and second child and took periods of leave for both.
Master’s in Computational Neuroscience | October 2010 to May 2013 |
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Bernstein Centre for Computational Neuroscience Berlin | Berlin, Germany |
- Supervisor: Professor Manfred Opper
Bachelor of Science | May 2004 to May 2009 |
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University of Toronto | Toronto, Canada |
- Specialist: Cognitive Science and Artificial Intelligence
- Major: Philosophy
- Minor: Statistics
Bibliography
Peer-Reviewed
- Katrin Franke et al., “Asymmetric Distribution of Color-Opponent Response Types Across Mouse Visual Cortex Supports Superior Color Vision in the Sky,” 2023. [Link]
- Sacha Sokoloski, Amir Aschner, and Ruben Coen-Cagli, “Modelling the Neural Code in Large Populations of Correlated Neurons,” ed. Jonathan W Pillow, Joshua I Gold, and Kenneth D Harris, eLife (2021). [Link] [PDF]
- Sacha Sokoloski, “Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics,” Neural Computation (2017). [Link] [PDF]
Preprints
- Lisa Schmors et al., “Effects of Non-Retinal Inputs in Visual Thalamus Depend on Visual Responsiveness and Stimulus Context,” 2023. [Link]
- Sacha Sokoloski and Philipp Berens, “Hierarchical Mixtures of Gaussians for Combined Dimensionality Reduction and Clustering,” 2022. [Link] [PDF]
- Sacha Sokoloski, “A Biologically Realistic Model of Saccadic Eye Control with Probabilistic Population Codes,” ArXiv12104145 Cs Q-Bio (2012). [Link] [PDF]
Theses
- Sacha Sokoloski, “Implementing Bayesian Inference with Neural Networks” (PhD thesis, University of Leipzig, 2019). [Link] [PDF]
- Sacha Sokoloski, “Efficient Stochastic Control with Kullback Leibler Costs Using Kernel Methods” (Master’s thesis, Technical University of Berlin, 2013). [PDF]
Professional Activities
Conferences and Workshops
EMBO Workshop: Subcortical sensory circuits | November 2023 |
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EMBL Heidelberg | Heidelberg, Germany |
- Poster: A computational approach to visual ecology with deep reinforcement learning (Sacha Sokoloski, Jure Majnik, Philipp Berens)
- Received best poster award
European Retina Meeting | September 2023 |
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University of Tübingen | Tübingen, Germany |
- Talk: Modelling ecological constraints on visual processing with deep reinforcement learning (Sacha Sokoloski, Jure Majnik, Thomas Euler, Philipp Berens)
Cosyne | March 2023 |
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Fairmont The Queen Elizabeth | Montreal, Canada |
- Poster: Modelling ecological constraints on visual processing with deep reinforcement learning (Sacha Sokoloski, Jure Majnik, Thomas Euler, Philipp Berens)
- Received travel grant
Population Models Workshop | July 2022 |
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University of Edinburgh | Edinburgh, Scotland |
- Invited Talk: Exact learning and inference in large-scale probabilistic graphical models
Cosyne | March 2022 |
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Lisboa Congress Centre | Lisbon, Portugal |
- Poster: Disentangling neural dynamics with fluctuating hidden Markov models (Sacha Sokoloski, Ruben Coen-Cagli)
- Poster: An interpretable spline-LNP model to characterize feedforward and feedback processing in mouse dLGN (Lisa Schmors, Yannik Bauer, Ziwei Huang, Lukas Meyerolbersleben, Simon Renner, Ann H. Kotkat, Davide Crombie, Sacha Sokoloski, Laura Busse, Philipp Berens)
Cosyne | February 2021 |
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Online |
- Poster: Information-limiting correlations linearize the neural code (Sacha Sokoloski, Ruben Coen-Cagli)
- Poster: Neural sampling from bimodal distributions in primary visual cortex (Ruben Coen-Cagli, Adam Kohn, Sacha Sokoloski)
Cosyne | February 2020 |
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Hilton Denver City Center | Denver, USA |
- Poster: Mixture of poisson models for neural correlations and coding (Sacha Sokoloski, Ruben Coen-Cagli)
- Received travel grant
Sense2Synapse | April 2017 |
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Rockefeller University | New York City, USA |
- Poster: Dynamic Bayesian Inference in the Brain
International Conference on Mathematical Neuroscience | May 2016 |
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Antibes Juan-les-Pins Conference Centre | Juan-les-Pins, France |
- Talk: Learning to Filter Spike Trains when the Stimulus Dynamics are Unknown and Nonlinear
HaL-10: Haskell in Leipzig | December 2015 |
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HTWK Leipzig | Leipzig, Germany |
- Talk: Typsichere Numerische Optimierung basierend auf Mannigfaltigkeiten
- English title: Typesafe Numerical Optimization based on Manifolds
Teaching
Teaching Essential Statistics | Winter 2022/23 & Winter 2023/24 |
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University of Tübingen |
- Teaching the Master’s course “Essential Statistics for Neuroscience”.
Mentorships
PhD Student: Fabio Seel | September 2023 to Present |
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Hertie Institute for AI in Brain Health |
- Co-supervising Fabio Seel with Philipp Berens in the area of retinal modelling with deep neural networks.
Master’s Student: Jure Majnik | Winter 2021/22 & Fall 2022 |
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University of Tübingen |
- Supervised Jure Majnik on developing code for the retinal-rl project.
Google Summer of Code: Zarak Mahmud | Summer 2022 |
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Haskell.org |
- Mentored Zarak Mahmud through the Google Summer of Code program to add GPU computation to my Geometric Optimization Libraries.
Google Summer of Code: Andrew Knapp | Summer 2018 |
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Haskell.org |
- Mentored a student through the Google Summer of Code program on developing a library for parallel automatic differentiation for the Haskell.org organization.
- Project was overall successful.
Peer Review
- IEEE Transactions on Artificial Intelligence (2023)
- PLOS Computational Biology (2023)
- Neural Processing Letters (2022)
- Nature Neuroscience (Co-review, 2022)
- eLife (2021)
- Nature Communications (Co-review, 2019)
- IEEE Transactions on Neural Networks and Learning Systems (2017)
Employment History
Group Leader | January 2024 to Present |
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Hertie Institute for AI in Brain Health | Tübingen, Germany |
- Group: Neuronal Modelling
- Director: Philipp Berens
Postdoctoral Researcher | July 2021 to December 2023 |
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University of Tübingen | Tübingen, Germany |
- Principal Investigator: Philipp Berens
- Project: Modelling neural circuits in the retina
Research Fellow | October 2019 to April 2021 |
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Albert Einstein College of Medicine | New York, USA |
- Principal Investigator: Ruben Coen-Cagli
- Project: Modelling Bayesian inference in neural circuits and analyzing neural population response recordings
Research Trainee | November 2017 to September 2019 |
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Albert Einstein College of Medicine | New York, USA |
- Principal Investigator: Ruben Coen-Cagli
Miscellaneous
Languages
- English (Mother tongue)
- German (Fluent, C1)
- French (Working knowledge)
Computer Skills
- Programming Languages: Haskell, C, Python, Matlab, R, Java, Prolog
- Advanced Linux user
- Experience maintaining a software library with approximately 10,000 lines of code
- Experience writing software for interfacing with scientific hardware