Dr. Eric Schulz

Max Planck Research Group Leader
Research Group Computational Principles of Intelligence

Curriculum Vitae

Eric Schulz did his undergrad in Psychology at Humboldt University in Berlin, followed by a MSc in Cognitive and Decision Sciences at University College London (UCL), a MSc in Applied Statistics at the University of Oxford, and a MRes in Computer Science again at UCL. He finished his PhD at UCL in 2017, where he worked on generalization and exploration in reinforcement learning and was supervised by Maarten Speekenbrink. From 2017 to 2019, he was a Data Science Postdoctoral Fellow at Harvard University, where he worked with Samuel Gershman and Joshua Tenenbaum on computational models of learning and decision making. He is a recipient of the Robert J. Glushko Prize for Outstanding Doctoral Dissertation in Cognitive Science and a Jacobs Foundation Research Fellowship.

Important Publications: 
Schulz, E., Franklin, N.T. & Gershman, S.J. (2020). Finding structure in multi-armed bandits. Cognitive Psychology. 
Dasgupta, I., Schulz, E., Tenenbaum, J.B. & Gershman, S.J. (2020). A theory of learning to infer. Psychological Review. 
Schulz, E., Wu, C.M., Ruggeri, A. & Meder, B. (2019). Searching for rewards like a child means less generalization and more directed exploration. Psychological Science. 
Schulz, E., Bhui, R. & Love, B.C., Brier, B., Todd, M.T. & Gershman, S.J. (2019). Structured, uncertainty-driven exploration in real-world consumer choice. Proceedings of the National Academy of Sciences. 
Schulz, E. & Gershman, S.J. (2019). The algorithmic architecture of exploration in the human brain. Current Opinion in Neurobiology. 
Wu, C.M., Schulz, E., Speekenbrink, M., Nelson, J.D., & Meder, B. (2018). Generalization guides human exploration in vast decision spaces. Nature Human Behaviour. 
Schulz, E., Tenenbaum, J.B., Duvenaud, D. Speekenbrink, M., & Gershman, S.J. (2017). Compositional Inductive Biases in Function Learning. Cognitive Psychology.
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