We use computational models to explain human learning and planning. We draw from reinforcement learning and bayesian frameworks to study basic cognition and psychopathology.
We are part of the Department of Psychology at Bar-Ilan University, near Tel Aviv. We welcome prospective trainees from psychology, neuroscience, computer science, and engineering.
Watch a TED-style talk describing our research here:
news
| Aug 25, 2026 | Our first lab publication! Article by Hadas Schiff and Paul B. Sharp in Topics in Cognitive Science shows that individuals high in trait worry undergeneralize actions learned under social threat when planning in novel contexts. |
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| Jul 17, 2026 | The lab traveled to the Computational Psychiatry Conference 2026 at Yale, where Noa Yadid won a best poster award. Congratulations Noa! |
| Oct 29, 2025 | MA fellows Dafna Yavetz (BA Princeton), Noa Yadid (BA BIU), and Adi Pizanti (BA Tel-Aviv College) begin as new lab members!!! |
| Jul 21, 2025 | Sharp lab wins a large grant (~ 1 million USD) to investigate computations of planning efficiency and inefficiency in health and psychopathology! |
| Jan 25, 2025 | Paul will chair a symposium at upcoming computational psychiatry conference on cognitive map biases in psychopathology |