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Muhammad Hashim Satti


Learning Lab

Ph.D. Candidate

Habelschwerdter Allee 45
Room JK25/222e
14195 Berlin
2020 -

PhD canditate FU Berlin and
Max Planck School of Cognition

2018 - 2019

MSc (Cognitive and Computational Neuroscience),
Department of Psychology, The University of Sheffield, UK

2013 - 2017 BSc (Electrical Engineering),
School of Electrical Engineering & Computer Sciences, NUST, Pakistan

My research interests include adaptive decision making, aversive learning under uncertainty and action selection. In my doctoral project, I am working to understand how anxiety effects learning and decision making, especially when individuals are faced with uncertainty and varying levels of threat. This project is being supervised by Rasmus Bruckner, Hauke Heekeren and Peter Dayan. In my previous projects, I have worked on identification and classification of Arkypallidal neurons in the basal ganglia, which are implicated in the action selection and response inhibition. I have also worked on developing efficient methods for automatic detection and sorting of neural spikes.

Satti, M. H., Wille, K., Nassar, M. R., Cichy, R. M., Schuck, N. W., Dayan, P., & Bruckner, R. (2024). Absence of systematic effects of trait anxiety on learning under uncertainty. Proceedings of the conference on Cognitive Computational Neuroscience 2024. <Link>

Tariq, T., Satti, M. H., Kamboh, H. M., Saeed, M., & Kamboh, A. M. (2019). Computationally efficient fully-automatic online neural spike detection and sorting in presence of multi-unit activity for implantable circuits. Computer Methods and Programs in Biomedicine179, 104986. <PDF>

Tariq, T., Satti, M. H., Saeed, M., and Kamboh, A. M. (2017). Low SNR neural spike detection using scaled energy operators for implantable brain circuits. 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). <PDF>