M. Hashim Satti

M. Hashim Satti

Doctoral Candidate
Research interests: • cognitive and computational basis of decision making • neural correlates of action selection • neural signal processing • mathematical modelling • neural population encoding


Academic education

since 2020    Doctoral candidate, Max Planck School of Cognition, Leipzig, Germany
                        Doctoral research performed at Freie Universität Berlin, Germany
                        Supervisors: Hauke R. Heekeren, Rasmus Bruckner, and Peter Dayan
                        Lab rotations in the orientation phase: Peter Dayan, Christian F. Doeller, and Hauke Heekeren

2018–2019   Master of Science in Cognitive and Computational Neuroscience, The University of Sheffield, UK

2013–2017   Bachelor of Electrical Engineering, National University of Sciences and Technology (NUST), Pakistan


Scientific awards

2019              David Marr Prize, The University of Sheffield, UK
2014–2017  Merit-based scholarship, NUST, Pakistan



Tariq, T., Satti, M., Kamboh, H., Saeed, M., & Kamboh, A. (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. https://doi.org/10.1016/j.cmpb.2019.104986

Tariq, T., Satti, M. H., Saeed, M., & A. M. Kamboh, A. M. (2017). Low SNR neural spike detection using scaled energy operators for implantable brain circuits. In 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1074–1077. https://doi.org/10.1109/embc.2017.8037013


Poster presentation

Satti, M., Cichy, R., Schuck, M., Dayan, P., & Bruckner, R. (2022, November). Effects of threat imminence on learning under uncertainty [Poster]. 51st Annual Meeting of the Society for Neuroscience (Neuroscience 2022), San Diego, USA.



Photo: Anja Schneider

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