M. Hashim Satti

Doctoral Candidate

M.Hashim.Satti@maxplanckschools.de

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

Publications

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 Biomedicine, 179, 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