Hugo Soulat
I am a third year PhD student in Computational Neuroscience and Machine Learning at Gatsby Unit where I use and develop mathematical and statistical tools to address brain related questions. I am currently working under the supervision of Prof. Maneesh Sahani on the modeling of neural population spike trains. Before starting my PhD, I obtained two master degrees in systems engineering and bioengineering from École Polytechnique (France) and EPFL (Switzerland) after which I worked two years with Prof. Emery Brown and Prof. Patrick Purdon as a data analyst and research assistant in the Neuroscience Statistics Research Laboratory (Harvard-MIT) and the Purdon's Laboratory (Harvard-MGH). There, I developed methods to study cross-frequency coupled EEG signals and simultaneous fMRI recordings aiming at characterizing the mechanism of general anaesthesia on human subjects.
Publications
[1] Soulat,H., Keshavarzi,S., Margrie, TW. & Sahani, M. (2021) “Probabilistic Tensor Decomposition of Neural Population Spiking Activity.” Advances in Neural Information Processing Systems 34 (accepted with spotlight).
[2] Gutiérrez, R. G., Egaña, J. I., Maldonado, F. A., Sáez, I. A., Reyes, F. I., Soulat,H., Purdon, PL., & Penna, A. (2021) “Association between lower preoperative cognition with intraoperative electroencephalographic features consistentwith deep states of anesthesia in older patients: an observational cohort study.“ Anesthesia & Analgesia, 133(1), 205-214.
[3] Beck, A., Soulat, H., Stephen ,E. , Purdon, PL. (2020), I-116. “State space oscillator models to identify and parameterize oscillatory signals in EEG“ (2020) COSYNE.
[4] Soulat, H., Beck, A., Stephen ,E. , Purdon, PL. (2020), I-116. “State space methods for phase amplitude coupling analysis“. (2019) bioRxiv : 772145.
[5] Song, AH. , Chlon L., Soulat, H. , Tauber,J. , Subramanian, S., Ba, D , Prerau, MJ. (2019) ”Multitaper Infinite Hidden Markov Model for EEG" Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE
Teaching
Probabilistic and Supervised Learning. Teaching Assistant. Master Level Machine Learning Class.
Systems and Theoretical Neuroscience. Teaching Assistant. Master Level Neuroscience Class.
Approximate Inference and Learning in Probabilistic Models. Teaching Assistant. Master Level Machine Learning Class.
In2scienceUK. Volonteer Mentor. Social mobility and diversity program.