Alireza Modirshanechi
Fields of expertise
Computational and Theoretical Neuroscience
Reinforcement Learning
Statistical Learning and Bayesian Inference
Reinforcement Learning
Statistical Learning and Bayesian Inference
Biography
I am a computer science Ph.D. student at EPFL working under the supervision of Wulfram Gerstner. I work on computational models of learning and decision-making in the brain with a focus on (i) mathematical definitions of surprise and novelty, (ii) their contributions to human exploratory and adaptive behavior, and (iii) their manifestation in physiological measurements. I use Bayesian inference, reinforcement learning, and information theory to develop computational models which I test against behavioral and physiological data (EEG, MEG, fMRI, and single neuron recordings).Prior to joining EPFL, I received my B.Sc. in Electrical Engineering from the Sharif University of Technology, Tehran. During the last two years of my study, I worked on several research projects and completed my B.Sc. thesis under the supervision of Hamid Aghajan. My projects were mainly on (i) EEG-based decoding of surprise and (ii) fMRI-based classification of visual and auditory stimuli. My thesis won the 2nd best thesis award in the annual departmental distinguished thesis competition.
You can find my random scientific notes and educational articles here in my Medium account, and more information about me on my personal website.
Publications
Selected publications
A. Modirshanechi, W. Lin, H.A. Xu, M.H. Herzog, W. Gerstner Preprint on bioRxiv, 2023 |
The curse of optimism: a persistent distraction by novelty |
A. Modirshanechi, S. Becker, J. Brea, W. Gerstner Current Opinion in Neurobiology, 2023 |
Surprise and novelty in the brain |
A. Modirshanechi, J. Brea, W. Gerstner Journal of Mathematical Psychology, 2022 |
A taxonomy of surprise definitions |
H.A. Xu*, A. Modirshanechi*, M.P. Lehmann, W. Gerstner, M.H. Herzog PLoS Computational Biology, 2021 |
Novelty is not Surprise: Human exploratory and adaptive behavior in sequential decision-making |
V. Liakoni*, A. Modirshanechi*, W. Gerstner, J. Brea Neural Computation, 2021 |
Learning in Volatile Environments with the Bayes Factor Surprise |
A. Modirshanechi, M.M. Kiani, H. Aghajan NeuroImage, 2019 |
Trial-by-trial surprise-decoding model for visual and auditory binary oddball tasks |
Full list of publications - |
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Posts on Medium - |
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