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• I am a Postdoc Research Associate in Control Theory and Mathematical Neuroscience at Washington University in St. Louis, James McKelvey School of Engineering. I am a part of the Brain Dynamics and Control Research Group link.

My current work focuses on studying the mechanisms underlying brain functions that give rise to (or identify brain regions that are involved in)  cognitive behaviors such as thinking, speaking, reasoning, decision-making, problem-solving, etc.  We aim to carry out these questions via the control of large-scale brain activity building on whole-brain Mesoscale Individualized NeuroDynamic (MINDy) models singhmf/MINDy. See also https://github.com/rq-Chen/MINDy_rfMRI_stable?tab=readme-ov-file#models for more details.

• I was a Postdoc Control Theory researcher for months at Institut Polytechnique des Sciences Avancées, INRIA, L2S, France.

During this period, my research work focused on the prescribed exponential stabilization of delayed differential equations with applications to neural control. The main purpose was to model individual neurons model of Hopfield-type with a delayed proportional-derivative controller to address the challenges posed by hyperexcitability and to prevent the destabilizing transitions that can lead to seizure-like states.

• I defended my PhD thesis on October 2nd, 2023, in Control Theory and Mathematical Neuroscience (visual illusions and perception) at Paris Saclay University in the Laboratory of Signals and Systems (L2S, UMR 8506). The manuscript is available here, and the thesis defense slides are available here.

During my thesis journey, I have focused on the mathematical modeling of the MacKay-type visual illusions in neuroscience. Specifically, via mathematical modeling, analysis, and computing, my thesis work has explored how precisely the intrinsic circuitry of the primary visual cortex (V1) generates the patterns of activity that underlie the visual illusions observed in the visual MacKay effect---from redundant stimulation---and the psychophysical experiments recently reported by Billock and Tsou---those associated with a regular funnel pattern---localized either in the fovea or in the peripheral visual field. To this aim, we put forward a controllability---to account for visual stimuli that do not necessarily exhibit Euclidean symmetries as do spontaneous geometric visual hallucinations --- approach of a one-layer Amari-type neural field equation modeling the average membrane potential of V1 spiking neurons that take into account the sensory inputs from the retina. Then, we proved the qualitative concordance between the output patterns of the proposed neural field model and the observed human perceptual response to these intriguing visual illusions. Our developed theory is mechanistic since the reason  V1's neurons behave that way is far from being understood.