Research Interests
System Identification
Nonlinear Dynamical Systems
Mathematical Neuroscience
Brain Connectomics
Control Theory
Machine Learning
Education
Neuroscience, PhD, Washington University St. Louis
Courses Taught
STAT 447: Data Science Programming Methods
Additional Campus Affiliations
Assistant Professor, Statistics
Assistant Professor, Beckman Institute for Advanced Science and Technology
Recent Publications
Levenstein, D., Alvarez, V. A., Amarasingham, A., Azab, H., Chen, Z. S., Gerkin, R. C., Hasenstaub, A., Iyer, R., Jolivet, R. B., Marzen, S., Monaco, J. D., Prinz, A. A., Quraishi, S., Santamaria, F., Shivkumar, S., Singh, M. F., Traub, R., Nadim, F., Rotstein, H. G., & Redish, A. D. (2023). On the Role of Theory and Modeling in Neuroscience. Journal of Neuroscience, 43(7), 1074-1088. https://doi.org/10.1523/JNEUROSCI.1179-22.2022
Etzel, J. A., Brough, R. E., Freund, M. C., Kizhner, A., Lin, Y., Singh, M. F., Tang, R., Tay, A., Wang, A., & Braver, T. S. (2022). The Dual Mechanisms of Cognitive Control dataset, a theoretically-guided within-subject task fMRI battery. Scientific Data, 9(1), Article 114. https://doi.org/10.1038/s41597-022-01226-4
Singh, M. F., Cole, M. W., Braver, T. S., & Ching, S. (2022). Control-theoretic integration of stimulation and electrophysiology for cognitive enhancement. Frontiers in Neuroimaging, 1. https://doi.org/10.3389/fnimg.2022.982288
Singh, M. F., Cole, M. W., Braver, T. S., & Ching, S. N. (2022). Developing control-theoretic objectives for large-scale brain dynamics and cognitive enhancement. Annual Reviews in Control, 54, 363-376. https://doi.org/10.1016/j.arcontrol.2022.05.001
Singh, M. F., Wang, M., Cole, M. W., & Ching, S. N. (2022). Efficient identification for modeling high-dimensional brain dynamics. In 2022 American Control Conference, ACC 2022 (pp. 1353-1358). (Proceedings of the American Control Conference; Vol. 2022-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC53348.2022.9867232