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My research focuses on uncovering the principles by which biological neural networks perform computation. I am particularly interested in identifying inductive biases in brain circuits and translating them to new designs of artificial neural networks.
My teaching integrates theory with hands-on computation. I aim to help students apply computational techniques to tackle complex problems in science and engineering.
Li C, Imam N, Manohar R. A deterministic neuromorphic architecture with scalable time synchronization. Nature Communications. 2025.
Chandravadia N, Imam N. Neural rhythms as priors of speech computations. bioRxiv. 2025.
Imam N, Kielo M, Trude BM, Finlay BL. Dual Computational Systems in the Development and Evolution of Mammalian Brains. bioRxiv. 2025.
Sharafeldin A, Imam N, Choi H. Active sensing with predictive coding and uncertainty minimization. Patterns. 2024.
Xie Y, Arcaro M, Imam N. Modeling the formation of extrastriate primate visual field maps. Journal of Vision. 2024.
Manipatruni S, Imam N, Odinaka I, Rios R, Dokania RK, Mathuriya A. Asynchronous circuit with threshold logic. U.S. Patent No. 11,716,083. 2023.
Imam N, L. Finlay B. Self-organization of cortical areas in the development and evolution of neocortex. Proceedings of the National Academy of Sciences. 2020.