2024 - now Assistant Professor, Department of Physics, Emory University, Atlanta, GA
2021 - 2024 Member, Simons Center for Systems Biology, School of Natural Sciences, Institute for Advanced Study, Princeton, NJ
2017 - 2021 Research Associate, Initiative for the Theoretical Sciences, The Graduate Center, CUNY, New York, NY
Independent postdoctoral research at the intersection of statistical physics, machine learning, and computational neuroscience
2014 - 2017 Research Assistant Professor, Simons Center for Geometry and Physics, Stony Brook University, Stony Brook, NY
Independent postdoctoral research in mathematical condensed matter physics
2018 General workshop award ($20,000) from Institute for Complex Adaptive Matter (ICAM) for "Machine Learning and Statistical Physics" (with S. Gopalakrishnan, V. Oganesyan, and D. Schwab)
2016 Invited paper for Emerging Talents special issue of Journal Physics A: Mathematical and Theoretical
2013 Gregor Wentzel Research Prize, University of Chicago, for outstanding work in theoretical physics
2010-2012 University of Chicago Robert A. Millikan Fellowship (U.S. DOE Graduate Assistance in Areas of National Need (GAANN) Fellowship)
2008 Distinction in general scholarship, UC Berkeley (cum laude equivalent)
2008 High Honors in Physics UC Berkeley (magna cum laude equivalent)
TC & K. Krishnamurthy, Emergence of Robust Memory Manifolds, PRX Life 2025
W. Zhong, TC, A. Georgiou, I. Shnayderman, M. Katkov, M. Tsodyks, Random Tree Model of Meaningful Memory, PRL 2025
Featured in Physics Magazine: How we remember stories
TC, Statistical Mechanics of Semantic Compression, preprint
A. Georgiou, TC, M. Katkov, M. Tsodyks, Large-scale study of human memory for meaningful narratives, Learning & Memory, 2025
A. Cowsik, TC, & P. Glorioso, Flatter, faster: scaling momentum for optimal speedup of SGD , 2022
T. D. Kim, TC, & K. Krishnamurthy, Trainability, Expressivity and Interpretability in Gated Neural ODEs , ICML 2023
K. Krishnamurthy, TC, & D. J. Schwab, Theory of Gating in Recurrent Neural Networks, Phys. Rev. X 2022
TC, K. Krishnamurthy, & D. J. Schwab, Gating creates slow modes and controls phase-space complexity in GRUs and LSTMs, MSML 2020
Full List of Publications can be found on Google Scholar
Dynamics of Gated Recurrent Neural Networks, City College of New York Physics Colloquium, Sept. 16, 2020
Gating Creates Slow Modes and Controls Phase-space Complexity in GRUs and LSTMs, Mathematical and Scientific Machine Learning (MSML) Virtual Conference July 20, 2020.