Thibaud Taillefumier

Biography

Originally trained in Mathematical Physics, Thibaud Taillefumier completed his PhD in Biophysics under the supervision of Professor Marcelo Magnasco at The Rockefeller University. There, he developed novel analytical and computational techniques to characterize different modalities of neural coding and acquired experimental experience by performing electrophysiological recordings. As an Associate Research Scholar at Princeton, he expanded his work on neural assemblies within the framework of stochastic dynamics and non-equilibrium thermodynamics with Professor Curtis G. Callan, Jr. In parallel, he studied bacterial communities from the perspective of information and optimization theory with Professor Ned S. Wingreen. Thibaud Taillefumier is now an Associate Professor jointly appointed by the Departments of Mathematics and Neuroscience at UT Austin.

Thibaud's research focuses on relating function and structure in finite neural network models, quantifying the information capabilities of mnemonic neural codes,  and understanding timing in neural dynamics to answer questions such as: Can one capture complex neural dynamics via realistic, yet tractable, neural network models? What are the information capabilities of the neural codes involved in memory formation and memory retrieval? How can neural networks reliably process temporal information in spite of biological noise?

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