Dr. Serre is a Professor of Cognitive and Psychological Sciences as well as Computer Science. He received his Ph.D. in Neuroscience from MIT in 2006 and his M.Sc. in Electrical Engineering and Computer Science from Télécom Bretagne in France in 2000. His research focuses on understanding the neural computations that support visual perception, and it has been featured in various media outlets, including the BBC, The Economist, New Scientist, Scientific American, Technology Review, and Slashdot.
Dr. Serre serves as the Faculty Director of the Center for Computation and Visualization and the Associate Director of the Center for Computational Brain Science. He is also an affiliate of the Carney Institute for Brain Science and the Data Science Institute at Brown University. Additionally, he holds an International Chair in Artificial Intelligence at the Artificial and Natural Intelligence Toulouse Institute in France.
He has actively participated as an area chair and senior program committee member for prestigious machine learning and computer vision conferences, such as AAAI, CVPR, ICML, ICLR, and NeurIPS. Dr. Serre is a Neuroscience section editor for the journal PLOS Computational Biology.
He has received several awards, including the NSF Early Career Award, DARPA’s Young Faculty Award, and the Director's Award. Along with his team, he was awarded the 2021 PAMI Helmholtz Prize and the 2022 PAMI Mark Everingham Prize for their work on human action recognition.
| Muzellec S, Alamia A, Serre T, VanRullen R. "Enhancing deep neural networks through complex-valued representations and Kuramoto synchronization dynamics." ArXiv, 2025. |
| Pelgrim MH, Raman SS, Serre T, Buchsbaum D. "Evaluating Dogs' Real-World Visual Environment and Attention." Cognitive Science, vol. 49, no. 6, 2025, pp. e70080. |
| Roelfsema PR, Serre T. "Feature binding in biological and artificial vision." Trends in Cognitive Sciences, 2025. |
| Spagnuolo EJ, Wilf P, Serre T. "Decoding family-level features for modern and fossil leaves from computer-vision heat maps." American journal of botany, vol. 109, no. 5, 2022, pp. 768-788. |
| Vaishnav M, Cadene R, Alamia A, Linsley D, VanRullen R, Serre T. "Understanding the Computational Demands Underlying Visual Reasoning." Neural Computation, vol. 34, no. 5, 2022, pp. 1075-1099. |
| Wilf P, Wing SL, Meyer HW, Rose JA, Saha R, Serre T, Cúneo NR, Donovan MP, Erwin DM, Gandolfo MA, González-Akre E, Herrera F, Hu S, Iglesias A, Johnson KR, Karim TS, Zou X. "An image dataset of cleared, x-rayed, and fossil leaves vetted to plant family for human and machine learning." PhytoKeys, vol. 187, 2021, pp. 93-128. |
| Kreiman G, Serre T. "Beyond the feedforward sweep: feedback computations in the visual cortex." Annals of the New York Academy of Sciences, vol. 1464, no. 1, 2020, pp. 222-241. |
| Serre T. "Deep Learning: The Good, the Bad, and the Ugly." Annual review of vision science, vol. 5, 2019, pp. 399-426. |
| Kott O, Linsley D, Amin A, Karagounis A, Jeffers C, Golijanin D, Serre T, Gershman B. "Development of a Deep Learning Algorithm for the Histopathologic Diagnosis and Gleason Grading of Prostate Cancer Biopsies: A Pilot Study." European urology focus, vol. 7, no. 2, 2019, pp. 347-351. |
| Goodwill HL, Manzano-Nieves G, Gallo M, Lee HI, Oyerinde E, Serre T, Bath KG. "Early life stress leads to sex differences in development of depressive-like outcomes in a mouse model." Neuropsychopharmacology, vol. 44, no. 4, 2019, pp. 711-720. |
| Mély DA, Linsley D, Serre T. "Complementary surrounds explain diverse contextual phenomena across visual modalities." Psychological Review, vol. 125, no. 5, 2018, pp. 769-784. |
| D. Linsley, J.W. Linsley, T. Sharma, N. Meyers & T. Serre. "Learning to predict action potentials end-to-end from calcium imaging data." IEEE Annual Conference on Information Sciences and Systems, 2018. |
| Kim J, Ricci M, Serre T. "Not-So-CLEVR: learning same-different relations strains feedforward neural networks." Interface Focus, vol. 8, no. 4, 2018, pp. 20180011. |
| M. A. White, E. Kim, A. Duffy, R. Adalbert, B.U. Phillips, O.M. Peters, J. Stephenson, S. Yang, F. Massenzio, Z. Lin, S. Andrews, A. Segonds-Pichon, J. Metterville, L.M. Saksida, R. Mead, R.R Ribchester, Y. Barhomi, T. Serre, M.P. Coleman, Justin Fallon, T.J. Bussey, R.H. Brown Jr & J. Sreedharan. "TDP-43 gains function due to perturbed autoregulation in a Tardbp knock-in mouse model of ALS-FTD." Nature Neuroscience, vol. 21, no. 4, 2018, pp. 52-563. |
| D Linsley, S Eberhardt, T Sharma, P Gupta & T Serre. "What are the visual features underlying human versus machine vision?." IEEE ICCV, Workshop on the Mutual Benefit of Cognitive and Computer Vision, 2017. |
| Mély, David A., Kim, Junkyung, McGill, Mason, Guo, Yuliang, Serre, Thomas. "A systematic comparison between visual cues for boundary detection." Vision research, vol. 120, 2016, pp. 93-107. |
| Wilf, Peter, Zhang, Shengping, Chikkerur, Sharat, Little, Stefan A., Wing, Scott L., Serre, Thomas. "Computer vision cracks the leaf code." Proceedings of the National Academy of Sciences, vol. 113, no. 12, 2016, pp. 3305-3310. |
| Cauchoix, Maxime, Crouzet, Sébastien M., Fize, Denis, Serre, Thomas. "Fast ventral stream neural activity enables rapid visual categorization." NeuroImage, vol. 125, 2016, pp. 280-290. |
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S. Eberhardt*, J. Cader* & T. Serre.
"How deep is the feature analysis underlying rapid visual categorization?." Neural Information Processing Systems (NIPS), 2016.
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| Serre, Thomas. "Models of visual categorization." Wiley Interdisciplinary Reviews: Cognitive Science, vol. 7, no. 3, 2016, pp. 197-213. |
| Pascarella, A., Todaro, C., Clerc, M., Serre, T., Piana, M. "Source modeling of ElectroCorticoGraphy (ECoG) data: Stability analysis and spatial filtering." Journal of Neuroscience Methods, vol. 263, 2016, pp. 134-144. |
| Sofer, Imri, Crouzet, Sébastien M., Serre, Thomas. "Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual Categorization." PLOS Computational Biology, vol. 11, no. 9, 2015, pp. e1004456. |
| Hofmann, Jeffrey W., Zhao, Xiaoai, De Cecco, Marco, Peterson, Abigail L., Pagliaroli, Luca, Manivannan, Jayameenakshi, Hubbard, Gene B., Ikeno, Yuji, Zhang, Yongqing, Feng, Bin, Li, Xiaxi, Serre, Thomas, Qi, Wenbo, Van Remmen, Holly, Miller, Richard A., Bath, Kevin G., de Cabo, Rafael, Xu, Haiyan, Neretti, Nicola, Sedivy, John M. "Reduced expression of MYC increases longevity and enhances healthspan." Cell, vol. 160, no. 3, 2015, pp. 477-88. |
| Parker, Sarah M., Serre, Thomas. "Unsupervised invariance learning of transformation sequences in a model of object recognition yields selectivity for non-accidental properties." Front. Comput. Neurosci., vol. 9, 2015. |
| Kuehne, Hilde, Arslan, Ali, Serre, Thomas. "The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities." 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014. |
| Cauchoix, M., Barragan-Jason, G., Serre, T., Barbeau, E. J. "The Neural Dynamics of Face Detection in the Wild Revealed by MVPA." Journal of Neuroscience, vol. 34, no. 3, 2014, pp. 846-854. |
| Poggio, Tomaso, Serre, Thomas. "Models of visual cortex." Scholarpedia, vol. 8, no. 4, 2013, pp. 3516. |
| Heindel, William, Festa, Elena, Ott, Brian, Sofer, Imri, Serre, Thomas. "Rapid visual categorization as a sensitive measure of early Alzheimer's disease." Alzheimer's & Dementia, vol. 9, no. 4, 2013, pp. P451-P452. |
| Leussis, Melanie P., Berry-Scott, Erin M., Saito, Mai, Jhuang, Hueihan, de Haan, Georgius, Alkan, Ozan, Luce, Catherine J., Madison, Jon M., Sklar, Pamela, Serre, Thomas, Root, David E., Petryshen, Tracey L. "The ANK3 Bipolar Disorder Gene Regulates Psychiatric-Related Behaviors That Are Modulated by Lithium and Stress." Biological Psychiatry, vol. 73, no. 7, 2013, pp. 683-690. |
| Zhang, Jun, Barhomi, Youssef, Serre, Thomas. "A New Biologically Inspired Color Image Descriptor." European Conference on Computer Vision, 2012, pp. 312-324. |
| Cauchoix, Maxime, Arslan, Ali Bilgin, Fize, Denis, Serre, Thomas. "The Neural Dynamics of Visual Processing in Monkey Extrastriate Cortex: A Comparison between Univariate and Multivariate Techniques." Neural Information Processing Systems, 2012, pp. 164-171. |
| Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T. "HMDB: A large video database for human motion recognition." 2011 International Conference on Computer Vision, 2011. |
| Zhang, Y., Meyers, E. M., Bichot, N. P., Serre, T., Poggio, T. A., Desimone, R. "Object decoding with attention in inferior temporal cortex." Proceedings of the National Academy of Sciences, vol. 108, no. 21, 2011, pp. 8850-8855. |
| Serre, Thomas, Poggio, Tomaso. "A neuromorphic approach to computer vision." Communications of the ACM, vol. 53, no. 10, 2010, pp. 54. |
| Jhuang, Hueihan, Garrote, Estibaliz, Yu, Xinlin, Khilnani, Vinita, Poggio, Tomaso, Steele, Andrew D., Serre, Thomas. "Automated home-cage behavioural phenotyping of mice." Nature Communications, vol. 1, no. 6, 2010, pp. 1-9. |
| Reddy, Leila, Tsuchiya, Naotsugu, Serre, Thomas. "Reading the mind's eye: Decoding category information during mental imagery." NeuroImage, vol. 50, no. 2, 2010, pp. 818-825. |
| Kliper, Roi, Serre, Thomas, Weinshall, Daphna, Nelkenz, Israel. "The story of a single cell: Peeking into the semantics of spikes." 2010 2nd International Workshop on Cognitive Information Processing, 2010. |
| Jhuang, Hueihan, Garrote, Estibaliz, Edelman, Nicholas, Poggio, Tomaso, Steele, Andrew, Serre, Thomas. "Trainable, vision-based automated home cage behavioral phenotyping." Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research - MB '10, 2010. |
| Chikkerur, Sharat, Serre, Thomas, Tan, Cheston, Poggio, Tomaso. "What and where: A Bayesian inference theory of attention." Vision research, vol. 50, no. 22, 2010, pp. 2233-2247. |
| Jhuang, H., Serre, T., Wolf, L., Poggio, T. "A Biologically Inspired System for Action Recognition." 2007 IEEE 11th International Conference on Computer Vision, 2007. |
| Serre, T., Oliva, A., Poggio, T. "A feedforward architecture accounts for rapid categorization." Proceedings of the National Academy of Sciences, vol. 104, no. 15, 2007, pp. 6424-6429. |
| Serre, Thomas, Wolf, Lior, Bileschi, Stanley, Riesenhuber, Maximilian, Poggio, Tomaso. "Robust Object Recognition with Cortex-Like Mechanisms." IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 3, 2007, pp. 411-426. |
| Sigala, Rodrigo, Serre, Thomas, Poggio, Tomaso, Giese, Martin. "Learning Features of Intermediate Complexity for the Recognition of Biological Motion." International Conference on Artificial Neural Networks, 2005, pp. 241-246. |
| Serre, T., Wolf, L., Poggio, T. "Object Recognition with Features Inspired by Visual Cortex." 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005. |
Our laboratory investigates the computational principles underlying visual perception in the primate brain through an integrative approach that spans multiple levels of analysis. We develop computational neuroscience models that emulate the feedforward and recurrent processes of the visual cortex, seeking to explain how neural circuits give rise to rapid object recognition, visual reasoning, and scene understanding. Our research combines theoretical modeling with experimental validation using human psychophysics, EEG recordings, and neuroimaging, while leveraging state-of-the-art deep learning architectures. We study fundamental questions including how the brain achieves invariant object recognition, the role of oscillatory dynamics in visual reasoning, the mechanisms of attention and perceptual grouping, and the computational strategies that enable "vision at a glance" – the remarkable ability to categorize complex scenes within milliseconds.
We believe that understanding the computational strategies evolved by biological vision systems will lead to transformative advances in both neuroscience and artificial intelligence. Our mission is to develop a unified, mechanistic theory of visual processing that not only explains human visual perception and its neural basis, but also inspires the next generation of machine vision algorithms. By identifying canonical computations shared across visual domains and cortical areas, we aim to bridge the gap between biological and artificial intelligence, creating brain-inspired models that are both interpretable and capable of human-like visual reasoning. Our work has direct applications in developing robust computer vision systems, automated behavioral phenotyping for neurodegenerative disease research, and advancing our fundamental understanding of how neural computations give rise to intelligent behavior. Through close collaboration between theorists and experimentalists, we strive to build models that are not merely descriptive, but predictive of both neural responses and behavioral outcomes across diverse visual tasks.
| Year | Degree | Institution |
|---|---|---|
| 2006 | PhD | Massachusetts Institute of Technology |
| 2000 | MS | Université de Rennes |
| 2000 | MS | École Nationale Supérieure des Telecommunications de Bretagne |
| 1997 | BS | Lycee Pasteur |
| Postdoctoral Associate | MIT, Mc Govern Institute for Brain Research | 2006-2010 | Cambridge, MA |
– Elected fellow in the ELLIS Program, Natural Intelligence • 2024
– Brown Mid‐Career Research Achievement Award • 2024
– Awarded Thomas J. Watson, Sr. Professor of Science endowed Chair • 2023
– Awarded Manning Assistant Professorship • 2010
– PAMI Mark Everingham Prize for pioneering human action recognition datasets. • 2022
– PAMI Helmholtz Prize for significant impact on computer vision research. • 2021
– Awarded International Chair in AI (ANITI, France) • 2019–present • 2019
– DARPA Director’s Award • 2016
– Distinguished Speaker in Behavioral and Brain Sciences, Cornell University (Ithaca, NY) • 2016
– DARPA Young Faculty Award • 2014
– Professeur Invité, Lorient University (Lorient, France) • 2014
– NSF Early Career Award • 2013
– Manning Assistant Professorship • 2013
– Teaching with Technology Course Design Award • 2012
– Sheridan Junior Faculty Teaching Fellows Program • 2011–2012
| Name | Title |
|---|---|
| Borton, David | Associate Professor of Engineering, Associate Professor of Neurosurgery, Associate Professor of Brain Science |
| Domini, Fulvio | Professor of Cognitive and Psychological Sciences |
| Fallon, Justin | Professor of Medical Science, Professor of Psychiatry and Human Behavior |
| Frank, Michael | Edgar L. Marston Professor of Psychology, Professor of Brain Science |
| Pavlick, Ellie | Briger Family Distinguished Associate Professor of Computer Science, Associate Professor of Cognitive and Psychological Sciences |
| Sheinberg, David | Professor of Neuroscience, Graduate Program Director for the Neuroscience Graduate Program |
| Associate Director. Brown Unversity , 2020- |
| Faculty Director. brown, 2018- |
| CLPS 0950 - Introduction to programming |
| CLPS 1291 - Computational Methods for Mind, Brain and Behavior |
| CLPS 1950 - Deep Learning in Brains, Minds and Machines |
