Gabriel Kreiman

Gabriel Kreiman
Associate Director, Research Module Co-Leader

Associated Research Module: 

Associated Research Thrust: 

Gabriel Kreiman is Professor in the Department of Ophthalmology at Harvard Medical School. He is also a faculty at Children’s Hospital, the Department of Neurology at HMS, the Center for Brain Science, the Swartz Center for Theoretical Neuroscience and the Mind, Brain and Behavior Initiative at Harvard. He studied Physical Chemistry for his B.Sc. at the University of Buenos Aires, Argentina (1996). He received a M.Sc. and Ph.D. (Biology and Computational Neuroscience) from the California Institute of Technology in 2002 under Prof. Koch’s mentorship. He pursued postdoctoral work with Prof. Poggio at MIT. The Kreiman Laboratory combines computational modeling, neurophysiological recordings and psychophysical measurements to further our understanding of the neuronal circuits and mechanisms underlying perception and cognition.

Phone:  (781) 214-0756

Current Advisees

Marcelo Armendariz - Postdoc
Frederico Azevedo - Research Scientist
Trenton Bricken - Graduate Student
Chenguang Li - Graduate Student
Spandan Madan - Graduate Student
Diego Mendoza-Halliday - Research Scientist
Pranav Misra - Graduate Student
Martin Schrimpf - Research Scientist
Morgan Talbot - Graduate Student
Annabelle Tao - Graduate Student
Will Xiao - Graduate Student
Zechen Zhang - Graduate Student

Past Advisees

Katarina Bendtz - Postdoc, Human Frontiers Science Program Cross Disciplinary Fellow
Stephen Casper - Undergrad
Emma Giles - Graduate Student
Stephan Grzelkowski - Graduate Student
Eleonora Iaselli - Graduate Student
Jiye Kim - Postdoc
Emma Krause - Graduate Student
Bill Lotter - Graduate Student
Boying Meng - Graduate Student
Joseph Olson - Graduate Student
Kristofor Payer - Research Staff
Nimrod Shaham - Postdoc
Duncan Stothers - Undergraduate Student
Kasper Vinken - Postdoc
Jerry Wang - Graduate Student
Farahnaz Wick - Postdoc
Kevin Wu - Graduate Student
Eric Wu - Graduate Student
Yuchen Xiao - Graduate Student
Zihao Xu - Graduate Student
Mengmi Zhang - Postdoc


CBMM Publications

A. Bardon, Xiao, W., Ponce, C. R., Livingstone, M. S., and Kreiman, G., Face neurons encode nonsemantic features, Proceedings of the National Academy of Sciences, vol. 119, no. 16, 2022.
G. Dellaferrera and Kreiman, G., Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass, Proceedings of the 39th International Conference on Machine Learning, PMLR, vol. 162. pp. 4937-4955, 2022.
G. Kreiman, Biological and Computer Vision. Cambridge, UK: Cambridge University Press, 2021.
M. Zhang and Kreiman, G., Beauty is in the eye of the machine, Nature Human Behaviour, vol. 5, no. 6, pp. 675 - 676, 2021.
G. Kreiman and Serre, T., Beyond the feedforward sweep: feedback computations in the visual cortex, Ann. N.Y. Acad. Sci. | Special Issue: The Year in Cognitive Neuroscience, vol. 1464, no. 1, pp. 222-241, 2020.
G. Kreiman and Serre, T., Beyond the feedforward sweep: feedback computations in the visual cortex, Annals of the New York Academy of Sciences, vol. 1464, no. 1, pp. 222 - 241, 2020.
G. Ben-Yosef, Kreiman, G., and Ullman, S., What can human minimal videos tell us about dynamic recognition models?, in International Conference on Learning Representations (ICLR 2020), Virtual Conference, 2020.
G. Kreiman, It's a small dimensional world after all, Physics of Life Reviews, vol. 29, pp. 96 - 97, 2019.
W. Eric, Kevin, W., and Kreiman, G., Learning scene gist with convolutional neural networks to improve object recognition, 2018 52nd Annual Conference on Information Sciences and Systems (CISS). Princeton, NJ, 2018.
A. Palepu and Kreiman, G., Development of automated interictal spike detector, 40th International Conference of the IEEE Engineering in Medicine and Biology Society - EMBC 2018. Honolulu, HI, 2018.
H. Tang, Kreiman, G., and Zhao, Q., Recognition of occluded objects, in Computational and Cognitive Neuroscience of Vision, Springer Singapore, 2017.
G. Kreiman, A null model for cortical representations with grandmothers galore, Language, Cognition and Neuroscience, pp. 274 - 285, 2017.
W. Lotter, Kreiman, G., and Cox, D., Unsupervised Learning of Visual Structure using Predictive Generative Networks, in International Conference on Learning Representations (ICLR), San Juan, Puerto Rico, 2016.
J. Singer, Madsen, J., Anderson, W. S., and Kreiman, G., Sensitivity to timing and order in human visual cortex, Journal of Neurophysiology, vol. 113, no. 5, pp. 1656 - 1669, 2015.
G. Kreiman, Rutishauser, U., Cerf, M., and Fried, I., The next ten years and beyond, in Single neuron studies of the human brain. Probing cognition, 2014.