Robert Yang is interested in building neural network and circuit models of brain functions. He has contributed to the modern use of recurrent neural networks as a modeling tool in neuroscience. His work has shed light on neural mechanisms for cognitive flexibility. The Yang lab focuses on building multi-scale, multi-system integrative models of higher cognitive functions.
Searle Scholar, 2022-2025
Junior Fellow, Simons Society of Fellows, 2018-2021
Dean’s Outstanding Dissertation Award in the Sciences, New York University, 2018
Samuel J. and Joan B. Williamson Fellowship, New York University, 2016
MacCracken Fellowship, New York University, 2013-2016
Benz Scholarship, Peking University, 2011
National Scholarship of China, 2010
A computer model can teach itself to smell in just a few minutes. When it does, Robert Yang found, it builds a neural network that closely mimics the olfactory circuits that animal brains use to process odors.
Nayebi, A, Rajalingham, R, Jazayeri, M, Yang, GR. Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes. ArXiv. 2023; :. . PubMed PMID:37292459 PubMed Central PMC10246064.
Molano-Mazón, M, Shao, Y, Duque, D, Yang, GR, Ostojic, S, de la Rocha, J et al.. Recurrent networks endowed with structural priors explain suboptimal animal behavior. Curr Biol. 2023;33 (4):622-638.e7. doi: 10.1016/j.cub.2022.12.044. PubMed PMID:36657448 .
Ito, T, Yang, GR, Laurent, P, Schultz, DH, Cole, MW. Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior. Nat Commun. 2022;13 (1):673. doi: 10.1038/s41467-022-28323-7. PubMed PMID:35115530 PubMed Central PMC8814166.