Sukbin Lim

Sukbin Lim is an Associate Professor of Neural Science at NYU Shanghai and a Global Network Associate Professor at the Center for Neural Science at NYU. Prior to joining NYU Shanghai, she was a postdoctoral researcher at University of California, Davis and University of Chicago.

Select Publications

• H. Gu, J. Lee, S. Kim, J. Lim, H. Lee, H. Lee, M. Choe, D. Yoo, J. Ryu, S. Lim [co-corresponding author], S. Lee (2025) Attractor dynamics of working memory explain a concurrent evolution of stimulus-specific and decision-consistent biases in visual estimation, Neuron, https://doi.org/10.1016/j.neuron.2025.07.003.
• Y. Jun, H. Zhang, S. Lim (2024) Sensory-memory interactions via modular structure explain errors in visual working memory, eLife, 13:RP95160.
• S. Chen, Q. Yang, S. Lim (2023) Efficient inference of synaptic learning rule with Gaussian process regression, iScience, 26 (3): 106182.
• J. Gu, S. Lim (2022) Unsupervised learning for robust working memory, PLoS Comput Biol., 18(5): e1009083.
• G. Mang, S. Lim, A. Chubykin (2021) Improved feature selectivity in V1 via theta oscillations induced by a familiar stimulus, Journal of Neuroscience, 41 (12) 2656-2667.

Education

• PhD, Mathematics
  New York University
• BS, Mathematics and Physics
  Seoul National University