• Computational Neuroscience for Decision-Making: How does decision-making arise from the connectome of single neurons? By analyzing patterns of neural activity, we explain behavior and neural activity across species, including humans, monkeys, rats, and mice, to understand the neural circuit computation underlying decision-making.
• Cognitive Dynamics of Decision-Making: How does human decision-making unfold over time? Using methods such as mouse tracking and fMRI brain imaging, we track the decision-making processes in real time. By studying the brain as a dynamical system, we build models to uncover the latent structures of circuit computation for decision-making.
• Decision-Making and Artificial Neural Networks: We train artificial neural networks for decision-making in dynamic, uncertain environments, to understand how neural systems can make autonomous decisions in complex situations.

2012.09 - 2018.07 Peking University, Ph.D. in Cognitive Psychology

2008.09 - 2012.06 Shanghai Jiaotong University, Bachelor's Degree in Physics

   

2022.10 - 2026.03 NYU Grossman School of Medicine, Research Scientist

2019.03 - 2022.10 NYU Grossman School of Medicine, Postdoc

   

（1） Early versus late noise differentially enhances or degrades context-dependent choice, NATURE COMMUNICATIONS, 2025, 

（2） A levels-of-analysis framework for studying social emotions, Nature Reviews Psychology, 2024, 

（3） The competition dynamics of approach and avoidance motivations following interpersonal transgression, PNAS, 2023, 

（4） Flexible control of representational dynamics in a disinhibition-based model of decision-making, ELIFE, 2023, 

（5） High-definition tDCS alters impulsivity in a baseline-dependent manner, NEUROIMAGE, 2016, 

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Decision-Making Cognitive Neuroscience Computational Neuroscience Artificial Intelligence