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I have been interested in the biological system since high school and received my bachelor’s degree from Jinlin University in biotechnology, where I was fortunate to find my passion in neurobiology from a small chapter of animal physiology. This led to my decision to stay and study the mechanism of depression during my Master in Neurophysiology. But later I convinced myself I should start from understanding how a normal brain works and received my Ph.D degree from Institute of Neuroscience, Chinese Academy of Sciences, where I worked with Ning-long Xu to study decision-making in mice by designing psychophysics experiments, which are normally used in primates studies, for mice combined with cutting-edge neural recording technology such as two-photon calcium imaging. While fascinated by the complexity of the brain, I realized that I need to learn more skills, such as computation and machine learning, in order to answer most of the questions related to cognitive functions. So I decided to join Janelia and am working with Marius Pachitariu and Carsen Stringer, both have strong computational machine learning background, to study the neural mechanism underlying visual learning, including visual generalization using various data analysis methods and computational tools. We train mice to perform a visual task inside a virtual reality (VR) environment while recording a large population of neurons (more than 50,000) from visual cortex, as well as surrounding areas to investigate how different learnings (supervised vs unsupervised learning) shape the neural representation and how they support high cognitive functions such as visual generalization.