Researcher · Tsinghua University
Chao Xie谢超
Department of Psychological and Cognitive Sciences, Tsinghua University
Research Vision
AI gives us a new opportunity to study the human brain — perhaps the most complex system in the universe. Using brain imaging and computational models, we seek to understand how human cognition works and develops across the lifespan.
By studying naturalistic behavior, we explore the complexity and creativity of human thought, while computational psychiatry connects these insights to mental health. In trying to understand the brain, we look not only to the stars above us, but also to the depths within ourselves.
Selected Publications
Recent Work
A shared neural basis underlying psychiatric comorbidity
Xie C, Xiang ST, et al.
Hierarchical Neurocognitive Model of Externalizing and Internalizing Comorbidity
Xie C, Xiang S, Zheng Y, et al.
Neural Network Involving Medial Orbitofrontal Cortex and Dorsal Periaqueductal Gray Regulation in Human Alcohol Abuse
Jia T*, Xie C*, Banaschewski T, et al.
Research
Research Areas
Neuroimaging in Psychiatric Disorders
Investigating neural correlates of psychiatric disorders using structural and functional MRI
Computational Modeling of Cognition
Developing mathematical and computational models to understand cognitive processes and decision-making
AI-Powered Clinical Tools
Developing artificial intelligence tools for diagnosis, prognosis, and treatment planning in psychiatry
Naturalistic Behavior Analysis
Understanding human behavior in real-world settings using wearable sensors and video analysis
Opportunities
Join Us
Brain Science
Study the human brain using neuroimaging techniques to understand neural mechanisms underlying cognition and behavior.
You Need:
AI + Naturalistic Behavior
Apply artificial intelligence and large language models to analyze naturalistic human behavior and cognitive processes.
You Need:
Mental Health
Bridge neuroscience and clinical practice to understand mental disorders and develop computational models for psychiatry.
You Need:
Recommended Background Knowledge
Brain Science
- • Neuroimaging analysis (FSL, SPM, AFNI)
- • Brain anatomy and connectivity
- • Statistics and experimental design
AI + Behavior
- • Machine learning / Deep learning
- • Natural language processing
- • Programming (Python, PyTorch)
Mental Health
- • Psychopathology and diagnosis
- • Clinical assessment methods
- • Translational research
Interested in Collaboration or Joining the Lab?
We welcome motivated PhD students, postdocs, and research collaborators in computational neuroscience, psychiatry, and AI.