School of Medicine
Showing 31-40 of 70 Results
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Douglas F. Levinson, M.D.
Walter E. Nichols, M.D. Professor in the School of Medicine, Emeritus
Current Research and Scholarly InterestsDr. Levinson directs the Program on the Genetics of Brain Function in the Department of Psychiatry and Behavioral Sciences. The program investigates the genetic basis of psychiatric disorders (schizophrenia and major depressive disorder), using genetic association, linkage and resequencing methodologies. In collaboration with Dr. Alice Whittemore, we are also actively engaged in statistical methods testing and development for genetic research.
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Lei Li
Postdoctoral Scholar, Psychiatry
BioPh.D., University of Electronic Science and Technology of China, Biomedical engineering 2024
B.E., University of Electronic Science and Technology of China, Biomedical engineering 2019 -
Celine Jia Rong Lim
Postdoctoral Scholar, Psychiatry
BioDr. Celine Lim is a Child Psychology Postdoctoral Fellow focusing on adolescent Dialectical Behavior Therapy (DBT) at Stanford School of Medicine, Department of Psychiatry and Behavioral Sciences. She earned her Doctor of Psychology (Psy.D.) in Clinical Psychology from the University of Indianapolis. Dr. Lim completed her pre-doctoral internship at the SUNY Upstate Medical University on the child and adolescent track. Her clinical experience includes a wide range settings: university counseling center, community mental health, academic medical center, private practice, inpatient psychiatric units, consultation-liaison services, and primary integrated care. She has a strong interest in providing evidence-based therapy to adolescents and families struggling with severe emotional dysregulation and complex trauma histories.
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Eric Lin
Clinical Assistant Professor (Affiliated), Psych/General Psychiatry and Psychology (Adult)
Staff, Psychiatry and Behavioral SciencesBioEric Lin, MD, is a Clinical Assistant Professor (Affiliated) of Psychiatry and Behavioral Sciences at Stanford University School of Medicine and an addiction psychiatrist at VA Palo Alto. His academic work focuses on artificial intelligence, large language models, machine learning, and psychiatry, with particular interest in the clinical evaluation, safety, and governance of AI systems used in mental health care and related psychological contexts.
Dr. Lin studies how AI systems should be assessed when they interact with patients, clinicians, or psychologically vulnerable users. His work addresses the limitations of benchmark-driven evaluation and the need for clinically meaningful approaches to AI evaluation that incorporate psychiatric expertise, real-world clinical complexity, and post-deployment risk. His broader interests include psychopathology, personality assessment, psychoanalytic and psychodynamic models of mind, and the translation of complex clinical judgment into rigorous evaluation frameworks for emerging technologies.
Dr. Lin completed psychiatry residency at Yale University, where he trained in the Neuroscience Research Training Program, and later completed a medical informatics fellowship through VA Boston, with research at Harvard Medical School/McLean Hospital on computational and digital approaches to psychiatric phenotyping. He is board certified in psychiatry and clinical informatics. His clinical and teaching work in addiction psychiatry grounds his interest in psychiatric complexity, risk assessment, care navigation, and pragmatic implementation of AI tools in health care. He is interested in collaborations across psychiatry, computer science, human-centered AI, health policy, digital mental health, and responsible technology development. -
Feng Vankee Lin
Associate Professor of Psychiatry and Behavioral Sciences (Public Mental Health & Population Sciences)
Current Research and Scholarly InterestsMy career has been devoted to understanding the neural mechanisms involved in brain aging and brain plasticity, with a special focus on early detection and prevention of Alzheimer’s disease (AD). My research approach integrates principles and findings from cognitive theory, clinical neuroscience, and computational neuroscience.
