Stanford University
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Seunggu Jude Han, MD
Clinical Associate Professor, Neurosurgery
BioDr. Han is a board-certified neurosurgeon with fellowship training in neuro-oncology. He is also a clinical associate professor in the Department of Neurosurgery at Stanford University School of Medicine and chief of neurosurgery at Palo Alto VA Medical Center.
Dr. Han diagnoses and treats a wide range of conditions, including brain tumors, pituitary tumors, spinal tumors, and degenerative spinal disorders. He is passionate about caring for underserved populations, as well as educating and mentoring the next generation of neurosurgeons.
Dr. Han’s academic and research interests include brain mapping, advancing diagnostic methods and treatments for brain tumors, and improving the quality of neurosurgical care. He has conducted several clinical trials to determine the safety and effectiveness of specific treatments for different tumors affecting the central nervous system.
Dr. Han has published over 100 peer-reviewed articles in prestigious journals, including Neurology, Neurosurgery, Neuro-Oncology, and the Journal of Neurosurgery. He also serves as a reviewer for many professional publications.
Dr. Han is a member of the American Association of Neurological Surgeons, the Congress of Neurological Surgeons, and the Society for Neuro-Oncology. He serves as an executive committee member and abstract reviewer for annual conferences in several of these organizations. -
Summer Han
Associate Professor (Research) of Neurosurgery, of Medicine (Biomedical Informatics) and, by courtesy, of Epidemiology and Population Health
Current Research and Scholarly InterestsMy current research focuses on understanding the genetic and environmental etiology of complex disease and developing and evaluating efficient screening strategies based on etiological understanding. The areas of my research interests include statistical genetics, molecular epidemiology, cancer screening, health policy modeling, and risk prediction modeling. I have developed various statistical methods to analyze high-dimensional data to identify genetic and environmental risk factors and their interactions for complex disease.
