School of Medicine
Showing 21-24 of 24 Results
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Walter Sujansky
Adjunct Professor, Department of Medicine, Center for Biomedical Informatics Research
BioWalter Sujansky, MD PhD is an Adjunct Professor of Biomedical Informatics at the Stanford Center for Biomedical Informatics Research in the Stanford Department of Medicine. Dr. Sujansky co-teaches BMI-210 Modeling Biomedical Systems, where he lectures on a variety of topics, including deep neural networks, probabilistic reasoning, electronic health records, and health data integration and interoperability. He also advises students in the Biomedical Data Science Graduate Program, an interdisciplinary graduate and postdoctoral training program that is part of the Department of Biomedical Data Science. His research interests include the modeling of biomedical concepts based on formal logic and the engineering of features for biomedical machine learning algorithms.
Dr. Sujansky earned an M.D. and a Ph.D. in Medical Informatics from Stanford University, where his doctoral research addressed heterogeneous database integration and clinical decision support. He also earned a B.A. in Economics from Harvard University.
Dr. Sujansky is also the managing consultant at Sujansky & Associates, LLC, a consulting firm that specializes in the representation, management, and analysis of clinical data in information systems. In this capacity, his work focuses on the modeling of complex biomedical data related to patient phenotyping, clinical genomics, quality measurement, automated decision support, and machine learning. His firm has helped to develop shared computing resources such as the California Joint Replacement Registry and the Laboratory Interoperability Data Repository. The firm's clients include the federal and state governments, non-profit organizations, health information system developers, and drug/device manufacturers. Dr. Sujansky also provides forensic analysis of health information technologies for medical malpractice and intellectual property litigation. -
Michael Wornow
Research Asst - Graduate, Med/BMIR
BioMichael is a computer science PhD student focused on developing and operationalizing large-scale pretrained models ("foundation models") in healthcare. He is advised by Nigam Shah and Chris Re and is supported by an NSF Graduate Research Fellowship.
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Xianghao Zhan
Postdoc Res Affiliate, Med/BMIR
BioXianghao Zhan earned his Ph.D. in Bioengineering from Stanford University in 2024, with a minor in Biomedical Data Science. He also completed dual M.S. degrees in Bioengineering (2021) and Statistics (2023) at Stanford, and holds undergraduate degrees in Control Science and Engineering and in English Literature from Zhejiang University’s Chu Kochen Honors College, where he graduated summa cum laude in 2019.
His research centers on understanding and modeling brain injury and neurodegeneration through data-driven approaches grounded in biomechanics, medical imaging, and clinical evidence. Under the mentorship of Prof. David B. Camarillo and Prof. Olivier Gevaert, his doctoral work advanced the computational modeling of traumatic brain injury, including the development of more accurate brain strain estimators, interpretable kinematic-to-strain models, and the first large-animal biomechanics-to-pathology correlation study.
Beyond traumatic brain injury, his research portfolio spans clinical data analysis for neurodegenerative diseases such as ALS, pathology-informed modeling of blood-brain barrier disruption, survival prediction using patient-derived motor neurons, and imaging-informed diagnosis in cancer. He has also contributed to clinical text mining and sensor-based health monitoring in contexts such as COVID-19 prognosis, surface electromyography, and artificial olfaction.
Xianghao has published 22 peer-reviewed papers as first or co-first author in journals including NPJ Digital Medicine, IEEE JBHI, and IEEE T-BME, with four additional first-author submissions under review. He has served as a reviewer for over 10 scientific journals, including Annals of Biomedical Engineering and Journal of Neurotrauma, and presented his work in 14 international conferences. He has co-written five research grants, contributing to over $400,000 in funding for brain injury studies.
His contributions have been recognized with several competitive honors, including the Siebel Scholars Class of 2024, the IET William James Award, the IET Postgraduate Research Award, the Stanford Interdisciplinary Graduate Fellowship, and trainee awards from AMIA and the American Society for Neurotrauma.
Outside of research, he is an avid volleyball and tennis player, having led teams to 16 intramural championships at Stanford. He values collaboration, leadership, and the joy of teamwork—on and off the court.
