School of Medicine
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Robin Sugiura
Director of Postdoctoral Training, Office of Postdoctoral Affairs
Current Role at StanfordDirector of Postdoctoral Training, Office of Postdoctoral Affairs
Director, Stanford PRISM -
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. -
Han Sun
Postdoctoral Scholar, Genetics
Biostatistician 2, Pediatrics - EndocrinologyBioHan had been a postdoc with Dr. Steinmetz at the genetics department for five years, working on both cancers and heart diseases, trying to understand the mechanisms linking from variants to disease phenotypes. This led to a few very interesting findings of aberrant splicing regulation, such as splicing-mediated readthrough stabilization (SRS), one more mechanism for oncogene activation in multiple types of cancers, and tissue-specific splicing of a mitochondrial inner membrane protein, suggesting a molecular connection between deficiency in energy-supplying and dilated cardiomyopathy.
After being a senior computational biologist with Dr. Gloyn, who has been dedicated to the research of type 2 diabetes for decades, Han switched to the field of this multifactorial metabolic disease. It did take some courage to make such a switch at his post-postdoc stage, however, Han has a consistent interest in studying PG&E, which is not pacific gas and electric nearby, but the interaction between phenotype, genotype, and environment. With years of hands-on experience in statistical modeling and the analysis of next-generation sequencing and mass spectrometry data, in addition to a good understanding of disease genetics, cancer biology, and systems biology, Han is highly confident that he will enjoy the adventure and contribute to our understanding of diabetes. -
Ruopeng (Robin) Sun
Physical Science Research Scientist, Orthopaedic Surgery
BioDr. Sun is the research scientist at the Wearable Health Lab. He received his Ph.D. in Human Performance from Indiana University, MS in mechanical engineering from Stony Brook University. His research focused on using novel technology to study human movement as a function of aging, promote functional independence and enhance quality of life. He is particularly interested in investigating balance/locomotion control and risk of falling among ambulatory populations and translating novel research findings and technology into clinic/community-based settings to enhance healthy independent aging. His recent work utilized machine learning and augmented reality tools to enhance precise and efficient functional mobility assessment.
