Stanford University
Showing 11-20 of 20 Results
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Justin Norden, MD, MBA, MPhil
Adjunct Professor, Med/BMIR
BioDr. Justin Norden is an Adjunct Professor at Stanford Medicine in the Department of Biomedical Informatics Research. He teaches courses on digital health and AI in Medicine. His research focuses on AI in healthcare, digital health, and care system transformation.
Additionally, Dr. Norden is a Partner at GSR Ventures where he focuses on early-stage investments in digital health and AI/ML in healthcare. Prior to GSR Ventures, Dr. Norden was founder and CEO of Trustworthy AI which was acquired by Waymo (Google Self-Driving). He worked on the healthcare team at Apple, co-founded Indicator (an NLP based platform for biopharma decision making), and helped start the Stanford Center for Digital Health.
Dr. Norden received an MD from Stanford University School of Medicine, where he served as student body president. An MBA from the Stanford Graduate School of Business, where he served as president of the healthcare club. An M.Phil in Computational Biology with distinction from the University of Cambridge, and a BA in Computer Science with distinction from Carleton College.
Finally, he is a professional athlete for the Oakland Spiders (ultimate frisbee) - holding the team all-time records for assists and completions. He is a 3x World Champion, 1x professional champion, former Team USA Captain (U24), and D1 University National Champion. -
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.
