School of Medicine
Showing 1-20 of 20 Results
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Alison Callahan
Research Engineer, Med/BMIR
BioAlison Callahan is an Instructor in the Center for Biomedical Informatics and Clinical Data Scientist in the Stanford Health Care Data Science team led by Nigam Shah. Her current research uses informatics to expand and improve the data available about pregnancy and birth, and to develop and maintain and EHR-derived obstetric database. She is also the co-leader of the OHDSI Perinatal & Reproductive Health (PRHeG) working group. Her work in the SHC Data Science team focuses on developing and implementing methods to assess and identify high value applications of machine learning in healthcare settings.
Alison completed her PhD in the Department of Biology at Carleton University in Ottawa, Canada. Her doctoral research focused on developing HyQue, a framework for representing and evaluating scientific hypotheses, and applying this framework to discover genes related to aging. She was also a developer for Bio2RDF, an open-source project to build and provide the largest network of Linked Data for the life sciences. Her postdoctoral work at Stanford applied methodologies developed during her PhD to study spinal cord injury in model organisms and humans in a collaboration with scientists at the University of Miami. -
Matthew A. Eisenberg
Clinical Assistant Professor (Affiliated), Med/BMIR
BioDr. Matthew A. Eisenberg joined Stanford Health Care in early 2013 and is the Medical Informatics Director for Analytics & Innovation with a focus on interoperability and health information exchange, regulatory reporting, health care analytics, patient reported outcomes and other uses of technology to meet our strategic initiatives.
Dr. Eisenberg is board certified in Pediatrics and Clinical Informatics. He is a Clinical Assistant Professor (Affiliated) in the Stanford Center for Biomedical Informatics Research at the Stanford University School of Medicine and he serves as the Stanford Health Care site director for the Stanford Clinical Informatics Fellowship Program. He previously held the position of Clinical Assistant Professor in Pediatrics at the University of Washington School of Medicine. He is a current member of the eHealth Exchange Coordinating Committee, a Sequoia Project Board member and serves as the current chair of the Epic Care Everywhere Network Governing Council. He is a member of the Carequality Advisory Council (past co-chair) and a member of IHE USA Implementation Committee. He is a Fellow of the American Academy of Pediatrics and a member of the American Medical Informatics Association and their Clinical Informatics Community. -
Jason Fries
Research Engineer, Med/BMIR
Current Role at StanfordI'm currently working as a staff research scientist in the Shah Lab and research scientist at Snorkel AI. My interests fall in the intersection of computer science and medical informatics. My research interests include:
• Foundation models and generative AI for healthcare
• Data-centric AI, focusing on training data curation, data generation, and quality assessment
• Learning with limited labeled data (e.g., weak supervision, zero/few-shot learning)
• Human-in-the-loop machine learning systems -
Josef Hardi
Software Dvlpr 3, Med/BMIR
BioI'm a software engineer with a keen interest in data science. I have over 10 years’ experience in software development and 5 years in the data processing. Currently, I work as a backend developer for the Stanford Center of Biomedical Informatics Research; tackling issues in data and metadata management and interoperability. I also actively engage in the work of converting health and claim records to the OMOP common data model as part of my collaboration with the Stanford Population Health Sciences. I have experience with Java, Python, R, RDF, OWL, OBDA, Schema.org and Elasticsearch.
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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.
