School of Medicine
Showing 11-19 of 19 Results
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Stefan Thottunkal
Other Tech - Graduate, Med/Quantitative Sciences Unit
Graduate Student Employee, Medicine - Primary Care and Population HealthBioStefan Thottunkal is a physician in training, Stanford researcher, and policymaker whose work sits at the intersection of artificial intelligence, precision medicine, translational science, and public health innovation. He completed the M.S. in Community Health and Prevention Research at Stanford University as an IIE Quad Fellow, one of the world’s most selective international research fellowships, where his thesis centered on computational pharmacogenomics and the use of data-driven LLM methods to advance precision prescribing.
His research focuses on translating innovation into clinically meaningful and implementation-ready health solutions, with particular interests in pharmacogenomics, chronic disease, and AI-enabled decision support. He is especially interested in how machine learning and large language models can be used not simply as technical advances, but as robust clinical tools that improve prescribing, strengthen care delivery, and incorporate human centered design principles to effectively integrate precision medicine in routine clinical practice.
At Stanford, he contributes to the Han Lab’s research on advancing precision oncology in advanced non-small cell lung cancer, while helping lead NOURISH, a pioneering Stanford Medicine initiative reimagining cardiometabolic care through culturally tailored nutrition science, behavioral insight, and digital innovation. NOURISH advances a model of lifestyle medicine that preserves cultural relevance while applying rigorous scientific methods to improve metabolic health. By integrating culinary medicine with emerging technologies, the initiative is exploring how AI-enabled tools, personalized digital education, and interactive nutrition support systems can make evidence-based dietary guidance more adaptive, engaging, and scalable across diverse populations. His work in this space reflects a broader interest in how technology can help transform nutrition care from generic advice into a more personalized, culturally tailored, and behaviorally attuned form of preventive medicine.
In parallel with his research career, Stefan brings close to half a decade of experience advising the Australian Federal Government on major health and social policy initiatives. His international experience also includes mentoring hackathon teams in India and medical device development in Nigeria, where he contributed to dialysis device innovation and clinical trials design in resource-constrained settings. Together, these experiences reflect his broader commitment to advancing equitable, evidence-based, and culturally tailored global health innovation. -
Rebecca Lauren Tisdale
Assistant Professor of Medicine (PCPH)
BioBecca Tisdale, MD, MPA is an internist, obesity medicine specialist, and health services researcher with interests in cardiovascular disease, global health, and health systems. As a VA Health Services Research & Development fellow (2020-2023) and Investigator in the VA Center for Innovation to Implementation (Ci2i) and Stanford Cardiovascular Outcomes, Policy, & Implementation Research Group (COPIR), her work has focused on value, access, and equity in cardiovascular disease care and the role of virtual care in achieving these goals. She additionally serves as Medical Director of the Evaluation Sciences Unit (ESU) with the Division of Primary Care and Population Health.
Previously, she received a BA with distinction in Human Biology from Stanford in 2009, followed by a master of public administration (MPA) joint degree from Sciences Po, Paris and the London School of Economics. She then matriculated at Columbia University College of Physicians and Surgeons for medical school, where she was active in global health activities, researching multidisciplinary teams in HIV care in Ethiopia and serving on the board of the student international health organization. As a global health track resident at Stanford, Becca spent time working in Rwanda through the Johnson and Johnson program and participated in the inaugural Women Leaders in Global Health conferences at Stanford and in London. In 2019-2020, she comprised one third of Stanford’s first all-woman internal medicine chief resident cohort. Outside of work, she enjoys all things French as well as running, both in races and after her young children. -
Cynthia Tsai, MD, FACP
Clinical Assistant Professor, Medicine - Primary Care and Population Health
BioDr. Cynthia Tsai, MD, FACP, is a board certified internal medicine physician and Clinical Assistant Professor in the Department of Medicine at Stanford within the Division of Primary Care and Population Health. She is the Medical Director of Stanford Primary Care in Los Altos and is also the Los Altos Clinic Site Director for the Stanford Internal Medicine Residency.
Within the Division of Primary Care and Population Health, she serves as the Division Lead for Quality and Equity, and she has spearheaded work to improve the equitable care of patients from racial and ethnic minority groups and limited English proficiency patients with chronic diseases such as hypertension and diabetes.
She completed medical school at the University of California, San Francisco, School of Medicine, and she completed residency training in internal medicine and primary care in the UCSF Primary Care/General Internal Medicine (UCPC-GIM) track of the Internal Medicine residency program. A Bay Area native, she is eager to provide primary care for a complex patient panel here in the Bay Area. Her clinical interests include preventative healthcare, the care of older adults, addiction medicine, and behavioral medicine. She grew up in a bicultural and bilingual home and is fluent in Mandarin Chinese, and she provides language concordant care to Mandarin speaking patients.
Outside of patient care, she has interests in ambulatory medical education, health equity, and the cultivation of early trainee interest in primary care. She also has strong interest in the medical humanities and narrative medicine, and has published personal perspective pieces in publications such as JAMA and the San Francisco Chronicle. -
Timothy Tsai
Clinical Assistant Professor, Medicine - Primary Care and Population Health
BioDr. Tsai is a board-certified family medicine physician, clinical informaticist, and trained in osteopathy. He is a clinical assistant professor in the Stanford University School of Medicine Department of Medicine – Primary Care and Population Health. Prior to joining Stanford Health Care, he obtained a Master of Management in clinical informatics from Duke University.
Dr. Tsai seeks to improve clinician workflows and patient care by applying his knowledge of clinical informatics. His innovations allow providers to quickly access, share, and document information to advance patient care. He has also held many notable leadership, educational, and quality control positions throughout his career.
Dr. Tsai investigates ways to maximize the time clinicians spend with patients. He expedites and standardizes communication between health care providers and patients through the integration of mobile devices and remote patient monitoring programs. He streamlines the documentation process by updating electronic medical record tools and creating more efficient patient questionnaires to optimize the quality of care.
He has presented his research orally or in poster format at the American Medical Informatics Association, Family Medicine Education Consortium, and American Association of Neuromuscular and Electrodiagnostic Medicine. As a medical student, Dr. Tsai developed an open online osteopathic manipulation course, enrolling over 1,200 students. As a clinical fellow at Duke, he co-authored a textbook chapter on the future of health informatics -
Geoffrey Tso
Clinical Assistant Professor, Medicine - Primary Care and Population Health
Current Research and Scholarly InterestsClinical Informatics, Generative AI, LLM, Clinical Decision Support, Digital Health, Multimorbidity, Preventive Health, Telemedicine, Telehealth, Machine Learning, Artificial Intelligence
