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Kaniksha Desai

Clinical Professor, Medicine - Endocrinology, Gerontology, & Metabolism

BioDr. Kaniksha Desai is a board-certified endocrinologist and clinical professor at Stanford University. She completed her endocrinology fellowship at the Mayo Clinic, with an emphasis on the management of patients with thyroid cancer. Dr. Desai’s clinical practice focuses on the management of patients with thyroid nodules and thyroid cancer. She also maintains board certification in neck ultrasonography.

Kavin Desai

Adjunct Clinical Associate Professor [Lpch], Pediatrics - Cardiology

Keval Niraj Desai

Clinical Assistant Professor, Medicine

Manisha Desai (She/Her/Hers)

Kim and Ping Li Professor, Professor (Research) of Medicine (Computational Medicine - QSU), of Biomedical Data Science and, by courtesy, of Epidemiology and Population Health

Current Research and Scholarly InterestsDr. Desai is the Director of the Quantitative Sciences Unit. She is interested in the application of biostatistical methods to all areas of medicine including oncology, nephrology, and endocrinology. She works on methods for the analysis of epidemiologic studies, clinical trials, and studies with missing observations.

Naomi Amish Desai

Resident in Pediatrics

Nimit Desai

Resident in Emergency Medicine

BioNimit Desai is an emergency medicine resident physician caring for patients at Stanford Hospital, Kaiser Permanente Santa Clara, and Santa Clara Valley Medical Center.

Before medicine, Nimit earned a B.S. in Computer Science from Stanford and worked as a product manager at Doctor On Demand (now Included Health), leading a team engineers that built the in-house electronic health record used by more than 1,000 clinicians across 300,000+ annual telemedicine visits. Nimit also co-founded Streamio, a browser extension that overlays real-time advanced statistics onto live NBA game streams.

While earning an MD at the UC San Diego School of Medicine, Nimit served as a Clinical Strategist at Pearl Health. In that role Nimit designed value-based care programs for more than 40,000 Medicare patients across 100+ primary care practices, including a comprehensive dementia care program, machine-learning prediction of preventable emergency department visits, and palliative care and advance care planning support for patients at risk of decline. As an informatics research fellow at UCSD's Altman Clinical and Translational Research Institute, Nimit studied artificial intelligence, health misinformation, and digital public health, with work published in JAMA, JAMA Internal Medicine, JAMA Network Open, and the Journal of Medical Internet Research.

Nimit's current work focuses on AI-enabled clinical care delivery models, services that help practices succeed in value-based care, and productivity tools that give residents more time for patient care and learning. Nimit is also interested in reinforcement learning for medicine, specifically how to enable and rigorously evaluate clinical superintelligence so that frontier AI systems are safe, reliable, and grounded in real-world clinical practice.