Stanford University
Showing 681-700 of 1,482 Results
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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.
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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.
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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. -
Priyamvada(Priya) Desai
Rsch Technical Mgr 1, Technology & Digital Solutions
Current Role at StanfordManager, Biomedical Informatics R &D
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Tushar Desai
Professor of Medicine (Pulmonary, Allergy and Critical Care Medicine)
Current Research and Scholarly InterestsBasic and translational research in lung stem cell biology, cancer, pulmonary fibrosis, COPD, and acute lung injury/ARDS. Upper airway stem cell CRISPR gene correction followed by autologous stem cell transplantation to treat Cystic fibrosis. Using lung organoids and precision cut lung slice cultures of mouse and human lungs to study molecular regulation of lung stem cells. Using transgenic mice to visualize Wnt protein transmission from niche cell to stem cell in vivo.
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Gaelle Desbordes
Sponsored By Stanford University:, Radiology
BioI am a radiologic data systems engineer at Stanford Medicine Children's Health, helping develop and implement data systems for radiologists with the aim to improve diagnostic accuracy and clinical outcomes.
My previous role was as a senior research engineer at Stanford School of Medicine – Radiology, where I was applying deep learning techniques to enhance the detection and classification of various cancer types in medical images.
I was initially trained as an engineer and research scientist – with an MS in Computer Science, PhD in Cognitive and Neural Systems, and postdoctoral training in computational neuroscience and human brain imaging. More recently, I completed a Professional Certificate in Data Engineering and additional training in machine learning and AI.
Over the course of my career, I have designed, built, and coded computational methods for data analysis, collected and analyzed a range of scientific and clinical data, and effectively communicated research findings to diverse audiences. -
Catherine Descanzo
Sr. Assistant Head, Access Services (Circulation), University Libraries
BioI have oversight of the daytime and evening circulation, course reserves, and the student staffing programs in Access Services at Cecil H. Green Library. I also am currently leading the Circulation Subgroup as part of Stanford Libraries' migration to the new open source integrated library system called FOLIO.
