Stanford University
Showing 2,541-2,560 of 3,295 Results
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Gayathri Srinivasan OD, MS
Clinical Associate Professor, Ophthalmology
BioDr. Srinivasan is a Clinical Associate Professor in the Department of Ophthalmology at Stanford University. Her clinical focus is on the management of amblyopia, strabismus, childhood refractive errors, and concussion-related vision disorders in children and adults. Dr. Srinivasan's research interests are amblyopia, strabismus, and concussion-related vision disorders. She serves as co-Investigator in ongoing clinical trials through the Pediatric Eye Disease Investigator Group (PEDIG), funded by the NIH, and chairs the Pediatrics and Strabismus subgroup within the Observational Health Data Sciences and Informatics (OHDSI) network.
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Malathi Srinivasan
Clinical Professor, Medicine - Primary Care and Population Health
BioDr. Srinivasan is a Clinical Professor of Medicine at Stanford University, Associate Director at the Stanford Center for Asian Healthcare Research and Education (Stanford CARE), Director of the Stanford CARE Scholars research program, Director of the Stanford Implementation Sciences Fellowship, Fellow at the Stanford Center for Innovation in Global Health (CIGH), Board Member for the Stanford Health Professions Education and Scholars (SHaPES, formerly CTSS), and member of the Stanford Teaching and Mentoring Academy (TMA). She is co-Director of the One Health Teaching Scholars Faculty Development Program, an international program focusing on faculty development for health professions education around the world. She was a regular contributor to CBS-KPIX “Medical Mondays”. Dr. Srinivasan brings her skills as an educator, physician, health services researcher, and entrepreneur to considering how scalable technologies can improve health care. Her work in Virtual Health/telemedicine and new patient engagement models has been published in the NEJM Catalyst – a leading healthcare innovation journal.
Previously, Dr. Srinivasan was a Master Clinical Educator and Professor of Clinical Medicine at the University of California, Davis School of Medicine. She was the Senior Associate Editor and Editorial Fellowship Director for the Journal of General Internal Medicine, and was the Kimitaka Kaga Visiting Professor at the University of Tokyo at the International Research Center for Medical Education. At UC Davis, Dr. Srinivasan was the Director of Practice Based Learning and Improvement and Medical Director of the Clinical Performance Examination for a decade. She is former President of the California-Hawaii Society of General Internal Medicine, and ex-officio National Council Member for SGIM. She was a Robert Wood Johnson Foundation Generalist Physician Faculty Scholar and US Health and Human Service Public Policy Fellow. Dr. Srinivasan has been awarded the California SGIM Educator of the Year Award, Mentor of the Year (California American College of Physicians), and Faculty of the Year (Stanford CARE), and was recognized with the Dean’s Award for Excellence in Education (UC Davis). Her research has focused on two themes. First, addressing health disparities for vulnerable populations, and improving the health of Asians through research & systems change. Second, improving physician competency around clinical decision-making, through Virtual Health, technology-aided education and reflective practice.
Dr. Srinivasan has been working in the Stanford Medical Humanities & the Arts program, as Director of the Medicine, Movement & Dance program, and building patient-facing programs n Medical Humanities She serves on the Executive Board of The Pegasus Physician Writers Program, and enjoys her time as a novice creative writer. -
Suhas Srinivasan, Ph.D.
Principal Bioinformatics Scientist, Dermatology
BioI develop computational algorithms including AI/ML and statistical methods to discover insights at various resolutions of the biological hierarchy i.e., molecules, cells, tissues, organs, organism and population-scale.
In my current role in the laboratories of Paul Khavari and Howard Chang I conduct bioinformatics research to study the molecular mechanisms of tissue development, cancers, autoimmunity and chronic diseases using multiomics, with a focus on the non-coding genome.
I have ten years of academic research experience and received my Ph.D. in Data Science specializing in AI/ML development for diverse topics in biomedicine.
My research interests include artificial intelligence to identify novel patterns in multiomics data, psychometrics and neuroimaging data; structural bioinformatics and computational epidemiology. Additionally, I have conducted research in anomaly detection, and community detection in biological networks.
I am the co-inventor of a patented anomaly detection method for real-time streaming data.
Prior to graduate training and academic research, I was a full-stack software engineer in industry for three years. -
Tara Srirangarajan
Postdoctoral Scholar, Business
Current Research and Scholarly InterestsNeuroeconomics, Affective Science, Consumer neuroscience
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Ram Dyuthi Sristi
Postdoctoral Scholar, Neurobiology
BioI am a postdoctoral researcher at Stanford University working at the intersection of machine learning and systems neuroscience. My research focuses on developing interpretable models to understand how distributed neural populations coordinate to generate behavior across contexts and brain regions.
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Ankit Srivastava
Instructor, Medicine - Gastroenterology & Hepatology
Current Research and Scholarly InterestsMy research focuses on deciphering novel molecular crosstalk between epithelial and immune cells in human epithelial cancers and skin aging. My current projects highlight the targetable epithelial-immune axis in aggressive metastatic tumors with perineural invasion- cutaneous squamous cell carcinoma (cSCC) and head and neck squamous cell carcinoma (HNSC). To accomplish this, I imply single-cell transcriptomics and spatial RNA detection methods- multiplex and hiplex RNAscope along with our newly developed novel tumor nerve invasion model. Additionally, I study the regulome of human skin aging (chronological and photo-aging) by investigating the multiome data to recognize molecular underpinnings of aging.
