Stanford University
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Gaurav Singh
Clinical Assistant Professor (Affiliated), Medicine - Med/Pulmonary, Allergy & Critical Care Medicine
Staff, Medicine - Med/Pulmonary, Allergy & Critical Care MedicineBioDr. Gaurav Singh is a Staff Physician in the Pulmonary, Critical Care, and Sleep Medicine Section at VA Palo Alto Health Care System, where he serves as the pulmonary/critical lead for the virtual integrated services network (VISN). He is also an affiliated Clinical Assistant Professor of the Division of Pulmonary, Allergy, and Critical Care Medicine at Stanford University. He completed his undergraduate studies in molecular and cellular biology at UC Berkeley, where he also completed a Master of Public Health (MPH). He received his medical degree from UC San Francisco. He completed residency training in internal medicine, followed by pulmonary and critical care fellowship as well as sleep medicine fellowship all at Stanford University. Dr. Singh chaired the annual California Thoracic Society (CTS) conference for three years, and he is currently serving on the executive committee. His clinical, research, and academic interests include chronic obstructive airways disease (COPD), chronic respiratory failure, and non-invasive ventilation.
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Harshit Singh
Research Assistant, Woods Research Natural Capital Project
Staff, Woods Research Natural Capital ProjectBioHarshit Singh is an AI Researcher and Engineer working across generative AI, agentic systems, and environmental modeling. He is currently working on the Natural Capital Project at Stanford, where he develops LLM-driven workflows for the InVEST ecosystem to enhance automation, data integration, and sustainable development research. He is also building HarshanAI, an emotionally intelligent voice-AI companion.
Previously, he worked at Amazon Web Services, contributing to Bedrock Flows and AgentCore for large-scale generative AI systems and at the MIT-IBM Watson AI Lab, leading DiffuseKronA as first author and advancing parameter-efficient methods for personalized diffusion models. He has also supported climate and energy research at the Center for Global Sustainability, University of Maryland through the development of G-MAST, a global methane abatement solutions database. His work emphasizes practical innovation, scalable AI systems, and applying machine learning to real-world societal and sustainability challenges.
