Stanford University


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  • Gary Darmstadt

    Gary Darmstadt

    Sue Alvarez Professor of Neonatal and Developmental Medicine and Professor (Teaching), by courtesy, of Obstetrics and Gynecology

    Current Research and Scholarly InterestsI have extensive experience in the development of global health innovations and in working to test and scale-up health interventions. At Stanford University, I am playing a leading role in developing global women and children’s health research and educational programs, including the establishment of a Global Center for Gender Equality at Stanford University. My research focuses on advancing child health and development in low resource settings and advancing gender equality and health globally, and includes several applications of artificial intelligence. Before joining Stanford, I was Senior Fellow at the Bill & Melinda Gates Foundation (BMGF), where I led the development of initiatives to address gender inequalities and empower women and girls. Prior to this role, I served as the BMGF Director of Family Health, leading strategy development and implementation across maternal, newborn and child health, nutrition, and family planning. In this role, I was responsible for investments ranging from scientific discovery to intervention development and delivery of interventions at scale. I worked closely with the Discovery team to shape discovery and development investments and was a co-founder of the Saving Lives at Birth Development Grand Challenge, the Putting Women and Girls at the Center of Development Grand Challenge, and the Healthy Birth, Growth and Development initiative. Based on these experiences, I understand how to identify knowledge gaps and generate evidence of impact for new interventions, and how to utilize evidence to influence the policy dialogue leading to programmatic adoption and scale-up of interventions in low income settings. As Director of Family Health, I also co-led the development and implementation of the BMGF global health strategy for India, which cuts across multiple health and development sectors. Before joining BMGF, I was Associate Professor and Founding Director of the International Center for Advancing Neonatal Health in the Department of International Health at the Johns Hopkins Bloomberg School of Public Health. I led the development of newborn health research, including numerous facility- and community-based maternal and child health research trials. Before joining Johns Hopkins, I was Senior Research Advisor for the $50M Saving Newborn Lives program of Save the Children-US, where I led the development and implementation of the global research strategy for newborn health and survival.

  • Beth Darnall, PhD

    Beth Darnall, PhD

    Professor of Anesthesiology, Perioperative and Pain Medicine (Adult Pain) and, by courtesy, of Psychiatry and Behavioral Sciences (General Psychiatry & Psychology (Adult))

    Current Research and Scholarly InterestsThe Stanford Pain Relief Innovations Lab is dedicated to better characterizing and treating pain with patient-centered solutions. We specialize in the conduct of large-scale acute and chronic pain clinical trials that aim to (1) expand and scale access to behavioral medicine via digital and brief treatments; (2) reduce opioid risks via reduction for some and improved opioid access for others; (3) equip healthcare providers with brief behavioral medicine interventions to optimize health outcomes.

  • Halley Darrach

    Halley Darrach

    Affiliate, Department Funds
    Resident in Surgery - Plastic and Reconstructive Surgery

    BioHalley Darrach is a plastic and reconstructive surgery resident (2020-2027) at Stanford Health. She is currently completing a professional development year with ReSurge International, a nonprofit dedicated to increasing global access to reconstructive surgery through surgeon education and sustainable, local-driven initiatives.

    Dr. Darrach received her medical degree from Johns Hopkins and her bachelor's in cellular biology from California State University Northridge. While at Hopkins, she completed a dedicated research fellowship studying oncologic reconstruction outcomes under the mentorship of Dr. Justin Sacks and worked as a medical illustrator designing patient and surgeon education tools.

    Prior to residency, she spent several years conducting astrobiology research at the Jet Propulsion Laboratory and was the first hire at a biotech startup company, where she helped adapt NASA technology for medical and counterterrorism applications. Outside of the OR, she enjoys figure drawing, long-distance swimming, and travelling the world in search of new favourite cuisines.

    Dr. Darrach's research interests include gender affirming surgery, oncologic reconstruction, ethnic plastic surgery, societal perceptions of deformity, and use of medical illustration in patient and surgeon education.

  • Barnabas Daru

    Barnabas Daru

    Assistant Professor of Biology and Center Fellow, by courtesy, at the Woods Institute for the Environment

    BioBarnabas Daru is an Assistant Professor of Biology. He is interested in the ecology and biogeography of plants across ecological scales. He studied botany in Johannesburg, and was a postdoctoral researcher at Harvard, where he worked on new uses of herbarium specimens for understanding plant ecology and evolution in the Anthropocene, the epoch of profound human impact on Earth. Current research in the Daru lab addresses the role of phylogeny in: 1) understanding how species are distributed, 2) conserving unique communities, and 3) understanding changing distributions in the Anthropocene.

  • Srivatsava Daruru

    Srivatsava Daruru

    Affiliate, Program-Koyejo, O.

    BioSrivatsava Daruru is a researcher and machine learning leader whose work spans natural language processing, neuro-symbolic AI, and large-scale learning systems. He is currently Chief AI Officer at Exlens AI and was formerly Senior Manager of Machine Learning at ServiceNow, where he led research in retrieval-augmented generation (RAG), question answering, post-training optimization of large language models, and agentic workflows for conversational AI. His contributions shaped ServiceNow’s generative AI strategy, including the company’s first production-grade generative application, Genius Q&A.

    Daruru’s research interests focus on self-improving large language models, reasoning, and mathematical verification. He is currently workin on VeriBench, an end-to-end benchmark for translating Python into Lean 4, and VeriCI, a continuous verification framework for CI/CD pipelines, as part of neuro-symbolic software reliability.

    He has published at leading venues such as ACM SIGKDD and IEEE ICDM, with research spanning scalable clustering for terascale astronomy, parallel data mining, and large-scale telecom analytics. His Google Scholar profile reflects a consistent track record of contributions to data mining, NLP, and applied machine learning. In addition, he is the inventor on multiple patents in NLP, fact validation, and semi-automated data labeling.

    Daruru holds an M.S. in Computer Science from the University of Texas at Austin and a B.Tech. (Hons) in Computer Science from IIIT Hyderabad.

    About Me (Informal)
    I am a scientist and engineer working at the intersection of large language models, reasoning, and verification. My long-term vision is to build AI systems that are not only powerful but also trustworthy, capable of explaining themselves and proving their correctness. I’m especially excited about self-improving LLMs, agentic workflows, and neuro-symbolic methods that combine data-driven learning with formal verification. Currently, I’m working on VeriBench and VeriCI, projects that push AI systems toward rigorous mathematical guarantees while remaining practical for real-world development pipelines.

  • Eric Darve

    Eric Darve

    Director, Institute for Computational and Mathematical Engineering (ICME) and Professor of Mechanical Engineering

    Current Research and Scholarly InterestsThe research interests of Professor Darve span across several domains, including machine learning for science and engineering, large-language models, transformer models, surrogate and reduced order modeling, stochastic inversing, anomaly detection, numerical linear algebra, high-performance, parallel, and GPU computing.