Stanford University
Showing 81-100 of 166 Results
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Ruotong Liao
Affiliate, Biomedical Data Science
BioVisiting Scholar with Prof. Serena Yeung-Levy at Stanford AI Lab.
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Matthew Lungren
Adjunct Professor, Biomedical Data Science
BioDr. Matthew Lungren is a physician-scientist whose research develops and evaluates machine learning systems that combine medical imaging, electronic health record data, and clinical outcomes. His current work concerns medical foundation models, agentic clinical systems, and the prospective evaluation of AI in real clinical workflows. He joined the Stanford faculty in 2014 in the Department of Radiology, serving as Assistant Professor and then Associate Professor through 2021 while leading a dedicated pediatric interventional radiology service. He co-founded and co-directed the Stanford Center for Artificial Intelligence in Medicine and Imaging. He remains Adjunct Professor of Biomedical Data Science at Stanford, where he co-teaches Generative AI and Medicine, and holds a part-time clinical appointment at UCSF. He serves as an independent board director and scientific advisor to medical technology, health system, and life science organizations. In industry, Dr. Lungren served as Chief Scientific Officer for Health and Life Sciences and as AI Technical Advisor in the Office of the CTO at Microsoft.
Dr. Lungren is also a top rated instructor leading AI in Healthcare courses designed especially for learners with non-technical backgrounds:
Stanford/Coursera: https://www.coursera.org/learn/fundamental-machine-learning-healthcare
LinkedIn Learning: https://www.linkedin.com/learning/an-introduction-to-how-generative-ai-will-transform-healthcare -
Daniel Mas Montserrat
Affiliate, Biomedical Data Science
BioDaniel Mas Montserrat holds a PhD in Electrical and Computer Engineering from Purdue University. Previously he graduated summa cum laude from the Polytechnic University of Catalonia in Audiovisual Systems in Telecommunications Engineering. Currently, he is a research fellow at the Stanford School of Medicine (Department of Biomedical Data Science). His research focuses on applying computational methods to problems in population genetics and biomedicine.
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Liam Edward Mulhall
Software Developer, Biomedical Data Science
Current Role at StanfordLiam develops and maintains the HLA Curation Interface, a tool that supports the assessment of HLA alleles and haplotypes for use in precision medicine and research. He also works on internal tools used by the Stanford ClinGen team.
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Fateme (Fatima) Nateghi
Postdoctoral Scholar, Biomedical Informatics
BioAs a postdoc researcher at the Division of Computational Medicine, I find myself at the exciting intersection of machine learning and healthcare. My journey began with a PhD in Biomedical Sciences from KU Leuven in Belgium, where I explored the complexities of machine learning algorithms and their transformative potential in clinical settings. My research focused on adapting these algorithms for time-to-event data, a method used to predict when specific events may occur in a patient’s future.
At Stanford, my work centers on building trustworthy AI systems to enhance healthcare delivery. I develop and evaluate machine learning models that integrate structured electronic health records (EHRs) and unstructured clinical notes to support real-world clinical decision-making. My recent projects include predicting treatment retention in opioid use disorder, improving antibiotic stewardship for urinary tract infections, and enabling digital consultations through large language models (LLMs). I'm particularly interested in embedding-based retrieval and retrieval-augmented generation (RAG) methods that help bridge cutting-edge AI research with clinical practice.
My role involves not just advancing the integration of machine learning in healthcare but also collaborating with a diverse team of clinicians, data scientists, and engineers. Together, we're striving to unravel complex healthcare challenges and ultimately improve patient outcomes.
