Stanford University
Showing 11-20 of 38 Results
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Abhi Jain
Clinical Assistant Professor, Radiology
BioDr. Jain is a neuroradiologist and a Certified Imaging Informatics Professional (CIIP) whose academic work bridges day-to-day neuroradiology practice with imaging informatics and clinically grounded artificial intelligence (AI).
His clinical research interests include quantitative imaging and radiomics in cerebrovascular disease, with particular emphasis on intracerebral hemorrhage (ICH), and imaging biomarkers in the aging brain and neurodegeneration, including limbic-predominant age-related TDP-43 encephalopathy (LATE).
His AI/informatics and quality-improvement interests include large language models (LLMs) for radiology reporting support and clinical decision support, with an emphasis on real-world evaluation and workflow integration.
His education interests focus on modern, technology-enabled neuroradiology teaching, including tailored language models and extended reality (XR; augmented/virtual/mixed reality) approaches to strengthen trainee learning. -
Siddhartha Jaiswal
Associate Professor of Pathology
Current Research and Scholarly InterestsWe identified a common disorder of aging called clonal hematopoiesis of indeterminate potential (CHIP). CHIP occurs due to certain somatic mutations in blood stem cells and represents a precursor state for blood cancer, but is also associated with increased risk of cardiovascular disease and death. We hope to understand more about the biology and clinical implications of CHIP using human and model system studies.
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Doug James
LeRa Professor and Professor, by courtesy, of Music
Current Research and Scholarly InterestsComputer graphics & animation, physics-based sound synthesis, computational physics, haptics, reduced-order modeling
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Michelle L. James
Associate Professor of Radiology (Molecular Imaging Program at Stanford) and of Neurology and Neurological Sciences (Neurology Research)
Current Research and Scholarly InterestsThe primary aim of my lab is to improve the diagnosis and treatment of brain diseases by developing translational molecular imaging agents for visualizing neuroimmune interactions underlying conditions such as Alzheimer’s disease, multiple sclerosis, and stroke.
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Ted Jardetzky
Professor of Structural Biology
Current Research and Scholarly InterestsThe Jardetzky laboratory is studying the structures and mechanisms of macromolecular complexes important in viral pathogenesis, allergic hypersensitivities and the regulation of cellular growth and differentiation, with an interest in uncovering novel conceptual approaches to intervening in disease processes. Ongoing research projects include studies of paramyxovirus and herpesvirus entry mechanisms, IgE-receptor structure and function and TGF-beta ligand signaling pathways.
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Daniel Jarosz
Senior Associate Dean, Basic Science, Professor of Chemical and Systems Biology and of Developmental Biology
Current Research and Scholarly InterestsMy laboratory studies conformational switches in evolution, disease, and development. We focus on how molecular chaperones, proteins that help other biomolecules to fold, affect the phenotypic output of genetic variation. To do so we combine classical biochemistry and genetics with systems-level approaches. Ultimately we seek to understand how homeostatic mechanisms influence the acquisition of biological novelty and identify means of manipulating them for therapeutic and biosynthetic benefit.
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Alireza Javadian Sabet
Affiliate, Stanford Digital Economy Lab (S-DEL)
BioAlireza Javadian Sabet is a Postdoctoral Scholar at the University of Chicago Knowledge Lab and a Digital Fellow at Stanford Digital Economy Lab. He earned a PhD in Information Science from the Resilient Economy Lab at the University of Pittsburgh, where his research focused on mapping career adaptability and understanding how skills and experience translate into changing sets of opportunities over time. He also holds a master’s degree in Computer Science and Engineering from Politecnico di Milano (PoliMi) and previously served as a research fellow at the Data Science Lab and the DEpendable Evolvable Pervasive Software Engineering group. His work has been discussed in policy and business outlets, including The Economist and the American Enterprise Institute.
Alireza studies how transformative AI reshapes labor markets and innovation systems, developing models and measures from large-scale datasets that link technological capabilities to changes in skills, mobility, and knowledge production. His work combines text and trajectory data to track skill formation in education, quantify how career opportunities expand or concentrate over time, and connect these dynamics to the movement of talent across organizations and borders. He is motivated by the broader challenge of assessing and predicting technology outcomes, including how advances diffuse through tasks and institutions, and how choices around funding, training, and governance influence who benefits from technological change.
