Vice Provost and Dean of Research


Showing 481-490 of 1,154 Results

  • Andrew D. Huberman

    Andrew D. Huberman

    Associate Professor of Neurobiology and, by courtesy, of Psychiatry and Behavioral Sciences

    Current Research and Scholarly InterestsAndrew Huberman is a tenured associate professor of neurobiology and of ophthalmology at Stanford University School of Medicine, where he directs the Huberman Lab. After earning his B.A. from the University of California, Santa Barbara and completing M.A. and Ph.D. degrees in neuroscience at UC Berkeley and UC Davis, he conducted post-doctoral work at Stanford.

  • John Huguenard

    John Huguenard

    Professor of Neurology and Neurological Sciences (Neurology Research), of Neurosurgery (Adult Neurosurgery) and, by courtesy, of Molecular and Cellular Physiology

    Current Research and Scholarly InterestsWe are interested in the neuronal mechanisms that underlie synchronous oscillatory activity in the thalamus, cortex and the massively interconnected thalamocortical system. Such oscillations are related to cognitive processes, normal sleep activities and certain forms of epilepsy. Our approach is an analysis of the discrete components (cells, synapses, microcircuits) that make up thalamic and cortical circuits, and reconstitution of components into in silico computational networks.

  • Sohail Z Husain

    Sohail Z Husain

    Chambers-Okamura Endowed Professor of Pediatric Gastroenterology

    Current Research and Scholarly InterestsMy research delves into three broad areas of the exocrine pancreas: (1) The crucial signaling pathways that initiate and transduce pancreatitis; (2) the factors that turn on pancreatic regeneration and recovery after pancreatic injury; and (3) the mechanisms underlying drug-induced pancreatitis.

  • Ruth Huttenhain

    Ruth Huttenhain

    Assistant Professor of Molecular and Cellular Physiology

    Current Research and Scholarly InterestsMy group deciphers how G protein-coupled receptors decode extracellular cues into dynamic and context-specific cellular signaling networks to elicit diverse physiologic responses. We exploit quantitative proteomics to capture the spatiotemporal organization of signaling networks combined with functional genomics to study their impact on physiology.

  • Gloria Hwang, MD

    Gloria Hwang, MD

    Clinical Professor, Radiology

    Current Research and Scholarly InterestsInterventional oncology, pancreatic interventions, image-guided gene therapy.

  • Joo Ha Hwang, MD, PhD

    Joo Ha Hwang, MD, PhD

    Fortinet Founders School of Medicine Professor and Professor, by courtesy, of Surgery

    Current Research and Scholarly InterestsSpecialize in early detection of gastrointestinal malignancies including esophageal, gastric, pancreatic, bile duct & colon cancers. I have both a clinical & research interest in improving the early detection of gastric cancer in particular. I am the PI of the Gastric Precancerous conditions Study, a prospective study of patients with gastric intestinal metaplasia & other precancerous conditions which combines comprehensive clinical & endoscopic data with a large bio-specimen repository.

  • Gianluca Iaccarino

    Gianluca Iaccarino

    Robert Bosch Chair of the Department of Mechanical Engineering and Joseph L. and Roberta M. Rodgers Professor

    Current Research and Scholarly InterestsComputing and data for energy, health and engineering

    Challenges in energy sciences, green technology, transportation, and in general, engineering design and prototyping are routinely tackled using numerical simulations and physical testing. Computations barely feasible two decades ago on the largest available supercomputers, have now become routine using turnkey commercial software running on a laptop. Demands on the analysis of new engineering systems are becoming more complex and multidisciplinary in nature, but exascale-ready computers are on the horizon. What will be the next frontier? Can we channel this enormous power into an increased ability to simulate and, ultimately, to predict, design and control? In my opinion two roadblocks loom ahead: the development of credible models for increasingly complex multi-disciplinary engineering applications and the design of algorithms and computational strategies to cope with real-world uncertainty.
    My research objective is to pursue concerted innovations in physical modeling, numerical analysis, data fusion, probabilistic methods, optimization and scientific computing to fundamentally change our present approach to engineering simulations relevant to broad areas of fluid mechanics, transport phenomena and energy systems. The key realization is that computational engineering has largely ignored natural variability, lack of knowledge and randomness, targeting an idealized deterministic world. Embracing stochastic scientific computing and data/algorithms fusion will enable us to minimize the impact of uncertainties by designing control and optimization strategies that are robust and adaptive. This goal can only be accomplished by developing innovative computational algorithms and new, physics-based models that explicitly represent the effect of limited knowledge on the quantity of interest.

    Multidisciplinary Teaching

    I consider the classical boundaries between disciplines outdated and counterproductive in seeking innovative solutions to real-world problems. The design of wind turbines, biomedical devices, jet engines, electronic units, and almost every other engineering system requires the analysis of their flow, thermal, and structural characteristics to ensure optimal performance and safety. The continuing growth of computer power and the emergence of general-purpose engineering software has fostered the use of computational analysis as a complement to experimental testing in multiphysics settings. Virtual prototyping is a staple of modern engineering practice! I have designed a new undergraduate course as an introduction to Computational Engineering, covering theory and practice across multidisciplanary applications. The emphasis is on geometry modeling, mesh generation, solution strategy and post-processing for diverse applications. Using classical flow/thermal/structural problems, the course develops the essential concepts of Verification and Validation for engineering simulations, providing the basis for assessing the accuracy of the results.

  • Andrei Iagaru

    Andrei Iagaru

    Professor of Radiology (Nuclear Medicine)

    Current Research and Scholarly InterestsCurrent research projects include:
    1) PET/MRI and PET/CT for Early Cancer Detection
    2) Targeted Radionuclide Therapy
    3) Clinical Translation of Novel PET Radiopharmaceuticals;

  • John P.A. Ioannidis

    John P.A. Ioannidis

    Professor of Medicine (Stanford Prevention Research Center), of Epidemiology and Population Health and, by courtesy, of Biomedical Data Science

    Current Research and Scholarly InterestsMeta-research
    Evidence-based medicine
    Clinical and molecular epidemiology
    Human genome epidemiology
    Research design
    Reporting of research
    Empirical evaluation of bias in research
    Randomized trials
    Statistical methods and modeling
    Meta-analysis and large-scale evidence
    Prognosis, predictive, personalized, precision medicine and health
    Sociology of science