Vice Provost and Dean of Research


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  • Christian Linder

    Christian Linder

    Professor of Civil and Environmental Engineering

    BioChristian Linder is a Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering. Through the development of novel and efficient in-house computational methods based on a sound mathematical foundation, the research goal of the Computational Mechanics of Materials (CM2) Lab at Stanford University, led by Dr. Linder, is to understand micromechanically originated multi-scale and multi-physics mechanisms in solid materials undergoing large deformations and fracture. Applications include sustainable energy storage materials, flexible electronics, and granular materials.

    Dr. Linder received his Ph.D. in Civil and Environmental Engineering from UC Berkeley, an MA in Mathematics from UC Berkeley, an M.Sc. in Computational Mechanics from the University of Stuttgart, and a Dipl.-Ing. degree in Civil Engineering from TU Graz. Before joining Stanford in 2013 he was a Junior-Professor of Micromechanics of Materials at the Applied Mechanics Institute of Stuttgart University where he also obtained his Habilitation in Mechanics. Notable honors include a Fulbright scholarship, the 2013 Richard-von-Mises Prize, the 2016 ICCM International Computational Method Young Investigator Award, the 2016 NSF CAREER Award, and the 2019 Presidential Early Career Award for Scientists and Engineers (PECASE).

  • Scott W Linderman

    Scott W Linderman

    Assistant Professor of Statistics

    BioScott Linderman, PhD, is an Assistant Professor at Stanford University in the Statistics Department and the Wu Tsai Neurosciences Institute, as well as the Co-Director of the Stanford Center for Neural Data Science. His research focuses on machine learning, computational neuroscience, and the general question of how computational and statistical methods can help to decipher neural computation. His work combines novel methodological development in the areas of state space models, deep generative models, point processes, and approximate Bayesian inference with applied statistical analyses of large-scale neural and behavioral data. Previously, he was a postdoctoral fellow at Columbia University and a graduate student at Harvard University. His work has been recognized with a Savage Award from the International Society for Bayesian Analysis, an AISTATS Best Paper Award, an NSF CAREER Award, and fellowships from the McKnight, Sloan, and Simons Foundations.

  • Malene Lindholm

    Malene Lindholm

    Sr. Research Engineer, Medicine - Med/Cardiovascular Medicine

    Current Research and Scholarly InterestsInterested in the genetics of human performance and the multi-omic response to exercise and training for optimizing human health.

  • Bruce Ling

    Bruce Ling

    Senior Research Scientist, Pediatrics - Neonatology

    Current Research and Scholarly InterestsA significant focus of my career is the use of AI to decode real-world datasets of electronic health records, high-resolution LCMS-based liquid/tissue biopsy proteomics/metabolomics, and multiple modality medical imaging.

  • Joseph (Joe) Lipsick

    Joseph (Joe) Lipsick

    Professor of Pathology and of Genetics

    Current Research and Scholarly InterestsFunction and evolution of the Myb oncogene family; function and evolution of E2F transcriptional regulators and RB tumor suppressors; epigenetic regulation of chromatin and chromosomes; cancer genetics.

  • Marc Lipsitch

    Marc Lipsitch

    Michael and Barbara Berberian Professor, Professor of Biology and Senior Fellow at the Freeman Spogli Institute for International Studies

    BioMarc Lipsitch started his appointments at Stanford on January 1, 2026. From 1999-2025 he was a faculty member at Harvard TH Chan Schooll of Public Health, where he was Professor of Epidemiology (20062025) and founding Director of the Center for Communicable Disease Dynamics (2009-2025).

  • Fang Liu

    Fang Liu

    Assistant Professor of Chemistry

    Current Research and Scholarly InterestsThe group will develop scalable and controllable processes to produce low dimensional materials and their artificial structures, and unravel their novel static and dynamical properties of broad interest to future photonic, electronic and energy technologies. The topics will include: a) Unraveling time-resolved dynamics in light-induced electronic response of two dimensional (2D) materials artificial structures. b) Fabrication of 1D atomically thin nanoribbon arrays and characterization of the electronic and magnetic properties for the prominent edge states. c) Lightwave manipulation with 2D superlattices. These research projects will provide participating students with broad interdisciplinary training across physics, chemistry, and materials science.

  • Jonathan T.C. Liu

    Jonathan T.C. Liu

    Professor of Pathology and Professor, by courtesy, of Bioengineering

    Current Research and Scholarly InterestsBiomedical optics
    In vivo microscopy
    Slide-free pathology
    Three-dimensional microscopy
    3D pathology
    Optical biopsy
    Image-guided surgery
    Early detection
    Artificial intelligence
    Machine learning
    Deep learning
    Computational analysis
    Computational pathology
    Virtual staining
    Molecular imaging

  • C. Karen Liu

    C. Karen Liu

    Professor of Computer Science

    BioC. Karen Liu is a professor in the Computer Science Department at Stanford University. Prior to joining Stanford, Liu was a faculty member at the School of Interactive Computing at Georgia Tech. She received her Ph.D. degree in Computer Science from the University of Washington. Liu's research interests are in computer graphics and robotics, including physics-based animation, character animation, optimal control, reinforcement learning, and computational biomechanics. She developed computational approaches to modeling realistic and natural human movements, learning complex control policies for humanoids and assistive robots, and advancing fundamental numerical simulation and optimal control algorithms. The algorithms and software developed in her lab have fostered interdisciplinary collaboration with researchers in robotics, computer graphics, mechanical engineering, biomechanics, neuroscience, and biology. Liu received a National Science Foundation CAREER Award, an Alfred P. Sloan Fellowship, and was named Young Innovators Under 35 by Technology Review. In 2012, Liu received the ACM SIGGRAPH Significant New Researcher Award for her contribution in the field of computer graphics.