Showing 41-50 of 73 Results

  • Michael Lin

    Michael Lin

    Associate Professor of Neurobiology, of Bioengineering and, by courtesy, of Chemical and Systems Biology

    Current Research and Scholarly InterestsOur lab applies biochemical and engineering principles to the development of protein-based tools for investigating biology in living animals. Topics of investigation include fluorescent protein-based voltage indicators, synthetic light-controllable proteins, bioluminescent reporters, and applications to studying animal models of disease.

  • Aaron Lindenberg

    Aaron Lindenberg

    Professor of Materials Science and Engineering and of Photon Science

    BioLindenberg's research is focused on visualizing the ultrafast dynamics and atomic-scale structure of materials on femtosecond and picosecond time-scales. X-ray and electron scattering and spectroscopic techniques are combined with ultrafast optical techniques to provide a new way of taking snapshots of materials in motion. Current research is focused on the dynamics of phase transitions, ultrafast properties of nanoscale materials, and charge transport, with a focus on materials for information storage technologies, energy-related materials, and nanoscale optoelectronic devices.

  • Christian Linder

    Christian Linder

    Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical 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 and, by courtesy, of Computer Science and of Electrical Engineering

    BioScott is an Assistant Professor of Statistics and, by courtesy, Electrical Engineering and Computer Science at Stanford University. He is also an Institute Scholar in the Wu Tsai Neurosciences Institute and a member of Stanford Bio-X and the Stanford AI Lab. His lab works at the intersection of machine learning and computational neuroscience, developing statistical methods to analyze large scale neural data. Previously, Scott was a postdoctoral fellow with Liam Paninski and David Blei at Columbia University, and he completed his PhD in Computer Science at Harvard University with Ryan Adams and Leslie Valiant. He obtained his undergraduate degree in Electrical and Computer Engineering from Cornell University and spent three years as a software engineer at Microsoft before graduate school.

  • Bruce Ling

    Bruce Ling

    Assistant Professor (Research) of Surgery (Pediatric Surgery)

    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.

  • 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.

  • Wendy Liu, MD, PhD

    Wendy Liu, MD, PhD

    Assistant Professor of Ophthalmology

    Current Research and Scholarly InterestsDr. Liu's research interests include the role of mechanosensation in the eye as it relates to the pathophysiology of glaucoma, with the goal of finding new druggable targets in glaucoma treatment.

  • Wu Liu

    Wu Liu

    Member, Bio-X

    Current Research and Scholarly InterestsTheranostic nanoparticles for radiosensitization and medical imaging. Novel treatment technique for ocular disease radiotherapy. Radio-neuromodulation using focused kV x-rays. Use artificial intelligence in image guided radiotherapy and medical image analysis. Ultrasound parametric imaging.