Wu Tsai Human Performance Alliance


Showing 161-178 of 178 Results

  • Greg Walton

    Greg Walton

    Associate Professor of Psychology

    Current Research and Scholarly InterestsMy research examines the nature of self and identity, often in the context of academic motivation and achievement. I'm interested in social factors relevant to motivation, in stereotypes and group differences in school achievement, and in social-psychological interventions to raise achievement and narrow group differences.

  • Brian A. Wandell

    Brian A. Wandell

    Isaac and Madeline Stein Family Professor and Professor, by courtesy, of Electrical Engineering, of Ophthalmology and at the Graduate School of Education

    Current Research and Scholarly InterestsModels and measures of the human visual system. The brain pathways essential for reading development. Diffusion tensor imaging, functional magnetic resonance imaging and computational modeling of visual perception and brain processes. Image systems simulations of optics and sensors and image processing. Data and computation management for reproducible research.

  • Adam Wang

    Adam Wang

    Assistant Professor of Radiology and, by courtesy, of Electrical Engineering

    BioMy group develops technologies for advanced x-ray and CT imaging, including artificial intelligence for CT acquisition, reconstruction, and image processing; novel system and detector designs; spectral imaging; model-based image reconstruction; and radiation transport methods. I am also the Director of the Zeego Lab and the Tabletop X-Ray Lab.

    I completed my PhD in Electrical Engineering at Stanford under the supervision of Dr. Norbert Pelc, developing strategies for maximizing the information content of dual energy CT and photon counting detectors. I then pursued a postdoc at Johns Hopkins with Dr. Jeff Siewerdsen in Biomedical Engineering, developing reconstruction and registration methods for x-ray based image-guided surgery. Prior to returning to Stanford in 2018, I was a Senior Scientist at Varian Medical Systems, developing x-ray/CT methods for image-guided radiation therapy.

  • Gordon Wetzstein

    Gordon Wetzstein

    Associate Professor of Electrical Engineering and, by courtesy, of Computer Science

    BioGordon Wetzstein is an Associate Professor of Electrical Engineering and, by courtesy, of Computer Science at Stanford University. He is the leader of the Stanford Computational Imaging Lab and a faculty co-director of the Stanford Center for Image Systems Engineering. At the intersection of computer graphics and vision, computational optics, and applied vision science, Prof. Wetzstein's research has a wide range of applications in next-generation imaging, display, wearable computing, and microscopy systems. Prior to joining Stanford in 2014, Prof. Wetzstein was a Research Scientist at MIT, he received a Ph.D. in Computer Science from the University of British Columbia in 2011 and graduated with Honors from the Bauhaus in Weimar, Germany before that. He is the recipient of an NSF CAREER Award, an Alfred P. Sloan Fellowship, an ACM SIGGRAPH Significant New Researcher Award, a Presidential Early Career Award for Scientists and Engineers (PECASE), an SPIE Early Career Achievement Award, a Terman Fellowship, an Okawa Research Grant, the Electronic Imaging Scientist of the Year 2017 Award, an Alain Fournier Ph.D. Dissertation Award, and a Laval Virtual Award as well as Best Paper and Demo Awards at ICCP 2011, 2014, and 2016 and at ICIP 2016.

  • Matthew Wheeler

    Matthew Wheeler

    Assistant Professor of Medicine (Cardiovascular Medicine)

    Current Research and Scholarly InterestsTranslational research in rare and undiagnosed diseases. Basic and clinical research in cardiomyopathy genetics, mechanisms, screening, and treatment. Investigating novel agents for treatment of hypertrophic cardiomyopathy and new mechanisms in heart failure. Cardiovascular screening and genetics in competitive athletes, disease gene discovery in cardiomyopathy and rare disease. Informatics approaches to rare disease and multiomics. Molecular transducers of physical activity bioinformatics.

  • Carl Wieman

    Carl Wieman

    Cheriton Family Professor and Professor of Physics and of Education

    Current Research and Scholarly InterestsThe Wieman group’s research generally focuses on the nature of expertise in science and engineering, particularly physics, and how that expertise is best learned, measured, and taught. This involves a range of approaches, including individual cognitive interviews, laboratory experiments, and classroom interventions with controls for comparisons. We are also looking at how different classroom practices impact the attitudes and learning of different demographic groups.

  • Leanne Williams

    Leanne Williams

    Professor of Psychiatry and Behavioral Sciences (Major Laboratories and Clinical Translational Neurosciences Incubator) and, by courtesy, of Psychology

    Current Research and Scholarly InterestsA revolution is under way in psychiatry. We can now understand mental illness as an expression of underlying brain circuit disruptions, shaped by experience and genetics. Our lab is defining precision brain circuit types for depression, anxiety and attention deficit. We apply computational models to large amounts of brain imaging, behavior and other data. These precision brain types inform our translational intervention studies. To close the loop, field ready insights are applied in practice.

  • Jiajun Wu

    Jiajun Wu

    Assistant Professor of Computer Science

    BioJiajun Wu is an Assistant Professor of Computer Science at Stanford University, working on computer vision, machine learning, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science at Massachusetts Institute of Technology. Wu's research has been recognized through the ACM Doctoral Dissertation Award Honorable Mention, the AAAI/ACM SIGAI Doctoral Dissertation Award, the MIT George M. Sprowls PhD Thesis Award in Artificial Intelligence and Decision-Making, the 2020 Samsung AI Researcher of the Year, the IROS Best Paper Award on Cognitive Robotics, and faculty research awards and graduate fellowships from Samsung, Amazon, Facebook, Nvidia, and Adobe.

  • Tony Wyss-Coray, PhD

    Tony Wyss-Coray, PhD

    D. H. Chen Professor II

    Current Research and Scholarly InterestsUse of genetic and molecular tools to dissect immune and inflammatory pathways in Alzheimer's and neurodegeneration.

  • Phillip C. Yang, MD

    Phillip C. Yang, MD

    Professor of Medicine (Cardiovascular Medicine)

    Current Research and Scholarly InterestsDr. Yang is a physician-scientist whose research interest focuses on clinical translation of the fundamental molecular and cellular processes of myocardial restoration. His research employs novel in vivo multi-modality molecular and cellular imaging technology to translate the basic innovation in cardiovascular pluripotent stem cell biologics. Dr. Yang is currently a PI on the NIH/NHLBI funded CCTRN UM1 grant, which is designed to conduct multi-center clinical trial on novel biological therapy.

  • Yunzhi Peter Yang

    Yunzhi Peter Yang

    Professor of Orthopaedic Surgery and, by courtesy, of Materials Science and Engineering and of Bioengineering

    Current Research and Scholarly InterestsYang’ lab's research interests are in the areas of bio-inspired biomaterials, medical devices, and 3D printing approaches for re-creating a suitable microenvironment for cell growth and tissue regeneration for musculoskeletal disease diagnosis and treatment, including multiple tissue healing such as rotator cuff injury, orthopedic diseases such as osteoporosis and osteonecrosis, and orthopedic traumas such as massive bone and muscle injuries.

  • Jason Yeatman

    Jason Yeatman

    Assistant Professor of Pediatrics (Developmental-Behavioral Pediatrics), of Education and of Psychology

    BioDr. Jason Yeatman is an Assistant Professor in the Graduate School of Education and Division of Developmental and Behavioral Pediatrics at Stanford University. Dr. Yeatman completed his PhD in Psychology at Stanford where he studied the neurobiology of literacy and developed new brain imaging methods for studying the relationship between brain plasticity and learning. After finishing his PhD, he took a faculty position at the University of Washington’s Institute for Learning and Brain Sciences before returning to Stanford.

    As the director of the Brain Development and Education Lab, the overarching goal of his research is to understand the mechanisms that underlie the process of learning to read, how these mechanisms differ in children with dyslexia, and to design literacy intervention programs that are effective across the wide spectrum of learning differences. His lab employs a collection of structural and functional neuroimaging measurements to study how a child’s experience with reading instruction shapes the development of brain circuits that are specialized for this unique cognitive function.

  • Serena Yeung

    Serena Yeung

    Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering

    BioDr. Serena Yeung is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. Her research focus is on developing artificial intelligence and machine learning algorithms to enable new capabilities in biomedicine and healthcare. She has extensive expertise in deep learning and computer vision, and has developed computer vision algorithms for analyzing diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images.

    Dr. Yeung leads the Medical AI and Computer Vision Lab at Stanford. She is affiliated with the Stanford Artificial Intelligence Laboratory, the Clinical Excellence Research Center, the Center for Artificial Intelligence in Medicine & Imaging, the Center for Human-Centered Artificial Intelligence, and Bio-X. She also serves on the NIH Advisory Committee to the Director Working Group on Artificial Intelligence.

  • Michael Zeineh

    Michael Zeineh

    Associate Professor of Radiology (Neuroimaging and Neurointervention)

    BioDr. Michael Zeineh received a B.S. in Biology at Caltech in 1995 and obtained his M.D.-Ph.D. from UCLA in 2003. After internship also at UCLA, he went on to radiology residency and neuroradiology fellowship both at Stanford. He has been faculty in Stanford Neuroradiology since 2010. Combining clinical acumen in neuroradiology with advanced MRI acquisition and image processing as well as histologic validation, Dr. Zeineh hopes to advance the care of patients with neurodegenerative disorders.

  • Jamie Zeitzer

    Jamie Zeitzer

    Associate Professor (Research) of Psychiatry and Behavioral Sciences (Sleep Medicine)

    Current Research and Scholarly InterestsDr. Zeitzer is a circadian physiologist specializing in the understanding of the impact of light on circadian rhythms and other aspects of non-image forming light perception.
    He examines the manner in which humans respond to light and ways to manipulate this responsiveness, with direct application to jet lag, shift work, and altered sleep timing in teens. Dr. Zeitzer has also pioneered the use of actigraphy in the determination of epiphenomenal markers of psychiatric disorders.

  • Renee Zhao

    Renee Zhao

    Assistant Professor of Mechanical Engineering

    BioRuike Renee Zhao is an Assistant Professor of Mechanical Engineering at Stanford University where she directs the Soft Intelligent Materials Laboratory. Renee received her BS degree from Xi'an Jiaotong University in 2012, and her MS and PhD degrees from Brown University in 2014 and 2016, respectively. She was a postdoc associate at MIT during 2016-2018 prior to her appointment as an Assistant Professor in the Department of Mechanical and Aerospace Engineering at The Ohio State University from 2018 to 2021.
    Renee’s research concerns the development of stimuli-responsive soft composites for multifunctional robotic systems with integrated shape-changing, assembling, sensing, and navigation. By combining mechanics, polymer engineering, and advanced material manufacturing techniques, the functional soft composites enable applications in soft robotics, miniaturized biomedical devices, flexible electronics, deployable and morphing structures.
    Renee is a recipient of the 2022 ASME Henry Hess Early Career Publication Award, 2022 ASME Pi Tau Sigma Gold Medal, 2021 ASME Applied Mechanics Division Journal of Applied Mechanics Award, 2020 NSF Career Award, and 2018 ASME Applied Mechanics Division Haythornthwaite Research Initiation Award.