Stanford University
Showing 18,101-18,150 of 36,301 Results
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Zhongxiao Li
Postdoctoral Scholar, Radiation Physics
BioZhongxiao Li is a postdoctoral researcher in Professor Ruijiang Li's lab at Stanford Medicine. His research focuses on computational biology and bioinformatics, particularly the development of deep learning methods for computational pathology and spatial transcriptomics/proteomics. Previously, his work has included developing machine learning models for histopathological image analysis, understanding gene regulation, and analyzing biological sequences.
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Zongbo Li
Postdoctoral Scholar, Health Policy
BioZongbo Li, PhD, is a postdoctoral researcher at Stanford Health Policy. His research focuses on applying simulation modeling and cost-effectiveness analysis to inform policy decisions related to substance use and infectious diseases. He evaluates overdose prevention interventions, including naloxone distribution and medications for opioid use disorder, with particular attention to vulnerable populations such as people who are incarcerated. His work also encompasses modeling infectious diseases and evaluating interventions for COVID-19, HIV, and HCV. Zongbo earned his PhD in Health Services Research, Policy & Administration from the University of Minnesota.
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April Shichu Liang
Clinical Assistant Professor, Medicine
BioApril S. Liang, M.D., is a Board-Certified internist and Clinical Informaticist. She serves as Clinical Assistant Professor in the Stanford Division of Hospital Medicine as well as Medical Informatics Director. Dr. Liang holds a B.S.E. in Computer Science from Princeton University and an M.D. from UCSF School of Medicine. She completed Internal Medicine residency at UCSF and Clinical Informatics fellowship at Stanford. Dr. Liang’s informatics interests include the implementation of AI tools in healthcare and data-driven quality improvement. Her past work includes the integrating a machine learning-driven clinical decision support tool in the EHR targeting lab overutilization and measuring the impact of ambient AI scribes on clinician documentation time.
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Dong Liang
Instructional Designer Dvlpr 2, IT Services
BioMy background gives me a unique perspective on the question of learning design. I have formal education in both computer science and humanities, which means I am not only trained to understand how technologies work, but also have strong research and writing skills. Years of reading and writing argumentative essays makes me fluent at the art of communicating complex ideas. I have extensive classroom teaching experience, which gives me a big advantage when approaching the problem of instructional design because I learned how to create e-learning courses from brick-and-mortar experiences. Finally, my passion for education technology drives me toward using innovative tools to create engaging, immersive learning experiences, within or without a classroom.
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Jiahao Liang
Ph.D. Student in Molecular and Cellular Physiology, admitted Autumn 2020
OTL Intern, Office of Technology Licensing (OTL)BioI'm currently a 6th-year Ph.D. student in Molecular & Cellular Physiology and an intern at the Office of Technology Licensing. I study how the spatial organization and structural conformation of synaptic proteins regulate synaptic transmission.
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Jing Liang
Postdoctoral Scholar, Computer Science
BioJing Liang is a postdoctoral scholar in the Department of Computer Science at Stanford University, where he is affiliated with the Stanford Robotics Center and the Stanford Center on Longevity. He received his Ph.D. in Computer Science from the University of Maryland, College Park.
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Mengning Liang
Lead Scientist, SLAC National Accelerator Laboratory
Current Role at StanfordMy role at LCLS at SLAC is SRD Deputy Director for Strategic Development - I aid management to develop FEL science sustainably and to increase the impact of FEL science in the broader scientific community.
Coherent X-ray Imaging (CXI) Instrument lead - Lead one of the scientific instruments at LCLS. CXI is a hard X-ray, in-vacuum instrument which specialized in low signal to noise experiments due to a vacuum sample environment and high X-ray power measurements due to a nanofocus beam which can provide X-ray power up to 10^20W/cm^2
LCLS-II-HE CXI upgrade science lead. LCLS-II-HE is an upgrade of the LCLS X-ray Free Electron Laser which will take the repetition rate from 120Hz to 1MHz. The CXI instrument will undergo a complete upgrade to maximally utilize this unprecedented new source. -
Mengyu Liang (Amber)
Postdoctoral Scholar, Earth System Science
BioI'm currently a postdoc at Stanford Woods Institute of the Environment working on combining remote sensing and econometric to assess the environmental and social outcomes of natural climate solutions and forest management interventions. I completed my PhD at the Department of Geographical Sciences at UMD in May 2024. During my PhD, I developed remote sensing techniques utilizing multi-source remote sensing data (e.g,. GEDI, ICESat2, Landsat archive, PlanetScope) for monitoring long-term carbon sequestration in forest restoration areas in East Africa. Seeking to understand how to use Earth Observation to improve the sustainability of human-environment interaction is both a passion of mine and the research agenda during my PhD and onwards. Moreover, I have developed skills in forest inventory and Terrestrial Laser Scanner (TLS) data collection from working on field campaigns in Mozambique and Uganda. Developing web-based interactive map dashboards is another set of technical expertise that I have been practicing (see http://mliang8.github.io/ for map portfolio ) and want to employ in future projects to enhance communications with various stakeholders.
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Percy Liang
Professor of Computer Science
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011) and the director of the Center for Research on Foundation Models (CRFM). He is currently focused on making foundation models (in particular, language models) more accessible through open-source and understandable through rigorous benchmarking. In the past, he has worked on many topics centered on machine learning and natural language processing, including robustness, interpretability, human interaction, learning theory, grounding, semantics, and reasoning. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), a Microsoft Research Faculty Fellowship (2014), and paper awards at ACL, EMNLP, ICML, COLT, ISMIR, CHI, UIST, and RSS.
