Stanford University
Showing 18,131-18,140 of 36,179 Results
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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
Associate Professor of Computer Science, Senior Fellow at the Stanford Institute for Human-Centered AI, and Associate Professor, by courtesy, of Statistics
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.
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Richard Liang
MD Student with Scholarly Concentration in Health Services & Policy Research / Global Health, expected graduation Spring 2026
Ph.D. Student in Epidemiology and Clinical Research with Scholarly Concentration in Health Services & Policy Research / Global Health, admitted Autumn 2022
MSTP Student
Master of Arts Student in East Asian Studies, admitted Spring 2024Current Research and Scholarly InterestsPrimary research interests include:
- applications of advanced epidemiological methods
- life course health and social epidemiology
- bridging population health and basic science research
Clinical & health services research topics have included:
- maternal/child health
- geriatrics/aging
- dermatology, particularly inflammatory skin diseases
