Stanford University
Showing 2,301-2,320 of 2,546 Results
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Junjie Lu
Ph.D. Student in Epidemiology and Clinical Research, admitted Autumn 2023
BioJunjie's research is centered on the social determinants of minority health, epidemiological methods, and clinical effectiveness. He is deeply committed to understanding the health disparities faced by minority populations. His clinical background helps bridge the gap between research and practical application, aiming to improve healthcare outcomes in real-world settings.
Junjie Lu earned a Master of Public Health degree from the Harvard T.H. Chan School of Public Health, where he concentrated on Health and Social Behavior. He also holds an MBBS and an MS from Shanghai University of Traditional Chinese Medicine. Junjie gained practical experience as an intern doctor at a university hospital for two years, during which he led a pilot randomized controlled trial on the effects of acupuncture on depressive symptoms. -
Lu Lu
Postdoctoral Scholar, Mechanical Engineering
BioDr. Lu Lu is currently a postdoctoral researcher at Stanford University. He received his B.S. and Ph.D. degrees from Ningbo University and Shanghai University in China in 2014 and 2019, respectively. He then worked as a postdoctoral researcher at Peking University from 2020 to 2022 before joining Stanford. His research interests focus on solid mechanics, with emphasis on mechanical instabilities, deployable structures, mechanics of intelligent soft materials, plate and shell theories, and nonlocal elasticity. He has published nearly 30 peer-reviewed papers in journals such as PNAS, JMPS, IJSS, AMR, IJMS, JAM, and PRSA, and received the ASME Melville Medal in 2024.
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Pan Lu
Postdoctoral Scholar, Biomedical Data Sciences
Current Research and Scholarly InterestsMy research goal is to build machines that can reason and collaborate with humans for the common good. My primary research focuses on machine learning and NLP, particularly machine reasoning, mathematical reasoning, and scientific discovery:
1. Mathematical reasoning in multimodal and knowledge-intensive contexts
2. Tool-augmented large language models for planning, reasoning, and generation
3. Parameter-efficient fine-tuning for fondation models
4. AI for scientific reasoning and discovery
