School of Medicine
Showing 831-840 of 923 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. -
Ning Lu
Postdoctoral Scholar, Molecular Imaging Program at Stanford
BioNing Lu received a joint Ph.D. degree in Biomedical Engineering and Scientific Computing from the University of Michigan, Ann Arbor, USA, in 2023. Previously, she earned a B.S.E. degree (highest honors) in Biomedical Engineering from Southeast University, Nanjing, China, in 2018. From May 2022 to September 2022, she worked at Meta (formerly Facebook) Reality Labs as a research scientist intern on ultrasonic eye tracking for AR/VR wearable devices, in Redmond, Washington, USA. Her research interests include ultrasound instrumentation, ultrasound therapy, ultrasound imaging algorithms, and AI in healthcare.
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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