Stanford University
Showing 1,351-1,360 of 2,678 Results
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Chenery Lowe
Postdoctoral Scholar, Biomedical Ethics
BioChenery Lowe, Ph.D., CGC, is a genetic counselor and healthcare communication researcher. She received her ScM in Genetic Counseling from the Johns Hopkins University/ National Institutes of Health Genetic Counseling Training Program in 2018. Chenery received her Ph.D. in Social and Behavioral Sciences from Johns Hopkins Bloomberg School of Public Health in 2022, where she later served as an assistant scientist and academic director for the JHU/NIH genetic counseling program. Clinically, she has provided genetic counseling in immunology and adult oncology settings. She has taught graduate-level courses on interpersonal communication in health care, health literacy, and social and behavioral research in genetic counseling. Her research interests are in the areas of patient-provider communication, health equity, implicit bias, communication skills training interventions, and the ethics of interpersonal influence in medical care.
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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
