Stanford University
Showing 27,001-27,020 of 35,037 Results
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Michael F. Schmid
Casual - Nonexempt, Stanford Synchrotron Radiation Lightsource
BioI have had more than five decades of experience in Structural Biology. I was a co-Director of a Biomedical Technology Research Resource Center, the National Center for Macromolecular Imaging, NCMI, supported by a P41 grant for thirty years. I am currently a co-Director of a National CryoEM Service Center for Cryoelectron Microscopy, the Stanford-SLAC CryoEM Center, S2C2, and of a part of the National Network for CryoET, the Stanford-SLAC CryoET Specimen Preparation Center, SCSC.
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Ludwig Schmidt
Assistant Professor of Computer Science
BioLudwig Schmidt is an assistant professor at Stanford University in the Computer Science Department and Stanford Data Science. Ludwig’s research interests revolve around the empirical foundations of machine learning, often with a focus on datasets, reliable generalization, multimodality, and language models. Recently, Ludwig’s research group contributed to open source machine learning by creating OpenCLIP, DCLM, and the LAION-5B dataset. Ludwig completed his PhD at MIT and was a postdoc at UC Berkeley. Ludwig’s research received a new horizons award at EAAMO, best paper awards at ICML & NeurIPS, a best paper finalist at CVPR, and the Sprowls dissertation award from MIT.
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Peter Schmidt
Clinical Assistant Professor, Anesthesiology, Perioperative and Pain Medicine
BioPete Schmidt, MD, MSc is an Assistant Clinical Professor in the Department of Anesthesiology, Perioperative, and Pain Medicine, Division of Pain Medicine at Stanford University School of Medicine, where he conceptualized and launched the Stanford Cancer Pain program. He provides comprehensive and individualized care for patients with cancer-related pain, including patients who are suffering from the effects of cancer treatment. His clinical expertise also includes ultrasound-guided nerve blocks, perioperative pain management, and safe medication tapering after definitive cancer treatment. He is board-certified in Anesthesiology, Pain Medicine, and Addiction Medicine.
Dr. Schmidt's research interests are in clinical trials, drug development, and novel regulatory endpoints. He has designed and led over a dozen clinical trials in the fields of pain management, neurology, infectious diseases, and rare diseases. Dr. Schmidt has published his research findings in several high-impact journals, including Science: Translational Medicine and the New England Journal of Medicine. He is also the author of several book chapters on pain management and perioperative management. -
Leonard Schmieding
Overseas Studies - Berlin, Bing Overseas Studies
BioI studied English, American Studies, History, and History Education at universities in Germany (Freiburg im Breisgau, Leipzig) and the U.S. (Indiana). In 2011, I received my PhD from the University of Leipzig with a dissertation on hip-hop culture in communist East Germany. Since then, I have been a researcher, educator, and public historian in the San Francisco Bay Area, Washington, DC, Münster, and Berlin. While I continue to be interested in youth cultures, migration, and public memory, I am now focusing on building networks between museums, memorials, archives, schools, and universities to use the power of history for active citizenship in our societies in Germany and the U.S. I bring together scholars, curators, and educators in partnerships and professional development, and I work with students, both in secondary schools and at university, to use museum resources for deep historical learning.
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Paul Schmiedmayer
Instructor, Computational Medicine
Current Research and Scholarly InterestsDr. Schmiedmayer develops open-source agentic AI systems and multimodal foundation models that transform electronic health records, wearable sensors, and patient-generated data into personalized healthcare. His research builds the next generation of interoperable computational medicine infrastructure, enabling scalable, privacy-preserving, patient-facing AI for cardiometabolic disease prevention and the translation of AI into routine clinical practice.
