Stanford University
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Mark J. Schnitzer
Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences and Professor of Biology, of Applied Physics and of Neurosurgery
Current Research and Scholarly InterestsThe goal of our research is to advance experimental paradigms for understanding normal cognitive and disease processes at the level of neural circuits, with emphasis on learning and memory processes. To advance these paradigms, we invent optical brain imaging techniques, several of which have been widely adopted. Our neuroscience studies combine these imaging innovations with behavioral, electrophysiological, optogenetic and computational methods, enabling a holistic approach to brain science.
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Austin Schoeffler
Fellow in Peds/Clinical Informatics
BioAustin Schoeffler, M.D., is an emergency medicine physician and clinical informatics fellow at Stanford University. Dr. Schoeffler earned his M.D. from The Ohio State University College of Medicine and completed his Emergency Medicine Residency at University Hospitals/Case Western Reserve University in Cleveland. He is currently pursuing a two-year fellowship in Clinical Informatics at Stanford, focusing on the integration of machine learning and digital health solutions within emergency care.
Dr. Schoeffler has a strong background in both clinical operations and digital innovation. He has assisted on projects leveraging AI-driven facial recognition software for depression screening in the emergency department, and is currently critically evaluating the impact of ambient AI scribes on clinical care and helping to create the first AI benchmark for emergency medicine. His operational experience includes governance and workflow optimization at his previous institution, where he contributed to initiatives enhancing patient care delivery and hospital efficiency.
His scholarly interests center on responsible AI integration, innovation, building the future of digital health technology, and expanding access to populations not traditionally reached by existing clinical infrastructure. He is committed to fostering industry-academic partnerships, rigorously evaluating emerging AI tools, and benchmarking AI products for deployment in acute care settings. Clinically, he is passionate about evidence-based care, digital health, and the development of novel care delivery models in emergency medicine.
