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Leonardo Aliaga is a Clinical Assistant Professor in the Department of Emergency Medicine at Stanford University, specializing in medical education research. His scholarly focus lies in error-based learning strategies, adaptive expertise, and clinical reasoning. As a co-Principal Investigator of the Right Kind Reps initiative, he has developed an AI-powered virtual patient simulator aimed at accelerating diagnostic skill development through purposeful exposure to cognitive struggles. His research has been published in JAMA Network Open and focuses on designing instructional methods that utilize errors as cognitive catalysts to deepen learning and cultivate adaptive expertise. Currently, he is pursuing a Master's in Health Professions Education from the University of Illinois at Chicago, where his thesis aims to establish a framework for implementing error-based learning strategies in diverse medical education settings. Dr. Aliaga collaborates with colleagues from renowned institutions, including UC Davis and the University of Toronto, enhancing educational methodologies within the Failure Education Research Network (FERN). His unique background in neurosurgery before transitioning to emergency medicine contributes significantly to his teaching philosophy, which emphasizes visual clarity and storytelling to help learners navigate the complexities of clinical practice. Known for delivering high-yield, visually rich learning experiences, he strives to transform missteps into mastery for his residents.
Stanford University • Stanford, CA
Teaching and research in Emergency Medicine and medical education.
The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.