Stanford University
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Cordelia Erickson-Davis MD PhD MPH
Clinical Assistant Professor, Psychiatry and Behavioral Sciences
BioDr. C. Erickson-Davis is a psychiatrist and medical anthropologist specializing in the care of patients with Functional Neurological Disorder (FND), and other complex neuropsychiatric presentations. Her clinical work is grounded in a deep respect for the lived experience of illness and healing and integrates neurological, psychiatric, and sociocultural perspectives. She is committed to collaborative, trauma-informed care that honors the mind-body relationship without reduction.
Her research investigates how theories of mind and brain are shaped by social context - and how, in turn, those theories of perception shape lived experience, including in the clinic. She is developing the framework of Perception as Constitutive Intra-action (PCI) to theorize these dynamics, and is currently writing a book on the lived experience of visual prosthesis users and the history of “information” in the neurosciences, tracing how it has shaped theories, technologies, and subjective experience.
She leads the Precision Language Lab Initiative at Stanford, a space for collaborative inquiry into how lived experience, narrative, and perception can be more meaningfully integrated into the clinical neurosciences. -
Anton Ermakov
Assistant Professor of Aeronautics and Astronautics and, by courtesy, of Geophysics and of Earth and Planetary Sciences
Current Research and Scholarly InterestsI am interested in the formation and evolution of the Solar System bodies and the ways we can constrain planetary interiors by geophysical measurements.
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Stefano Ermon
Associate Professor of Computer Science and Senior Fellow at the Woods Institute for the Environment
On Partial Leave from 10/01/2025 To 06/30/2026BioI am an Assistant Professor in the Department of Computer Science at Stanford University, where I am affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment.
My research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability.
