About
Logan Grosenick builds artificial intelligence and neurotechnology to make the treatment of mental illness more precise. Trained as both a neuroscientist and a statistician, he leads a lab that develops machine-learning methods to define biological subtypes of psychiatric disorders, predict who will respond to which treatment, and design the neurotechnology that produces the data those models learn from. The work spans depression, treatment-resistant depression, and autism, and that runs from algorithms to the clinic.
Before founding his lab, Logan helped build several tools now common in neuroscience: he developed fiber photometry, a method for recording the activity of genetically- and connectivity-defined neural projections that is now commercialized and used worldwide, and he pioneered the use of light-field imaging in biology for fast, volumetric recording of neural activity. His group’s work established some of the first evidence that data-driven neurophysiological subtypes, rather than symptom categories alone, can identify which patients benefit from targeted therapies such as TMS.
He is an Assistant Professor of Neuroscience in Psychiatry at Weill Cornell Medicine, in the Feil Family Brain & Mind Research Institute and the Tri-Institutional MD-PhD Program. His research is supported by the NIMH, the Whitehall Foundation, the Simons Foundation, and others, and his trainees have gone on to faculty positions and to leading roles in industry and research. The lab is actively recruiting curious people across machine learning, neuroscience, and engineering.
Bios for talks & introductions
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Speaker introduction (read aloud, ~90 words)
Logan Grosenick is an Assistant Professor of Neuroscience in Psychiatry at Weill Cornell Medicine, where he directs the Grosenick Lab. Trained as both a neuroscientist and a statistician, with a PhD from Stanford and a Simons fellowship at Columbia, he builds artificial intelligence and neurotechnology to make psychiatric treatment more precise. His lab develops machine-learning methods to define biological subtypes of depression and autism and to predict who will respond to which therapy. Earlier in his career he invented fiber photometry, now a standard recording tool in neuroscience labs worldwide.
Short bio (~80 words)
Logan Grosenick directs the Grosenick Lab at Weill Cornell Medicine, where he is an Assistant Professor of Neuroscience in Psychiatry. A neuroscientist and statistician by training (PhD, Stanford; Simons Junior Fellow, Columbia), he develops machine learning and neurotechnology to understand psychiatric illness and personalize its treatment, from data-driven biological subtypes of depression and autism to generative models that predict individual treatment response. His earlier work includes inventing fiber photometry and pioneering light-field imaging in neuroscience. His research is supported by the NIMH, the Whitehall Foundation, and others.
One line (~25 words)
Logan Grosenick is an Assistant Professor of Neuroscience in Psychiatry at Weill Cornell Medicine, building AI and neurotechnology to personalize the treatment of mental illness.