School of Medicine
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Seena Dehkharghani MD FAHA
Clinical Professor, Radiology
BioMy research spans human, animal, and phantom studies of cerebral perfusion and metabolism, emphasizing thermometry and neuroenergetics. My investigations into ischemic thermometry were twice recognized with the Foundation of the ASNR Scholar Award in Neuroradiology Research and subsequently by a R01 awarded by the NIBIB. My group has developed novel computational models for cerebral hemodynamics (dynamic BOLD-CVR) and first-of-kind hyperportable microwave stroke detection tools using deep learning. I have obtained formal certification (Mathworks, Google) in machine learning and data analytics and remain engaged in self-learning in AI/ML methodologies. I have also been a post-graduate student through the Stanford University School of Engineering SCPD program in Computer Science, again with a focus in artificial intelligence through the Stanford University School of Engineering, with core competencies including machine learning, Bayesian Networks, Markov Decision Processes, and Deep Learning.
I formerly served as Director of Stroke and Cerebrovacular Imaging Programs at Emory University and New York University, leading basic, translational, and clinical cerebrovascular imaging programs in collaboration with academic and industry partners worldwide. I returned to Stanford in Feb 2025 as Professor and Associate Chair of Informatics, and as Affiliate Faculty of the Wu Tsai Neuroscience Institute, Stanford Artificial Intelligence in Medicine and Imaging (AIMI) Center, Integrated Biomedical Imaging Informatics at Stanford (IBIIS), Center for Digital Health (CDH), and Human-Centered AI (HAI) Institute.
Ongoing projects that I would like to highlight include:
1R01EB034820-01 (NIBIB).
Previously, I was funded in an application to the Google AI Social Impact Challenge for the development of portable ultra-wideband microwave imaging instrumentation (patents issued), work for which I was selected to the NIH-NIBIB c3i Concept to Clinic: Commercializing Innovation Program.
Presently, we have proposed to develop realistic computational models of ischemic stroke and bridge a heretofore unattempted multiscale and multiphysics view of neuroenergetic disturbance in the ischemic brain. The merger of a state of the art in silico neurobiological canvas with more than a decade of insights from rigorous experimental neuroscience and biophysical modeling points us to disturbed thermoregulation/dysthermia at the critical intersection of cerebral perfusion, metabolism, viability, and hence neuroenergetic balance.
Cerebral dysthermia will be formalized in a radical departure from the historically perfusion-centered frame of reference in cerebrovascular ischemia, the latter having shown unfit to capture fully the adaptive, dynamic metabolic changes that subserve the ischemic brain. We leverage the pathoanatomic realism of our complete multiscale vascular, flow, and perfusion model tuned to direct measures of cerebral perfusion, oximetry, and thermography across hemodynamics states in individuals subjected to hemodynamics provocation, linking two procedures developed by my lab: time-resolved BOLD cerebrovascular reactivity with acetazolamide and the brain thermal response (BTR). This work represents a new direction of cerebrovascular and neurometabolic research enabled by traditionally unattainable biomarker ensembles based in non-invasive, spatiotemporally-resolved brain thermography. -
Karl Deisseroth
D. H. Chen Professor, Professor of Bioengineering and of Psychiatry and Behavioral Sciences
Current Research and Scholarly InterestsKarl Deisseroth's laboratory created and developed optogenetics, hydrogel-tissue chemistry (beginning with CLARITY), and a broad range of enabling methods. He also has employed his technologies to discover the neural cell types and connections that cause adaptive and maladaptive behaviors.
