Stanford University
Showing 31-40 of 168 Results
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Elaheh Hashemi
Postdoctoral Scholar, Pathology
BioI am a postdoctoral researcher specializing in computational biology, bioinformatics, and multi-omics data analysis. My research focuses on integrating single-cell, spatial transcriptomic, and clinical datasets to better understand cellular heterogeneity and disease biology. I am passionate about using computational approaches to uncover biological mechanisms and translate complex datasets into insights that can ultimately improve human health. Outside of research, I enjoy hiking, mountaineering, camping, and playing the piano.
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Hoda Hashemi
Postdoctoral Scholar, Radiological Sciences Laboratory
BioHoda S. Hashemi is a postdoctoral scholar at the Ultrasound Imaging & Instrumentation Lab at Stanford University. She received her PhD in Electrical and Computer Engineering from the University of British Columbia (UBC) in 2023. She was also an ultrasound research intern in research and innovation team at DarkVision Technologies Inc. from 2021 to 2023. She holds a M.A.Sc. from Concordia University and a B.Sc. from Sharif University of Technology. Her research interests are ultrasound molecular imaging, elastography and AI in medical image processing. Her research has been funded by the NIH T32 Fellowship at Stanford, the Canadian NSERC Postdoctoral Fellowship, and the Ultrasound Imaging & Instrumentation Lab at Stanford University.
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John Lyon Havlik
Postdoctoral Medical Fellow, Psychiatry
Resident in Psychiatry and Behavioral SciencesBioHello! I'm the inaugural Humanities and Social Medicine research track resident at Stanford University.
Psychiatric and substance use disorders are usually caught only after substantial, sometimes irreparable, harm has already occurred. My work is about changing that: I build artificial intelligence models that identify people earlier, and I evaluate whether the systems that receive them, like health plans, treatment facilities, and now generative AI chatbots, are equipped to respond appropriately. I believe this kind of early intervention will one day be commonplace and prevent a great deal of human suffering.
On the building side, I'm technical lead and first author on a supervised model that detects substance use disorders from EHR-like data, currently in press at Nature Mental Health; related work uses multimodal data to flag who will go on to develop opioid use disorder and to predict imminent psychiatric emergency-department visits. I also co-authored a Nature Medicine paper on how to rigorously test the true capabilities of medical AI. I work across a wide range of deterministic and probabilistic methods, including the transformer architectures behind modern "chatbots." My work has been featured in 40+ peer-reviewed publications and featured in national news outlets.
In production, spinout AI-enabled clinical workflow automation software I developed is in use at the U.S. Department of Veterans Affairs and here at Stanford. The aim of my work is to move advances in artificial intelligence out of publications and into the clinic.
On the evaluating side, I serve as an expert reviewer of AI-in-medicine trials for the State of Utah's Office of Artificial Intelligence Policy, and I am a sought-after health-tech advisor for Silicon Valley's leading venture capital firms and companies. I write on psychiatric services and health policy, recently in JAMA Health Forum on private-equity residential treatment and JAMA Network Open on the economics of telemedicine "house calls". Alongside my research, I founded and lead Research Roundtable, a mentorship group whose undergraduates have published 10+ first-author papers. Before medicine, with Peggy Mason at UChicago, I found the human bystander effect in rats (Science Advances).
