Stanford University
Showing 781-800 of 2,733 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, published in 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). -
Adam He
Postdoctoral Scholar, Genetics
BioI am a computational biologist/bioinformatician. My primary research interests lie in using machine learning models to decipher how gene regulation is encoded in our genomes. I’ve also worked on variant effect and complex disease risk prediction.
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Siyu He
Postdoctoral Scholar, Biomedical Data Sciences
BioI am a postdoctoral fellow in the Department of Biomedical Data Science at Stanford University, where I am advised by Dr. James Zou and Dr. Stephen Quake.
My research interests lie at the intersection of statistical machine learning, computational biology, stem cell engineering, and disease modeling. My mission is to leverage AI methodologies in biomedicine to accelerate our understanding of diseases. I earned my PhD in Biomedical Engineering from Columbia University, where I am co-advised by Dr. Kam Leong and Dr. Elham Azizi. I hold a Bachelor's degree in Physics from Xi'an Jiaotong University. -
Yahui He
Postdoctoral Scholar, Archaeology
BioYahui He is an environmental archaeologist specializing in archaeobotany in East Asia. Her research investigates the dynamics of human-plant relationships in multi-scalar socio-political contexts, focusing on the materiality of plants in processes of sedentism and urbanism.
Her PhD and ongoing research work in the Northern Zone, China (northern Loess Plateau and southern Mongolian Plateau) utilizes multi-proxy methods, including starch, phytolith, fungi, and use-wear analyses, to explore plant-based food and drink practices across different social contexts, such as household, community, and mortuary settings. Yahui’s collaborative research extends to studies on plant exploitation and dispersal, as well as related technologies such as plant food fermentation and bast fiber production across mainland China and beyond, including Erlitou in Henan and others in Taiwan and Honduras.
Prior to joining the Stanford Archaeology Center as a postdoctoral scholar, Yahui obtained her PhD at Stanford and was a Li Foundation in New York Fellow at the Needham Research Institute in Cambridge, UK (2024). -
Yan He
Postdoctoral Scholar, Infectious Diseases
BioI am an air quality and environmental health researcher with experience in field monitoring, exposure assessment, and spatial analysis. My research focuses on characterizing air pollution across communities, identifying potential sources, and improving our understanding of environmental exposures.
