Stanford University
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Orr Zohar
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
BioOrr Zohar is a PhD candidate in Electrical Engineering at Stanford University and a Knight-Hennessy Scholar. He builds large-scale multimodal foundation models - spanning data curation, pretraining, and post-training - with a focus on video understanding, long-horizon reasoning, and robust transfer under real-world distribution shift. His work includes open-source model and dataset efforts and methods for evaluation and alignment of multimodal systems, with an emphasis on turning research into deployment-ready learning systems.
Before Stanford, he earned a BSc in Chemical Engineering (summa cum laude) and an MSc in Electrical Engineering from the Technion–Israel Institute of Technology, and worked as a machine learning and algorithms engineer at proteanTecs. Earlier research experiences include applied sensing and medical-imaging work. -
James Zou
Associate Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering
Current Research and Scholarly InterestsMy group works on both foundations of statistical machine learning and applications in biomedicine and healthcare. We develop new technologies that make ML more accountable to humans, more reliable/robust and reveals core scientific insights.
We want our ML to be impactful and beneficial, and as such, we are deeply motivated by transformative applications in biotech and health. We collaborate with and advise many academic and industry groups. -
Tijana Zrnic
Assistant Professor of Statistics, of Management Science and Engineering and, by courtesy, of Computer Science
BioTijana Zrnic is an Assistant Professor at Stanford University, jointly appointed between Statistics, Management Science & Engineering, and, by courtesy, Computer Science. She works on foundational questions in machine learning, statistics, and data-driven decision-making. Example topics of interest include AI-assisted statistical inference and data collection, performative prediction, and studying selection bias.
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Adam Zsarnoczay
Senior Research Engineer
Current Research and Scholarly InterestsAdam's research focuses on disaster simulations that support multi-hazard risk assessment and management at a regional scale. His research interests include probabilistic natural hazard assessment, model development and calibration for structural response estimation and performance assessment, surrogate modeling and uncertainty quantification in large-scale, regional simulations, and using quantitative disaster simulations to support risk management and mitigation.
