Computer Science
Showing 2,001-2,100 of 2,209 Results
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Sanna Kaisa Wong Toropainen
Graduate, Computer Science
BioSanna Wong-Toropainen researches neuro-symbolic AI approaches to regulatory compliance and legal reasoning. Her doctoral work at the University of Helsinki Faculty of Law focuses on computational methods for interpreting EU digital regulations, including the AI Act, Data Act, and GDPR.
At Stanford CodeX, she is conducting the ComplianceTwin research pilot with five European enterprises (including Vaisala, PwC Finland, Tieto, iLOQ), developing AI systems that transform regulatory texts into structured legal knowledge for explainable compliance decisions. The project investigates how knowledge graphs and large language models can support traceable legal reasoning in high-stakes regulatory contexts.
She is affiliated with the University of Helsinki Legal Tech Lab and the Trust-M research consortium on trustworthy AI-enabled digital infrastructures (Strategic Research Council of Finland). Her research is supported by scholarships from the Finnish Work Environment Fund and the Foundation for Economic Development. Previously, she served as Data Protection Officer for Finland's Criminal Sanctions Agency and co-founded Muna.io, a privacy-tech startup. -
Theodora Worledge
Ph.D. Student in Computer Science, admitted Autumn 2022
BioTheodora (Teddi) Worledge is a PhD student in Computer Science at Stanford University, where she works on making machine learning models more reliable and trustworthy. Her research focuses on developing interpretability and attribution tools that help users verify and understand language model outputs. She is advised by Carlos Guestrin and supported by the NSF Graduate Research Fellowship. Before Stanford, she earned her BA in Computer Science from UC Berkeley.
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Jiajun Wu
Assistant Professor of Computer Science and, by courtesy, of Psychology
BioJiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University, working on computer vision, machine learning, robotics, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu's research has been recognized through the Young Investigator Programs (YIP) by ONR and by AFOSR, the NSF CAREER award, the Okawa research grant, the AI's 10 to Watch by IEEE Intelligent Systems, paper awards and finalists at ICCV, CVPR, SIGGRAPH Asia, ICRA, CoRL, and IROS, dissertation awards from ACM, AAAI, and MIT, the 2020 Samsung AI Researcher of the Year, and faculty research awards from Microsoft, Google, Nvidia, J.P. Morgan, Samsung, Amazon, and Meta.
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Tiange Xiang
Ph.D. Student in Computer Science, admitted Autumn 2022
BioTiange Xiang is a Ph.D. student in Computer Science at Stanford University, where he is a member of the Stanford AI Lab (SAIL) and Stanford Vision and Learning Lab (SVL). His research interests include machine learning and computer vision in general. He received a bachelor's degree in Computer Science and Technology (Advanced)(Honors) from the University of Sydney, where he was awarded Honors Class I and the University Medal.
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Connor Lucero Yako
Affiliate, Computer Science
BioHello, whoever is reading this! My name is Connor, and I am a recent Mechanical Engineering PhD graduate advised by Ken Salisbury. My research focused on non-anthropomorphic means for robotic in-hand manipulation, specifically, how vibrations can be used to move grasped parts in desirable ways. The totality of my dissertation provides both a solid theoretical and practical foundation for the use of vibrations for robotic in-hand manipulation. Post graduation, I hope to apply the research and electromechanical skills I have learned to robotics in general, though I still view the "hand" as perhaps the most interesting and elusive part of robotics today.
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Daniel Yamins
Associate Professor of Psychology and of Computer Science
Current Research and Scholarly InterestsOur lab's research lies at intersection of neuroscience, artificial intelligence, psychology and large-scale data analysis. It is founded on two mutually reinforcing hypotheses:
H1. By studying how the brain solves computational challenges, we can learn to build better artificial intelligence algorithms.
H2. Through improving artificial intelligence algorithms, we'll discover better models of how the brain works.
We investigate these hypotheses using techniques from computational modeling and artificial intelligence, high-throughput neurophysiology, functional brain imaging, behavioral psychophysics, and large-scale data analysis. -
Diyi Yang
Assistant Professor of Computer Science
BioDiyi Yang is an Assistant Professor in Computer Science at Stanford University. Professor Yang's research interests are Computational Social Science and Natural Language Processing. Her research goal is to understand the social aspects of language and then build socially aware NLP systems to better support human-human and human-computer interaction. Professor Yang received her PhD from the School of Computer Science, Carnegie Mellon University, and her bachelor's degree from Shanghai Jiao Tong University, China. Her work has received multiple best paper nominations or awards at ICWSM, EMNLP, SIGCHI, ACL, and CSCW. She is a recipient of Forbes 30 under 30 in Science, IEEE “AI 10 to Watch”, the Intel Rising Star Faculty Award, Microsoft Research Faculty Fellowship, and NSF CAREER Award.
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Serena Yeung-Levy
Assistant Professor of Biomedical Data Science and, by courtesy, of Electrical Engineering and of Computer Science
BioDr. Serena Yeung-Levy is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. Her research focus is on developing artificial intelligence and machine learning algorithms to enable new capabilities in biomedicine and healthcare. She has extensive expertise in deep learning and computer vision, and has developed computer vision algorithms for analyzing diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images.
Dr. Yeung-Levy leads the Medical AI and Computer Vision Lab at Stanford. She is affiliated with the Stanford Artificial Intelligence Laboratory, the Clinical Excellence Research Center, and the Center for Artificial Intelligence in Medicine & Imaging. She is also a Chan Zuckerberg Biohub Investigator and has served on the NIH Advisory Committee to the Director Working Group on Artificial Intelligence.
