School of Engineering
Showing 51-100 of 1,815 Results
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Youssef Allouah
Postdoctoral Scholar, Computer Science
BioYoussef Allouah is a postdoctoral scholar at Stanford University. He is working with Prof. Sanmi Koyejo at the Computer Science department. His research interests are broadly in the principles of trustworthy machine learning, specifically the theory and practice of privacy, robustness, and unlearning.
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Emily Alsentzer
Assistant Professor of Biomedical Data Science, of Medicine (Computational Medicine) and, by courtesy, of Computer Science
BioDr. Emily Alsentzer is an Assistant Professor in Biomedical Data Science and, by courtesy, Computer Science at Stanford University. Her research leverages machine learning (ML) and natural language processing (NLP) to augment clinical decision-making and broaden access to high quality healthcare. She focuses on integrating medical expertise into ML models to ensure responsible deployment in clinical workflows. Dr. Alsentzer completed a postdoctoral fellowship at Brigham and Women’s Hospital where she worked to deploy ML models within the Mass General Brigham healthcare system. She received her PhD from the Health Sciences and Technology program at MIT and Harvard Medical School and holds degrees in computer science (BS) and biomedical informatics (MS) from Stanford University. She has served as General Chair for the Machine Learning for Health Symposium and founding organizer for SAIL and the Conference on Health, Inference, and Learning (CHIL).
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Russ B. Altman
Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine, of Biomedical Data Science, Senior Fellow at the Stanford Institute for Human-Centered AI and Professor, by courtesy, of Computer Science
Current Research and Scholarly InterestsI refer you to my web page for detailed list of interests, projects and publications. In addition to pressing the link here, you can search "Russ Altman" on http://www.google.com/
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Leni Aniva
Ph.D. Student in Computer Science, admitted Autumn 2022
Current Research and Scholarly InterestsMy main research interest is Machine-Assisted Theorem Proving, which refers to using machine-learning agents to find proofs of mathematical theorems and conduct reasoning. We are pursuing a hybrid algorithm between neural networks and SMT solvers to solve some of the long standing problems facing machine learning models today such as opaqueness, hallucinations, and information leakage. I also do research on SMT solvers and automatic verifications of programs.
