Institute for Human-Centered Artificial Intelligence (HAI)
Showing 111-120 of 188 Results
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Matthew Lungren
Adjunct Professor, Biomedical Data Science
BioDr. Lungren is Chief Data Science Officer for Microsoft Health & Life Sciences where he focuses on translating cutting edge technology, including generative AI and cloud services, into innovative healthcare applications. As a physician and clinical machine learning researcher, he maintains a part-time clinical practice at UCSF while also continuing his research and teaching roles as adjunct professor at Stanford University.
Prior to joining Microsoft, Dr Lungren was a clinical interventional radiologist and research faculty at Stanford University Medical School where he led the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI). He later served as Principal for Clinical AI/ML at Amazon Web Services in World Wide Public Sector Healthcare, focusing on business development for clinical machine learning technologies in the public cloud.
His scientific work has led to more than 150 publications, including work on multi-modal data fusion models for healthcare applications, new computer vision and natural language processing approaches for healthcare specific domains, opportunistic screening with machine learning for public health applications, open medical data as public good, prospective clinical trials for clinical AI translation, and application of generative AI in healthcare. He has served as advisor for early stage startups and large fortune-500 companies on healthcare AI technology development and go-to-market strategy. Dr. Lungren's work has been featured in national news outlets such as NPR, Vice News, Scientific American, and he regularly speaks at national and international scientific meetings on the topic of AI in healthcare.
Dr. Lungren is also a top rated instructor on Coursera where his AI in Healthcare course designed especially for learners with non-technical backgrounds has been completed by more than 20k students around the world - enrollment is open now: https://www.coursera.org/learn/fundamental-machine-learning-healthcare -
Katharine (Kate) Maher
Professor of Earth System Science, Senior Fellow at the Woods Institute for the Environment and Professor, by courtesy, of Earth and Planetary Sciences
Current Research and Scholarly InterestsHydrology, reactive transport modeling and environmental geochemistry
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Christopher Manning
Thomas M. Siebel Professor of Machine Learning, Professor of Linguistics, of Computer Science and Senior Fellow at the Stanford Institute for HAI
BioChristopher Manning is the inaugural Thomas M. Siebel Professor of Machine Learning in the Departments of Linguistics and Computer Science at Stanford University, Director of the Stanford Artificial Intelligence Laboratory (SAIL), and an Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). His research goal is computers that can intelligently process, understand, and generate human languages. Manning was an early leader in applying Deep Learning to Natural Language Processing (NLP), with well-known research on the GloVe model of word vectors, attention, machine translation, question answering, self-supervised model pre-training, tree-recursive neural networks, machine reasoning, dependency parsing, sentiment analysis, and summarization. He also focuses on computational linguistic approaches to parsing, natural language inference and multilingual language processing, including being a principal developer of Stanford Dependencies and Universal Dependencies. Manning has coauthored leading textbooks on statistical approaches to NLP (Manning and Schütze 1999) and information retrieval (Manning, Raghavan, and Schütze, 2008), as well as linguistic monographs on ergativity and complex predicates. His online CS224N Natural Language Processing with Deep Learning videos have been watched by hundreds of thousands of people. He is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and a Past President of the ACL (2015). His research has won ACL, Coling, EMNLP, and CHI Best Paper Awards, and an ACL Test of Time Award. He has a B.A. (Hons) from The Australian National University and a Ph.D. from Stanford in 1994, and an Honorary Doctorate from U. Amsterdam in 2023, and he held faculty positions at Carnegie Mellon University and the University of Sydney before returning to Stanford. He is the founder of the Stanford NLP group (@stanfordnlp) and manages development of the Stanford CoreNLP and Stanza software.
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David J. Maron
C. F. Rehnborg Professor and Professor of Medicine (Stanford Prevention Research Center)
Current Research and Scholarly InterestsDr. Maron is the Co-Chair and Principal Investigator of the ISCHEMIA trial, and Co-Chair of the ISCHEMIA-CKD trial. These large, international, NIH-funded studies will determine whether an initial invasive strategy of cardiac catheterization and revascularization plus optimal medical therapy will reduce cardiovascular events in patients with and without chronic kidney disease and at least moderate ischemia compared to an initial conservative strategy of optimal medical therapy alone.
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Jay McClelland
Lucie Stern Professor in the Social Sciences, Professor of Psychology and, by courtesy, of Linguistics and of Computer Science
On Leave from 04/01/2024 To 06/30/2024Current Research and Scholarly InterestsMy research addresses topics in perception and decision making; learning and memory; language and reading; semantic cognition; and cognitive development. I view cognition as emerging from distributed processing activity of neural populations, with learning occurring through the adaptation of connections among neurons. A new focus of research in the laboratory is mathematical cognition and reasoning in humans and contemporary AI systems based on neural networks.
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Daniel McFarland
Professor of Education and, by courtesy, of Sociology and of Organizational Behavior at the Graduate School of Business
Current Research and Scholarly InterestsThe majority of my current research projects concern the sociology of science and research innovation. Here are some examples of projects we are pursuing:
1. the process of intellectual jurisdiction across fields and disciplines
2. the process of knowledge innovation diffusion in science
3. the propagators of scientific careers and advance
4. the role of identity and diversity on the process of knowledge diffusion and career advance
5. the process of research translation across scientific fields and into practice
6. the formal properties and mechanisms of ideational change (network analysis, or holistic conceptions of scientific propositions and ideas)
7. developing methods for identifying the rediscovery of old ideas recast anew
8. investigating the process of scientific review
I am also heavily involved in research on social networks and social network theory development. Some of my work concerns relational dynamics and cognitive networks as represented in communication. This often concerns the communication of children (in their writings and speech in classrooms) and academic scholars. I am also co-editing a special issue in Social Networks on "network ecology", and I am a coauthor on a social network methods textbook coming out with Cambridge Press (Forthcoming, by Craig Rawlings, Jeff Smith, James Moody and Daniel McFarland).
Last, I am heavily involved in institutional efforts to develop computational social science, computational sociology, and education data science on Stanford's campus. -
Arnold Milstein
Professor of Medicine (General Medical Discipline)
Current Research and Scholarly InterestsDesign national demonstration of innovations in care delivery that provide more with less. Informed by research on AI-assisted clinical workflow, positive value outlier analysis and triggers of loss aversion bias among patients and clinicians.
Research on creation of a national index of health system productivity gain.
