Institute for Human-Centered Artificial Intelligence (HAI)
Showing 91-100 of 188 Results
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Jennifer King
HAI Privacy and Data Policy Fellow
Current Research and Scholarly InterestsI research information privacy from the user's perspective (HCI) across multiple domains, including: online commercial contexts, IoT/Ubicomp, human genetics. I conduct both theoretical and applied privacy research, with a focus on the impacts of law and policy on privacy. My dissertation research explored the effects of social structures (such as power differentials) on individuals' decisions to disclose personal information in commercial contexts.
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Brian Knutson
Professor of Psychology
Current Research and Scholarly InterestsMy lab and I seek to elucidate the neural basis of emotion (affective neuroscience), and explore implications for decision-making (neuroeconomics) and psychopathology (neurophenomics).
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Mykel Kochenderfer
Associate Professor of Aeronautics and Astronautics and, by courtesy, of Computer Science
BioMykel Kochenderfer is Associate Professor of Aeronautics and Astronautics at Stanford University. Prior to joining the faculty, he was at MIT Lincoln Laboratory where he worked on airspace modeling and aircraft collision avoidance, with his early work leading to the establishment of the ACAS X program. He received a Ph.D. from the University of Edinburgh and B.S. and M.S. degrees in computer science from Stanford University. Prof. Kochenderfer is the director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and other aerospace applications where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations. He is an author of "Decision Making under Uncertainty: Theory and Application" (2015), "Algorithms for Optimization" (2019), and "Algorithms for Decision Making" (2022), all from MIT Press. He is a third generation pilot.
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Michal Kosinski
Associate Professor of Organizational Behavior at the Graduate School of Business
BioPlease visit: http://www.michalkosinski.com/
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Anshul Kundaje
Associate Professor of Genetics
Current Research and Scholarly InterestsWe develop statistical and machine learning frameworks to learn predictive, dynamic and causal models of gene regulation from heterogeneous functional genomics data.
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Monica Lam
Kleiner Perkins, Mayfield, Sequoia Capital Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
BioDr. Monica Lam is a Professor in the Computer Science Department at Stanford University, and the Faculty Director of the Stanford Open Virtual Assistant Laboratory. Dr. Monica Lam obtained her BS degree in computer science from University of British Columbia, and her PhD degree in computer science from Carnegie Mellon University in 1987. She joined Stanford in 1988.
Professor Lam's current research is on conversational virtual assistants with an emphasis on privacy protection. Her research uses deep learning to map task-oriented natural language dialogues into formal semantics, represented by a new executable programming language called ThingTalk. Her Almond virtual assistant, trained on open knowledge graphs and IoT API standards, can be easily customized to perform new tasks. She is leading an Open Virtual Assistant Initiative to create the largest, open, crowdsourced language semantics model to promote open access in all languages. Her decentralized Almond virtual assistant that supports fine-grain sharing with privacy has received Popular Science's Best of What's New Award in Security in 2019.
Prof. Lam is also an expert in compilers for high-performance machines. Her pioneering work of affine partitioning provides a unifying theory to the field of loop transformations for parallelism and locality. Her software pipelining algorithm is used in commercial systems for instruction level parallelism. Her research team created the first, widely adopted research compiler, SUIF. She is a co-author of the classic compiler textbook, popularly known as the “dragon book”. She was on the founding team of Tensilica, now a part of Cadence.
Dr. Lam is a Member of the National Academy of Engineering and an Association of Computing Machinery (ACM) Fellow. -
Eric Lambin
George and Setsuko Ishiyama Provostial Professor and Senior Fellow at the Woods Institute for the Environment
Current Research and Scholarly InterestsI study human-environment interactions in land systems by linking remote sensing, GIS and socio-economic data. I aim at better understanding causes and impacts of changes in tropical forests, drylands, and farming systems. I currently focus on land use transitions – i.e., the shift from deforestation (or land degradation) to reforestation (or land sparing for nature), – the influence of globalization on land use decisions, and the interactions between public and private governance of land use.
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James Landay
Denning Co-Director (Acting) of Stanford HAI, Anand Rajaraman and Venky Harinarayan Professor and Senior Fellow at the Stanford Institute for HAI
Current Research and Scholarly InterestsLanday's current research interests include Technology to Support Behavior Change (especially for health and sustainability), Demonstrational User Interfaces, Mobile & Ubiquitous Computing, Cross-Cultural Interface Design, Human-Centered AI, and User Interface Design Tools. He has developed tools, techniques, and a top professional book on Web Interface Design.
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Curtis Langlotz
Professor of Radiology (Thoracic Imaging), of Biomedical Informatics Research, of Biomedical Data Science and Senior Fellow at the Stanford Institute for HAI
Current Research and Scholarly InterestsI am interested in the use of deep neural networks and other machine learning technologies to help radiologists detect disease and eliminate diagnostic errors. My laboratory is developing deep neural networks that detect and classify disease on medical images. We also develop natural language processing methods that use the narrative radiology report to create large annotated image training sets for supervised machine learning experiments.
