Institute for Human-Centered Artificial Intelligence (HAI)
Showing 61-80 of 273 Results
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Stefano Ermon
Associate Professor of Computer Science and Senior Fellow at the Woods Institute for the Environment
BioI am an Assistant Professor in the Department of Computer Science at Stanford University, where I am affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment.
My research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability. -
Loredana Fattorini
Research Associate, Institute for Human-Centered Artificial Intelligence (HAI)
BioLoredana is a Research Associate at Stanford's Institute for Human-Centered Artificial Intelligence (HAI), where she is a member of the AI Index team. She is primarily involved in preparing the AI Index annual report and developing the Global AI Vibrancy tool. Using data analysis techniques, Loredana helps make complex information regarding the rapidly evolving AI landscape more accessible and understandable for policymakers, industry leaders, researchers, and the general public.
With a Ph.D. in Applied Economics from the IMT School for Advanced Studies Lucca, Italy, Loredana has conducted empirical research in the fields of Industrial Organization and International Trade. She also holds both Bachelor's and Master's degrees with honors in Economics from the University of Pisa and Scuola Superiore Sant'Anna, Italy.
Before joining HAI, Loredana worked as a Visiting Researcher at the Vienna Institute for International Economic Studies (WiiW). Her research focused on the competitiveness of firms in Europe, as part of a project funded by the Austrian National Bank. Additionally, she worked as a Data Analyst for a fast-growing eCommerce startup that managed online sales for Europe's largest food retail cooperative. -
Chelsea Finn
Assistant Professor of Computer Science and of Electrical Engineering
BioChelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University, and the William George and Ida Mary Hoover Faculty Fellow. Professor Finn's research interests lie in the ability to enable robots and other agents to develop broadly intelligent behavior through learning and interaction. Her work lies at the intersection of machine learning and robotic control, including topics such as end-to-end learning of visual perception and robotic manipulation skills, deep reinforcement learning of general skills from autonomously collected experience, and meta-learning algorithms that can enable fast learning of new concepts and behaviors. Professor Finn received her Bachelors degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley. Her research has been recognized through the ACM doctoral dissertation award, an NSF graduate fellowship, a Facebook fellowship, the C.V. Ramamoorthy Distinguished Research Award, and the MIT Technology Review 35 under 35 Award, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg. Throughout her career, she has sought to increase the representation of underrepresented minorities within CS and AI by developing an AI outreach camp at Berkeley for underprivileged high school students, a mentoring program for underrepresented undergraduates across three universities, and leading efforts within the WiML and Berkeley WiCSE communities of women researchers.
Website: https://ai.stanford.edu/~cbfinn -
James Fishkin
Janet M. Peck Professor of International Communication, Senior Fellow at the Freeman Spogli Institute for International Studies and Professor, by courtesy, of Political Science
BioJames S. Fishkin holds the Janet M. Peck Chair in International Communication at Stanford University where he is Professor of Communication, Professor of Political Science (by courtesy) and Director of the Center for Deliberative Democracy.
He received his B.A. from Yale in 1970 and holds a Ph.D. in Political Science from Yale as well as a second Ph.D. in Philosophy from Cambridge.
He is the author of Democracy When the People Are Thinking (Oxford 2018), When the People Speak (Oxford 2009), Deliberation Day (Yale 2004 with Bruce Ackerman) and Democracy and Deliberation (Yale 1991).
He is best known for developing Deliberative Polling® – a practice of public consultation that employs random samples of the citizenry to explore how opinions would change if they were more informed. His work on deliberative democracy has stimulated more than 100 Deliberative Polls in 28 countries around the world. It has been used to help governments and policy makers make important decisions in Texas, China, Mongolia, Japan, Macau, South Korea, Bulgaria, Brazil, Uganda and other countries around the world.
He is a Fellow of the American Academy of Arts and Sciences, a Guggenheim Fellow, a Fellow of the Center for Advanced Study in the Behavioral Sciences at Stanford, and a Visiting Fellow Commoner at Trinity College, Cambridge. -
Sean Follmer
Associate Professor of Mechanical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsHuman Computer Interaction, Haptics, Robotics, Human Centered Design
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Michael Frank
Benjamin Scott Crocker Professor of Human Biology and Professor, by courtesy, of Linguistics
Current Research and Scholarly InterestsHow do we learn to communicate using language? I study children's language learning and how it interacts with their developing understanding of the social world. I use behavioral experiments, computational tools, and novel measurement methods like large-scale web-based studies, eye-tracking, and head-mounted cameras.
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Takako Fujioka
Associate Professor of Music
BioResearch topics include neural oscillations for auditory perception, auditory-motor coupling, brain plasticity in development and aging, and recovery from stroke with music-supported therapy.
Her post-doctoral and research-associate work at Rotman Research Institute in Toronto was supported by awards from the Canadian Institutes of Health Research. Her research continues to explore the biological nature of human musical ability by examining brain activities with non-invasive human neurophysiological measures such as magnetoencephalography (MEG) and electroencephalography (EEG). -
Francis Fukuyama
Olivier & Nomellini Senior Fellow in International Studies at the Freeman Spogli Institute for International Studies and Professor, by courtesy, of Political Science
Current Research and Scholarly InterestsDeveloping nations; governance; international political economy; nation-building and democratization; strategic and security issues
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Surya Ganguli
Associate Professor of Applied Physics, Senior Fellow at the Stanford Institute for HAI and Associate Professor, by courtesy, of Neurobiology and of Electrical Engineering
Current Research and Scholarly InterestsTheoretical / computational neuroscience
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Justin Gardner
Associate Professor of Psychology
Current Research and Scholarly InterestsHow does neural activity in the human cortex create our sense of visual perception? We use a combination of functional magnetic resonance imaging, computational modeling and analysis, and psychophysical measurements to link human perception to cortical brain activity.
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Michael Genesereth
Associate Professor of Computer Science and, by courtesy, of Law
BioGenesereth is most known for his work on Computational Logic and applications of that work in Enterprise Management, Computational Law, and General Game Playing. He is one of the founders of Teknowledge, CommerceNet, Mergent Systems, and Symbium. Genesereth is the director of the Logic Group at Stanford and the founder and research director of CodeX - the Stanford Center for Legal Informatics.
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Michael Gensheimer
Clinical Associate Professor, Radiation Oncology - Radiation Therapy
Current Research and Scholarly InterestsIn addition to my clinical research in head and neck and lung cancer, I work on the application of computer science and machine learning to cancer research. I develop tools for analyzing large datasets to improve outcomes and safety of cancer treatment. I developed a machine learning prognostic model using data from around 13,000 patients with metastatic cancer which performs better than traditional models and physicians [PubMed ID 33313792]. We recently completed a prospective randomized study in thousands of patients in which the model was used to help improve advance care planning conversations.
I also work on the methods underpinning observational and predictive modeling research. My open source nnet-survival software that allows use of neural networks for survival modeling has been used by researchers internationally. In collaboration with the Stanford Research Informatics Center, I examined how electronic medical record (EMR) survival outcome data compares to gold-standard data from a cancer registry [PubMed ID 35802836]. The EMR data captured less than 50% of deaths, a finding that affects many studies being published that use EMR outcomes data.