Institute for Human-Centered Artificial Intelligence (HAI)


Showing 1-20 of 20 Results

  • Christopher Manning

    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.

  • David J. Maron

    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.

  • Nestor Maslej

    Nestor Maslej

    Research Manager, Institute for Human-Centered Artificial Intelligence (HAI)

    BioNestor Maslej is a Research Manager at Stanford’s Institute for Human-Centered Artificial Intelligence (HAI). In this position, he manages the AI Index and Global AI Vibrancy Tool. In developing tools that track the advancement of AI, Nestor hopes to make the AI space more accessible to policymakers, business leaders and the lay public.

    Nestor’s work on AI, namely the AI Index, has been cited in newspapers across the globe including: The New York Times, Financial Times, Bloomberg, The Washington Post, The Guardian, Vox, Al Jazeera, Fortune, Forbes, San Francisco Chronicle, Politico, The Register, Der Spiegel, The Verge, IEEE Spectrum, VentureBeat and more. Nestor’s publications have likewise informed AI policymaking worldwide, having been referenced by policymakers in countries such as the United States, Canada, Germany, the United Kingdom, China, Japan as well as Korea.

    Nestor also speaks frequently about trends in AI, having briefed high-level US policymakers, testified in front of both the Canadian and Italian parliaments and presented to CEOs from a plethora of industries. Nestor is also a fellow at the Centre for International Governance Innovation (CIGI) where he regularly writes opinion pieces on developments in AI. In his spare time, when he is not musing about AI, Nestor likes to hike, ski, cook and read.

    Prior to joining HAI, Nestor worked in Toronto as an analyst in several startups. He graduated from the University of Oxford in 2021 with an MPhil in Comparative Government (Distinction), and Harvard College in 2017 with an A.B. in Social Studies (Magna Cum Laude, PBK).

  • Jay McClelland

    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 06/30/2024

    Current 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.

  • Daniel McFarland

    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.

  • Caroline Meinhardt

    Caroline Meinhardt

    Policy Research Manager, Institute for Human-Centered Artificial Intelligence (HAI)

    BioCaroline Meinhardt is the policy research manager at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), where she develops and oversees policy research initiatives. She is passionate about harnessing AI governance research to inform policies that ensure the safe and responsible development of AI around the world—with a focus on research on the privacy implications of AI development, the implementation challenges of AI regulation, and the governance of large-scale AI models. Prior to joining HAI, Caroline worked as a China-focused consultant and analyst, managing and delivering in-depth research and strategic advice regarding China’s development and regulation of emerging technologies including AI. She holds a Master's in International Policy from Stanford University and a Bachelor's in Chinese Studies from the University of Cambridge.

  • Arnold Milstein

    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.

  • William Mitch

    William Mitch

    Professor of Civil and Environmental Engineering
    On Leave from 04/01/2024 To 06/30/2024

    BioBill Mitch received a B.A. in Anthropology (Archaeology) from Harvard University in 1993. During his studies, he excavated at Mayan sites in Belize and surveyed sites dating from 2,000 B.C. in Louisiana. He switched fields by receiving a M.S. degree in Civil and Environmental Engineering at UC Berkeley. He worked for 3 years in environmental consulting, receiving his P.E. license in Civil Engineering in California. Returning to UC Berkeley in 2000, he received his PhD in Civil and Environmental Engineering in 2003. He moved to Yale as an assistant professor after graduation. His dissertation received the AEESP Outstanding Doctoral Dissertation Award in 2004. At Yale, he serves as the faculty advisor for the Yale Student Chapter of Engineers without Borders. In 2007, he won a NSF CAREER Award. He moved to Stanford University as an associate professor in 2013.

    Employing a fundamental understanding of organic chemical reaction pathways, his research explores links between public health, engineering and sustainability. Topics of current interest include:

    Public Health and Emerging Carcinogens: Recent changes to the disinfection processes fundamental to drinking and recreational water safety are creating a host of highly toxic byproducts linked to bladder cancer. We seek to understand how these compounds form so we can adjust the disinfection process to prevent their formation.

    Global Warming and Oceanography: Oceanic dissolved organic matter is an important global carbon component, and has important impacts on the net flux of CO2 between the ocean and atmosphere. We seek to understand some of the important abiotic chemical reaction pathways responsible for carbon turnover.

    Sustainability and Persistent Organic Pollutants (POPs): While PCBs have been banned in the US, we continue to produce a host of structurally similar chemicals. We seem to understand important chemical pathways responsible for POP destruction in the environment, so we can design less persistent and problematic chemicals in the future.

    Engineering for Sustainable Wastewater Recycling: The shortage of clean water represents a critical challenge for the next century, and has necessitated the recycling of wastewater. We seek to understand ways of engineer this process in ways to minimize harmful byproduct formation.

    Carbon Sequestration: We are evaluating the formation of nitrosamine and nitraminecarcinogens from amine-based carbon capture, as well as techniques to destroy any of these byproducts that form.

  • John Mitchell

    John Mitchell

    Mary and Gordon Crary Family Professor in the School of Engineering, and Professor, by courtesy, of Electrical Engineering and of Education

    Current Research and Scholarly InterestsProgramming languages, computer security and privacy, blockchain, machine learning, and technology for education

  • Benoit Monin

    Benoit Monin

    Bowen H. and Janice Arthur McCoy Professor of Leadership Values and Professor of Psychology

    Current Research and Scholarly InterestsMy research deals with how people address threats to the self in interpersonal situations: How they avoid feeling prejudiced, how they construe other people's behavior to make to their own look good, how they deal with dissonance, how they affirm a threatened identity, how they resent the goodness of others when it makes them look bad, etc. I study these issues in the context of social norms, the self, and morality, broadly defined.

  • Erin Mordecai

    Erin Mordecai

    Associate Professor of Biology and Senior Fellow at the Woods Institute for the Environment

    Current Research and Scholarly InterestsOur research focuses on the ecology of infectious disease. We are interested in how climate, species interactions, and global change drive infectious disease dynamics in humans and natural ecosystems. This research combines mathematical modeling and empirical work. Our main study systems include vector-borne diseases in humans and fungal pathogens in California grasses.

  • Elizabeth Mormino

    Elizabeth Mormino

    Assistant Professor (Research) of Neurology (Neurology Research Faculty)

    BioDr. Beth Mormino completed a PhD in Neuroscience at UC Berkeley in the laboratory of Dr. William Jagust, where she performed some of the initial studies applying Amyloid PET with the tracer PIB to clinically normal older individuals. This initial work provided evidence that the pathophysiological processes of Alzheimer’s disease begin years before clinical symptoms and are associated with subtle changes to brain regions critical for memory. During her postdoctoral fellowship with Drs. Reisa Sperling and Keith Johnson at Massachusetts General Hospital she used multimodal imaging techniques to understand longitudinal cognitive changes among individuals classified as preclinical AD. In 2017, Dr. Mormino joined the faculty at Stanford University in the department of Neurology and Neurological Sciences. Her research program focuses on combining imaging and genetics to predict cognitive trajectories over time, and the integration of novel PET scans to better understand human aging and neurodegenerative diseases.

  • Mark Musen

    Mark Musen

    Stanford Medicine Professor of Biomedical Informatics Research, Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science

    Current Research and Scholarly InterestsModern science requires that experimental data—and descriptions of the methods used to generate and analyze the data—are available online. Our laboratory studies methods for creating comprehensive, machine-actionable descriptions both of data and of experiments that can be processed by other scientists and by computers. We are also working to "clean up" legacy data and metadata to improve adherence to standards and to facilitate open science broadly.