Audrey
Tang
Digital Minister of Taiwan
Audrey is Taiwan's digital minister in charge of Social Innovation. She entered politics through Taiwan's 2014 Sunflower Student Movement demonstrations, appointed the youngest minister without portfolio in Taiwanese history. Tang led the open source g0v ("gov zero") project, built a vibrant community creating tools for civil society, with the call to "fork the government." With vTaiwan, she led a social platform for citizens to create digital petitions (5,000+ signatories are addressed by government leadership.) She has also worked on sharing economy software to facilitate free exchange well beyond ride-sharing and peer hotel applications. As a practice of "radical transparency," all of Tang's meetings are recorded and uploaded to a public website. Audrey is also known for revitalizing computer languages Perl and Haskell, and for the online spreadsheet system EtherCalc.
Chris
Bail
Duke University
Chris Bail is Professor of Sociology and Public Policy at Duke University, where he directs the Polarization Lab. He studies political tribalism, extremism, and social psychology using data from social media and tools from the emerging field of computational social science.
Marta Gonzalez
University of California,
Berkeley
Marta Gonzalez works in urban sciences, with a focus on the intersections of people with the built and the natural environment and their social networks. Her ultimate goal is to design urban solutions and to enable a caring development in the use of new technologies. She has developed new tools that impact transportation research and discovered novel approaches to model human mobility and the adoption of energy technologies. Statistical Physics of Complex Systems and Network Science founded her scientific approach, Spatial AI, digital traces, and Environmental data, keep her busy.
Rediet Abebe
University of California, Berkeley
Rediet Abebe is an Assistant Professor of Computer Science at the University of California, Berkeley and a Junior Fellow at the Harvard Society of Fellows. Her research is broadly in the fields of algorithms and artificial intelligence, with a focus on inequality and distributive justice concerns. She is serving on the Executive Committee of and was an inaugural Program Co-Chair for the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO '21). She also co-founded and co-organize the related MD4SG research initiative.
Tom
Griffiths
Princeton University
Tom Griffiths is the Henry R. Luce Professor of Information Technology, Consciousness and Culture, and director of the Computational Cognitive Science Lab at Princeton University.
His focus is on inductive problems, such as probabilistic reasoning, learning causal relationships, acquiring and using language, and inferring the structure of categories. He tries to analyze these aspects of human cognition by comparing human behavior to optimal or "rational" solutions to the underlying computational problems. For inductive problems, this usually means exploring how ideas from artificial intelligence, machine learning, and statistics (particularly Bayesian statistics) connect to human cognition. These interests have sometimes led him into other areas of research such asnonparametric Bayesian statistics and formal models of cultural evolution.
Lillian
Lee
Cornell University
Lillian Lee is a professor of computer science at Cornell University. Her research interests include natural language processing, information retrieval, and machine learning. She is the recipient of the inaugural Best Paper Award at HLT-NAACL 2004 (joint with Regina Barzilay), a citation in "Top Picks: Technology Research Advances of 2004" by Technology Research News (also joint with Regina Barzilay), and an Alfred P. Sloan Research Fellowship; and in 2013, she was named a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI). Her group's work has received several mentions in the popular press, including The New York Times, NPR's All Things Considered, and NBC's The Today Show.
Cristian Danescu Niculescu Mizil
Cornell University
Danescu-Niculescu-Mizil is an associate professor in the information science department at Cornell University. His research aims at developing computational methods that can lead to a better understanding of our conversational practices, supporting tools that can improve the way we communicate with each other. He is the recipient of several awards – including an NSF CAREER Award, the WWW 2013 Best Paper Award, a CSCW 2017 Best Paper Award, and two Google Faculty Research Awards – and his work has been featured in popular media outlets such as The Wall Street Journal, NBC's The Today Show, NPR and The New York Times.
Iyad
Rahwan
Max Planck Institute for Human Development
Iyad Rahwan is the managing director of the Max Planck Institute for Human Development in Berlin, where he founded and directs the Center for Humans & Machines. He is also an honorary professor of Electrical Engineering and Computer Science at the Technical University of Berlin. Until June 2020, he was an Associate Professor of Media Arts & Sciences at the Massachusetts Institute of Technology (MIT).
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His research is motivated by the following overarching question:
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How can science help us understand, anticipate, and shape major disruptions from Artificial Intelligence, the Web, and social media to the way we think, learn, work, play, and govern?
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Molly
Roberts
University of California,
San Diego
Margaret E. (Molly) Roberts is an associate professor of political science at UC San Diego. Her research interests lie in the intersection of political methodology and the politics of information, with a specific focus on methods of automated content analysis and the politics of censorship in China. Currently, she is working on a variety of projects that span censorship, propaganda, topic models and other methods of text analysis. Her work has appeared or is forthcoming in the American Journal of Political Science, American Political Science Review, and Political Analysis.
Ted
Underwood
University of Illinois Urbana-Champaign
Ted Underwood is a professor in the School of Information Sciences and also holds an appointment with the Department of English in the College of Liberal Arts and Sciences. After writing two books that describe eighteenth- and nineteenth-century literature using familiar critical methods, he turned to new opportunities created by large digital libraries. Since that time, his research has explored literary patterns that become visible across long timelines, when we consider hundreds or thousands of books at once. He recently used machine learning, for instance, to trace the consolidation of detective fiction and science fiction as distinct genres, and to describe the shifting assumptions about gender revealed in literary characterization from 1780 to the present.
Chenhao
Tan
University of Chicago
Chenhao Tan is an assistant professor at the Department of Computer Science at the University of Chicago. He is also affiliated with the Harris School of Public Policy. He directs the Chicago Human+AI lab. His main research interests include: human-centered machine learning, language and social dynamics, and multi-community engagement.
Anjali
Adukia
University of Chicago
Anjali Adukia is an assistant professor at the University of Chicago Harris School of Public Policy and the College and the director of the MiiE Lab (Messages, Identity, and Inclusion in Education). In her work, she is interested in understanding how to reduce inequalities such that children from historically disadvantaged backgrounds have equal opportunities to fully develop their potential. Her research is focused on understanding factors that motivate and shape behavior, preferences, attitudes, and educational decision-making, with a particular focus on early-life influences. She examines how the provision of basic needs—such as safety, health, justice, and representation—can increase school participation and improve child outcomes in developing contexts.
Laura
Nelson
University of British Columbia
Laura Nelson uses computational methods - principally text analysis, natural language processing, machine learning, and network analysis techniques - to study social movements, culture, gender, and organizations and institutions. Substantively, her research has examined processes around the formation of collective identities and social movement strategy in feminist and environmental movements, continuities between cycles of activism and the role of place in shaping social movement activity, intersectionality in women's movements and in the lived experiences during the 19th century in the U.S. South, gender inequality in startups and entrepreneurship, the translation of academic ideas to practice in the National Science Foundation's ADVANCE program (a program aimed at promoting women in STEM field in higher education), and gender inequality in emergency medicine departments.
Annie
Liang
Northwestern University
Annie Lang is an Assistant Professor of Economics (primary appointment) and the Karr Family Assistant Professor of Computer Science at Northwestern University.
Her research is in economic theory—in particular, learning and information—and the application of machine learning methods for model building and evaluation. Prior to joining Northwestern, she was an Assistant Professor of Economics at the University of Pennsylvania, and a postdoctoral researcher at Microsoft Research-New England.
Sendhil Mullainathan
University of Chicago
Sendhil Mullainathan is the Roman Family University Professor of Computation and Behavioral Science at Chicago Booth. His current research uses machine learning to understand complex problems in human behavior, social policy, and especially medicine, where computational techniques have the potential to uncover biomedical insights from large-scale health data. In addition to being a co-PI at the joint Berkeley-UChicago Laboratory for Systems Medicine, Sendhil is the cofounder of the computational medicine initiative, Nightingale. He's also a co-founder of Pique, a an app that changes how people read books and learn; and Dandelion, a company that catalyzes AI in healthcare.
Rochelle
Terman
University of Chicago
Rochelle Terman is an assistant professor in the Department of Political Science at the University of Chicago. She studies international norms, gender, and advocacy, with a focus on the Muslim world. Her current book project, Backlash: Defiance, Human Rights, and the Politics of Shame, investigates counter-productive consequences of global "naming and shaming" campaigns. The manuscript is based on her dissertation, which won the 2017 Merze Tate Award for the best dissertation in international relations, law, and politics from the American Political Science Association. Terman is also interested is computational social science, and teaches courses on machine learning, text analysis, and programming.
James
Evans
University of Chicago
James Evans is Professor of Sociology, Director of Knowledge Lab, and Faculty Director of Computational Social Science at the University of Chicago. His research uses large-scale data, machine learning and generative models to understand how collectives think and what they know. This involves inquiry into the emergence of ideas, shared patterns of reasoning, and processes of attention, communication, agreement, and certainty. Thinking and knowing collectives like science, Wikipedia or the Web involve complex networks of diverse human and machine intelligences, collaborating and competing to achieve overlapping aims. Evans' work connects the interaction of these agents with the knowledge they produce and its value for themselves and the system.
Luis
Bettencourt
University of Chicago
Luís M. A. Bettencourt is the Inaugural Director the Mansueto Institute for Urban Innovation at the University of Chicago and Professor of Ecology and Evolution at the College. He is also Associate Faculty of the Department of Sociology and External Professor at the Santa Fe Institute. He conducts interdisciplinary research on complex adaptive systems in biology and society and leads research and education programs in Urban Science and Sustainable Development. His research focuses on the identification, modeling and theory of the systemic processes and properties that create and sustain cities.
Fengli
Xu
University of Chicago
Fengli Xu is a Postdoctoral Fellow at Mansueto Institute for Urban Innovation and Knowledge Lab at University of Chicago. His research interests lie in the interdisciplinary area of data science, computational social science and complex network, aiming to develop scientific methods and artificial intelligence tools to address the long-standing puzzles in complex networks arise from human behavior and social interactions. His research aims to tackle the challenges of principally integrating data science techniques into social science and complex network research, and fully exploit the opportunities offered by recent data explosion.