Current Members

Solon Barocas

Adjunct Assistant Professor; Principal Researcher; AIPP Project PI
Department of Information Science, Cornell University; Microsoft Research


Solon Barocas is a Principal Researcher in the New York City lab of Microsoft Research and an Adjunct Assistant Professor in the Department of Information Science at Cornell University. He is also a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard University.




Jon Kleinberg

Professor; AIPP Project PI
Departments of Computer Science and Information Science, Cornell University


Jon Kleinberg is the Tisch University Professor in the Departments of Computer Science and Information Science at Cornell University. His research focuses on the interaction of algorithms and networks, the roles they play in large-scale social and information systems, and their broader societal implications. He is a member of the National Academy of Sciences and National Academy of Engineering, and the recipient of MacArthur, Packard, Simons, Sloan, and Vannevar Bush research fellowships.




Karen Levy

Assistant Professor; AIPP Project PI
Department of Information Science, Cornell University; Associated Faculty, Cornell Law School


Karen Levy is an assistant professor in the Department of Information Science at Cornell University and associate faculty at Cornell Law School. Her research examines the legal, social, and ethical dimensions of data-intensive technologies. Levy holds a Ph.D. in Sociology from Princeton University and a J.D. from Indiana University Maurer School of Law.




Helen Nissenbaum

Professor; AIPP Project PI
Department of Information Science, Cornell Tech


Helen Nissenbaum is a professor in the Department of Information Science at Cornell Tech. Her research takes an ethical perspective on policy, law, science, and engineering relating to information technology, computing, digital media and data science. Topics have included privacy, trust, accountability, security, and values in technology design. She is the recipient of the 2014 Barwise Prize of the American Philosophical Association.




Sarah Dean

Assistant Professor
Department of Computer Science, Cornell University


Sarah Dean is an Assistant Professor in the Computer Science Department at Cornell. She is interested in the interplay between optimization, machine learning, and dynamics. Her research focuses on understanding the fundamentals of data-driven control and decision-making, inspired by applications ranging from robotics to recommendation systems. She received a PhD in Electrical Engineering and Computer Science from UC Berkeley in 2021.




Hoda Heidari

Assistant Professor
Machine Learning Department, Carnegie Mellon University


Hoda Heidari is currently an Assistant Professor in Machine Learning and Societal Computing at the School of Computer Science, Carnegie Mellon University. Before joining Carnegie Mellon, she was a postdoctoral associate at AIPP. Her research is broadly concerned with the societal and economic aspects of AI. In particular, her recent work has sought to define and mitigate issues of unfairness and inexplicability through ML, utilizing tools and ideas from CS, economics, and political philosophy. Her work in collaboration with AIPP has won a best-paper award at the ACM FAccT Conference and an exemplary track award at the ACM Conference on Economics and Computation (EC). She has organized several academic events on topics related to responsible and trustworthy AI, including a tutorial at the Web Conference (WWW), and several workshops at NeurIPS and ICLR.




Stephen Hilgartner

Professor
Department of Science & Technology Studies, Cornell University


Stephen Hilgartner is Professor of Science & Technology Studies at Cornell University. His research examines the social dimensions and politics of contemporary and emerging science and technology, a theme he has addressed in studies of scientific advice, risk disputes, and control over knowledge and information. Recent books include: Reordering Life: Knowledge and Control in the Genomics Revolution and Science & Democracy: Making Knowledge and Making Power in the Biosciences and Beyond. Relevant work includes research on knowledge-control regimes and a current study examining how those building machine learning systems conceptualize ethical and policy issues.




Emma Pierson

Assistant Professor
Department of Computer Science, Cornell Tech


Emma Pierson is an assistant professor of computer science at the Jacobs Technion-Cornell Institute at Cornell Tech and the Technion, and a computer science field member at Cornell University. She develops data science and machine learning methods to study inequality and healthcare. Her work has been recognized by a Rhodes Scholarship, Hertz Fellowship, Rising Star in EECS, MIT Technology Review 35 Innovators Under 35, and Forbes 30 Under 30 in Science. She has written for The New York Times, FiveThirtyEight, The Atlantic, The Washington Post, Wired, and various other publications.




Manish Raghavan

Postdoctoral Fellow; Incoming Assistant Professor
Harvard University; MIT EECS and the Sloan School of Management


Manish is a recent Cornell PhD graduate studying the societal implications of algorithmic decision-making. His research draws upon connections to economics, law, and policy to better understand the impacts that computation has on society.




Gili Vidan

Assistant Professor
Department of Information Science, Cornell University


Gili Vidan is an assistant professor in the Department of Information Science at the Cornell Bowers College of Computing and Information Science. She is a historian of information technology and Science and Technology Studies (STS) researcher. Her work examines how trust is established both in digital technologies and through digital mediation and how notions of authenticity, knowability, and good governance are implicated in the making of new digital objects. Her book project, “Technologies of Trust,” traces technical attempts to solve the problems of trust and authentication in late 20th- and early 21st-century US.




Baobao Zhang

Assistant Professor
Maxwell School of Citizenship and Public Affairs, Syracuse University


Baobao is currently the Klarman Postdoctoral Fellow in the Cornell Society of Fellows. At Cornell, she is based in the Department of Government; she has a secondary affiliation with the Department of Information Science. In Fall 2021, she will start as an assistant professor of Political Science at the Maxwell School of Citizenship and Public Affairs at Syracuse University. She is also a research affiliate with the Centre for the Governance of AI at the University of Oxford and a CIFAR Azrieli Global Scholar. Her current research focuses on trust in digital technology and the governance of artificial intelligence (AI).




Malte Ziewitz

Assistant Professor
Department of Science & Technology Studies, Cornell University


Malte Ziewitz is Assistant Professor at the Department of Science & Technology Studies at Cornell University. An ethnographer and sociologist, he studies the changing role of governance and regulation in, of, and through digitally networked environments. His recent work looks at the use of patient feedback in the British hospitals, the search engine optimization industry, and people’s attempts to repair a broken credit score. At Cornell, he directs the Digital Due Process Clinic, a clinical research program that helps ordinary people to cope with, understand, and challenge automated scoring systems.




Lydia Liu

Incoming Postdoctoral Associate
Department of Computer Science, Cornell University


Lydia T. Liu is currently a PhD candidate in the EECS at University of California, Berkeley, advised by Moritz Hardt and Michael I. Jordan. Lydia’s research examines the mathematical foundations of machine learning and algorithmic decision-making, with a focus on societal impact and human welfare. Her current work also approaches questions of algorithmic impact from an integrated and interdisciplinary perspective. She is the recipient of a Best Paper Award at the International Conference on Machine Learning, a Microsoft Ada Lovelace Fellowship, and an Open Philanthropy AI Fellowship.




Katy Blumer

PhD Student
Department of Computer Science, Cornell University


Katy Blumer is a PhD student in the Department of Computer Science at Cornell University, advised by Jon Kleinberg. She is interested generally in machine learning understanding. Before Cornell, Katy worked on machine learning for retinal imaging at Google. She has a bachelor’s degree in physics from NYU Abu Dhabi.




Madiha Zahrah Choksi

PhD Student
Department of Information Science, Cornell Tech


Madiha’s research focuses on the intersection of technology, law, and privacy. More specifically, the sociological implications of mass-surveillance on user privacy, trust, and agency, and the interconnected relationship between privacy and human rights. Madiha completed a Master of Information from the University of Toronto and a Master of Arts from Columbia University.




A. Feder Cooper

PhD Student
Department of Computer Science, Cornell University


A. Feder Cooper is a Ph.D. student in Computer Science, researching how to build accountable, robust distributed machine learning systems with theoretical guarantees. Cooper also investigates the legal and social dimensions of this work.




Fernando Delgado

PhD Student
Department of Information Science, Cornell University


Fernando A. Delgado is a Ph.D. student in the College of Computing and Information Science at Cornell University. Prior to commencing his doctoral studies, Fernando worked at H5, a pioneering firm in the field of legal technology, designing and deploying algorithmic systems for content classification and evidentiary fact-finding in civil litigation and investigations. His current academic research focuses on the design, evaluation, and governance of AI systems in the law. His doctoral research is supported by the McNair Scholars Program, the MacArthur Foundation program on Technology in the Public Interest, and the Russell Sage Foundation initiative on Computational Social Science.




Kate Donahue

PhD Student
Department of Computer Science, Cornell University


Kate Donahue is a 4th year CS PhD candidate. She generally works in theory, especially questions around fairness in machine learning, and strategic behavior under uncertainty, and is extremely fortunate to be advised by Jon Kleinberg.




Margot Hanley

PhD Student
Department of Information Science, Cornell Tech


Margot Hanley is a Ph.D. student in Information Science at Cornell Tech, as well as a Doctoral Fellow at the Digital Life Initiative and she is advised by Helen Nissenbaum. Her research is motivated by normative questions surrounding the design, development, and use of computational systems, especially those which use machine learning and other data-driven techniques, and how they may threaten or limit human autonomy, agency, and expression. Margot holds a B.A. from Oberlin College in Economics and an M.A from Columbia University in Sociology.




Kowe Kadoma

PhD Student
Department of Information Science, Cornell University


Kowe is an Information Science Ph.D. student interested in the intersection of technology, law, and social science. She is particularly passionate about the spread of misinformation in historically marginalized communities and the social implications of bias in machine learning.




Benjamin Laufer

PhD Student
Department of Information Science, Cornell Tech


Ben is a PhD student in the Department of Information Science at Cornell University. He is interested in leveraging computational methods to evaluate decision-making processes in the public realm. Prior to joining Cornell, Ben worked as a data scientist at Lime, where he applied machine learning to urban mobility decisions. He graduated from Princeton Unviersity, where he studied Operations Research and Financial Engineering.




Michela Meister

PhD Student
Department of Computer Science, Cornell University


Michela Meister is a PhD student in the Department of Computer Science at Cornell University, advised by Jon Kleinberg. Her main interests are in algorithms, network science, and machine learning. Her work is supported by an NDSEG fellowship.




Pegah Moradi

PhD Student
Department of Information Science, Cornell University


Pegah is a PhD student in the Department of Information Science at Cornell University. Her research interests lie in technology and labor, with a focus on how AI-driven automation affects workers. Her work is supported by an NSF GRFP award.




Aspen Russell

PhD Student
Department of Information Science, Cornell University


Aspen studies the history and impact of bias in online spaces. Her work on understanding user intention, and its impact, are used to inform tech innovation and policy aimed at the mitigation of bias. Aspen’s research is founded on an intersectional framework primarily using surveys, interviews, and content analysis. Her goal is to bring issues of inequity to the forefront for tangible change online, while also engaging allies to be active change makers in their communities.




Katherine Van Koevering

PhD Student
Department of Computer Science, Cornell University


Katherine is a fourth year PhD candidate in computer science at Cornell University where she works with Jon Kleinberg and Austin Benson. Her interests span across the spectrum of graph and network science from theoretical to applied with particular interest around random graphs and online communities. She graduated from the University of Washington with bachelor degrees in Computer Science and Statistics in 2018.




Briana Vecchione

PhD Student
Department of Information Science, Cornell University


Briana is a PhD student in Information Science at Cornell University, advised by Solon Barocas and Karen Levy. Her research addresses issues of measurement and evaluation in sociotechnical systems, with particular attention to systemic issues of algorithmic bias and equity in public policy and human-centered domains. Prior to Cornell, Briana worked in civic technology at Microsoft. Briana’s undergraduate background is in computer science and mathematics. Her work is supported by a Facebook Fellowship and Google Women Techmakers scholarship.




Alumni

Rediet Abebe

Lauren Kilgour

Samir Passi

David Robinson