Keynotes

We are excited to have enlisted the following distinguished speakers to present at IC2S2. Look forward to their introductions in the weeks leading up to the conference!

UTC+2WednesdayThursdayFridaySaturday
09:30Deborah Lupton
14:30Meeyoung ChaDavid GarciaRobert WestSune Lehmann
15:10Thomas GrundSilke AdamFrank TakesYong Yeol Ahn
15:50Brooke Foucault WellesChristian SandvigMargaret HuFrauke Kreuter


Frauke Kreuter
University of Maryland & LMU Munich
Maryland Population Research Center

Professor Frauke Kreuter Professor of Statistics and Data Science at the Ludwig-Maximilians-University of Munich (Germany) and co-director of Data Science Centers at the University of Maryland (USA) and Mannheim (Germany). She is an elected fellow of the American Statistical Association and the 2020 recipient of the Warren Mitofsky Innovators Award of the American Association for Public Opinion Research. In addition to her academic work Dr. Kreuter is the Founder of the International Program for Survey and Data Science, developed in response to the increasing demand from researchers and practitioners for the appropriate methods and right tools to face a changing data environment; Co-Founder of the Coleridge Initiative, whose goal is to accelerate data-driven research and policy around human beings and their interactions for program management, policy development, and scholarly purposes by enabling efficient, effective, and secure access to sensitive data about society and the economy; and Co-Founder of the German language podcast Dig Deep.

EPJ Data Science Cover
EPJ Data Science Keynote

Silke Adam
University of Berne
Institute of Communications and Media Studies

Silke Adam is professor of political communication at the University of Bern (CH). Her research focuses on how digitalization changes political communication processes. She thereby has studied hyperlink networks in the realm of climate politics and is currently analyzing how political attitudes and (online) information consumption are related combining survey and tracking research. She has published among others in New Media & Society, Social Networks, Communication Methods and Measures, PLoS ONE, International Journal of Press/ Politics, International Journal of Communication and European Union Politics.


Yong Yeol Ahn
Indiana University Bloomington
Luddy School of Informatics, Computing, and Engineering

His research focuses on complex social and biological systems by developing and applying network science and machine learning methods to a wide range of domains, including large-scale social phenomena, health, inequality, neuroscience, culture, and science of science.


Meeyoung Cha
Institute for Basic Science (IBS)
Korea Advanced Institute of Science and Technology (KAIST)
School of Computing

Meeyoung Cha is an associate professor at the Korea Advanced Institute of Science and Technology (KAIST) in South Korea. Her research is on data science with an emphasis on modeling socially relevant information propagation processes. Her work on misinformation, poverty mapping, fraud detection, and long-tail content has gained more than 16,000 citations. Meeyoung has worked at Facebook’s Data Science Team as a Visiting Professor and is a recipient of the Korean Young Information Scientist Award and AAAI ICWSM Test of Time Award. She is currently jointly affiliated as a Chief Investigator at the Institute for Basic Science (IBS) in Korea.


Brooke Foucault Welles
Northwestern University
College of Arts, Media and Design

Brooke Foucault Welles is an Associate Professor in the Department of Communication Studies and a core faculty member of the Network Science Institute at Northeastern University. Combining the methods of computational social science and network science with the theories of communication studies, Foucault Welles studies how online communication networks enable and constrain behavior, with particular emphasis on how these networks enable the pursuit of individual, team, and collective goals.


David Garcia Beccera
Graz University of Technology and Complexity Science Hub Vienna

David Garcia is Professor for Computational Behavioral and Social Sciences at the Graz University of Technology, where he leads the Computational Social Science Lab. He is also faculty member at the Complexity Science Hub Vienna and group leader at the Medical University of Vienna.  David Garcia’s work aims to understand human behavior and emergent technological phenomena in the digital society. His research applies computational methods and digital trace data to study emotions, online polarization, inequality, and social privacy issues. He publishes his work at the intersection between disciplines in journals including Psychological Science, EPJ Data Science, Science Advances, and PNAS.  David is coordinating the curriculum of the upcoming Master’s Programme in Computational Social Systems that is planned to start at the Graz University of Technology and the University of Graz from October 2021.


Thomas Grund
University College Dublin
School of Sociology

Thomas Grund is associate professor of Sociology at University College Dublin. His research aims to understand social facts (e.g. social networks, crime, social movements, segregation, cooperation) not merely by relating them to other social facts, but rather by detailing the pathways through which they are brought about. He is interested in three main aspects in this regard: (1) social structure limits individuals’ view of the world; (2) embeddedment in social context affects individuals’ behavior and relational choices; and (3) combined relational patterns lead to broader macro-level outcomes. 


Margret Hu
The Pennsylvania State University
PennState Law

Professor Margaret Hu is a Professor of Law and of International Affairs, Co-Hire for the Institute for Computational and Data Sciences, and Faculty Member of the Institute for Network and Security Research in the College of Engineering at The Pennsylvania State University. She also serves as Penn State Law’s inaugural Dean for Non-JD Programs. Her research interests include the intersection of immigration policy, national security, cybersurveillance, and civil rights. She has published several works on dataveillance and cybersurveillance, including, Biometric ID CybersurveillanceBig Data BlacklistingTaxonomy of the Snowden DisclosuresBiometric Cyberintelligence and the Posse Comitatus Act; and Algorithmic Jim Crow.  She is currently a member of the Advisory Board of the Future of Privacy Forum, a non-profit think tank in Washington, D.C., that promotes responsible data privacy policies. Previously, she served as special policy counsel in the Office of Special Counsel for Immigration-Related Unfair Employment Practices (OSC), Civil Rights Division, U.S. Department of Justice. Dean Hu holds a B.A. from the University of Kansas and a J.D. from Duke Law School. She clerked for Judge Rosemary Barkett on U.S. Court of Appeals for the Eleventh Circuit, and subsequently joined the U.S. Department of Justice through the Attorney General’s Honors Program.


Sune Lehmann
Technical University of Denmark

The background of Sune Lehmann is in physics and network science, but he has since specialized in looking for patterns in large-scale data on human behavior, publishing on topics such as human mobility, scientific publication patterns, collective attention, complex spreading phenomena, sentiment analysis, higher order network structures, and human sleep.


Deborah Lupton
University of New South Wales, Sydney
Arts, Design & Architecture

Deborah Lupton is SHARP Professor in the Faculty of Arts & Social Sciences, UNSW Sydney, working in the Centre for Social Research in Health and the Social Policy Research Centre and leading the Vitalities Lab. Her research is interdisciplinary, spanning sociology and media and cultural studies. She is the author/co-author of 18 books, the latest of which are Data Selves (2019) and The Face Mask in COVID Times (2021). She has also edited/co-edited a further eight volumes. Lupton is Leader of the UNSW Node of the Australian Research Council Centre of Excellence for Automated Decision-Making + Society. She is a Fellow of the Academy of the Social Sciences in Australia and holds an Honorary Doctor of Social Science degree awarded by the University of Copenhagen.


Christian Sandvig
University of Michigan
School of Information

Christian Sandvig is a faculty member at the School of Information specializing in information infrastructure and social media. His current work focuses on the implications of algorithmic systems that filter and curate culture. Before moving to Michigan, Sandvig taught at the University of Illinois at Urbana-Champaign and Oxford University. Sandvig’s research has been covered by The Economist, The New York Times, Le Monde, National Public Radio, CBS News, and other media outlets. His own writing appears in Wired and The Guardian. His work has been funded by the National Science Foundation, the MacArthur Foundation, and the Social Science Research Council. He has consulted for Intel, Microsoft, and the San Francisco Public Library.


Frank Takes
Leiden University
Computational Network Science Lab

Frank Takes is head of the Computational Network Science Lab at Leiden University and research fellow in computational social science at the University of Amsterdam. He is co-director of the Platform for Population-scale Social Network Analysis (POPNET) and board member of the Dutch Network Science Society (NL NetSci). His research deals with methods for large-scale social network analysis, with a focus on applications in economic networks, scientific collaboration networks and population-scale social networks. 


Robert West
Swiss Federal Institute of Technology, Lausanne (EPFL)
Data Science Laboratory

Robert West is an assistant professor of computer science at EPFL, where he heads the Data Science Lab. His research aims to understand, predict, and enhance human behavior in social and information networks by developing techniques in computational social science, data mining, network analysis, machine learning, and natural language processing. He holds a PhD in computer science from Stanford University.