Rich Context Competition
Workshop Agenda


Join us to hear presentations from the finalists for the NYU Coleridge Initiative’s Rich Context Competition. The competition challenged computer scientists to find ways of automating the discovery of research datasets, fields and methods used in social science research publications.

The teams are representatives from GESIS, KAIST, Paderborn University, and Allen AI


Date: February 15, 2019
Time: 8:30am - 3:30pm Eastern Time (EST)
Registration: Register here to receive an email reminder with a link to the webcast.
Webcast Link:


8:30 - 9:00 Breakfast and Coffee
9:00 - 9:30 Welcome and Introductions Julia Lane; Sponsors
9:30 - 10:00 Demonstration of Rich Context Tool John Case; ÜberResearch
10:00 - 10:30 Presentation of Results GESIS team; General Discussion
10:30 – 11:00 Presentation of Results KAIST team; General Discussion
11:00 – 11:30 Coffee Break
11:30 – 12:00 Presentation of Results Paderborn team; General Discussion
12:00 – 12:30 Presentation of Results Allen AI team; General Discussion
12:30 – 1:00 Networking lunch
1:00 – 1:45 Judges’ reviews and comments Judges
1:45 – 2:00 Announcement of winner Julia Lane; Sponsors
2:00 – 2:30 Future agenda and next steps
2:30 – 3:30 Networking reception

Team Representatives

Rricha Jalota

Paderborn University

Rricha Jalota is a developer in the Data Science Group at Paderborn University, Germany. Her interests lie in the application of Machine Learning/Deep Learning to solve NLP problems in the domain of (but not limited to) Question Answering, Chatbots and Information Retrieval.

Daniel King

Allen AI

Daniel King is a Predoctoral Young Investigator at The Allen Institute for Artificial Intelligence. He graduated from Harvey Mudd College with a degree in computer science in May 2018. His research interests are in natural language processing and applying AI for the benefit of everyone.

Wolfgang Otto


Wolfgang Otto is a Postgraduate and Research Assistant at GESIS - Leibniz Institute for the Social Sciences in Germany. As part of the Knowledge Technologies for the Social Sciences Department under Stefan Dietze, he applies NLP-techniques on text and data corpora in the Social Sciences. After finishing with a master degree at the NLP Group at Leipzig University (Prof. Dr. Gerhard Heyer), he is part of a team in a third funded project (German Research Fund) to build up a Specialized Information Service for Political Scientists ( A Project the State and University Library Bremen (SuUB) is realizing in cooperation with GESIS. During his studies, he collaborated in Projects on Digital Humanities, Applied Text Mining, and Data Science.

Haritz Puerto-San-Roman


Haritz Puerto-San-Roman is a Spanish research assistant at IR&NLP lab at KAIST and Master’s degree student at the School of Computing at KAIST in Korea. He is sponsored by the KGSP scholarship from the Korean Government. His research field is NLP and machine learning. He wants to make computers understand human languages. Before coming to KAIST, he was an undergraduate student of Computer Science at the University of Malaga in Spain where he graduated with honors. He also studied part of his BSc at Seoul National University and worked for 2 years as a software engineer while he was finishing his BSc.


Stefan Bender

Deutsche Bundesbank

Stefan Bender is Head of the Research Data and Service Center of the Deutsche Bundesbank and Honorary Professor at the University of Mannheim (School of Social Science). One of his positions is vice-chair of the German Data Forum ( Before joining the Deutsche Bundesbank Bender was head of the Research Data Center of the Federal Employment Agency at the Institute for Employment Research (IAB), where he developed one of the worldwide leading research data centers. His research interests are data access, data quality, merging administrative, survey data and/or big data, record linkage, unemployment, management quality and mobility of inventors. He has published over 100 articles in journals including the American Economic Review or the Quarterly Journal of Economics. Latest publications can be found here.

Jordan Boyd-Graber

University of Maryland

Jordan Boyd-Graber is an associate professor in the University of Maryland Computer Science Department (tenure home), Institute of Advanced Computer Studies, iSchool, and Language Science Center. Previously, Jordan was an assistant professor at Colorado's Department of Computer Science (tenure granted in 2017). He was a graduate student at Princeton with David Blei. Jordan’s research focuses on making machine learning more useful, more interpretable, and able to learn and interact from humans. This helps users sift through decades of documents; discover when individuals lie, reframe, or change the topic in a conversation; or to compete against humans in games that are based in natural language.

Ophir Frieder

Georgetown University

Ophir Frieder holds the Robert L. McDevitt, K.S.G., K.C.H.S. and Catherine H. McDevitt L.C.H.S. Chair in Computer Science and Information Processing and previously served as the Chair of the Department of Computer Science at Georgetown University. He is also Professor of Biostatistics, Bioinformatics and Biomathematics in the Georgetown University Medical Center. In addition to his academic positions, he is the Chief Scientific Officer for Invaryant, Inc. (formerly UMBRA Health, LLC.) and a Research Associate at the Institute of Information Science and Technology at the Italian National Research Council (ISTI-CNR). He is a Fellow of the AAAS, ACM, IEEE, and NAI, and a Member of Academia Europaea and the European Academy of Sciences and Arts.

Rayid Ghani

University of Chicago

Rayid Ghani is the Director of the Center for Data Science & Public Policy, Research Associate Professor in the Department of Computer Science, and a Senior Fellow at the Harris School of Public Policy at the University of Chicago. Rayid is a reformed computer scientist and wanna-be social scientist, but mostly just wants to increase the use of large-scale AI/ML/DS/data-related buzzword approaches in solving large public policy and social challenges responsibly, ethically, and equitably. Rayid works with governments and non-profits in policy areas such as health, criminal justice, education, public safety, economic development, and urban infrastructure. Rayid is also passionate about teaching practical data science and started the Data Science for Social Good Fellowship at UChicago that trains computer scientists, statisticians, and social scientists from around the world to work on data science problems with social impact.

Frauke Kreuter

University of Maryland

Frauke Kreuter is Professor in the Joint Program in Survey Methodology at the University of Maryland, Professor of Methods and Statistics at the University of Mannheim, and head of the statistical methods group at the German Institute for Employment Research in Nuremberg. Previously, she held positions in the Department of Statistics at the University of California, Los Angeles, and the Department of Statistics at the Ludwig-Maximillian’s University of Munich. Frauke serves on several advisory boards for National Statistical Institutes around the world, and within the Federal Statistical System in the United States. Frauke is also a Gertrude Cox Award winner, which recognizes statisticians in early- to mid-career who have made significant breakthroughs in statistical practice, and an elected fellow of the American Statistical Association. Additioanlly, she is co-founder of the Coleridge Initiative and founder of the International Program in Survey and Data Science.

Julia Lane

New York University

Julia Lane is a Professor at the NYU Wagner Graduate School of Public Service, at the NYU Center for Urban Science and Progress, and a NYU Provostial Fellow for Innovation Analytics. She cofounded the Coleridge Initiative, whose goal is to use data to transform the way governments access and use data for the social good through training programs, research projects and a secure data facility. The approach is attracting national attention, including the Commission on Evidence Based Policy and the Federal Data Strategy. Previous to this, Julia was a Senior Managing Economist and Institute Fellow at American Institutes for Research. In this role Julia co-founded the Institute for Research on Innovation and Science (IRIS) at the University of Michigan. Julia has held positions at the National Science Foundation, The Urban Institute, The World Bank, American University and NORC at the University at Chicago.

Ian Mulvany

SAGE Publications

Ian Mulvany is an experienced digital technical manager, with wide experience in the STM industry. Ian is based in London and is head of transformation for SAGE publishing where he looks at how technology can help us improve our processes and products.

Alex Wade

Chan Zuckerberg Initiative

Alex Wade currently works with the Chan Zuckerberg Initiative as technical program manager for Meta. Previously Wade served as the Director for Scholarly Communication for Microsoft Research, focused on Microsoft Academic, a semantic knowledge graph of academic research publications, people, and institutions. During his career at Microsoft, Wade managed the corporate search and taxonomy management services and served as Senior Program Manager for Windows Search. Prior to joining Microsoft, he held Systems Librarian, Engineering Librarian, and Philosophy Librarian, and technical library positions at the University of Washington, the University of Michigan, and the University of California, Berkeley. Wade holds a bachelor's degree in Philosophy from the University of California, Berkeley, and a Master of Librarianship degree from the University of Washington.