Fair February: Data Science for Social Good

January 27 – February 12, 2021: Fair February is a three-week symposium. Each week concentrates on a theme under the umbrella “Data Science for Social Good.” The purpose of this symposium is to let young researchers of various disciplines who are interested in these themes meet each other and learn more about each other's work and research at Brown University and beyond. Each theme starts with a keynote address, followed by presentations from younger researchers. The speakers are listed below, and you can view recordings of all talks.

More details and full abstracts here. 

Organized by Shahrzad Haddadan, DSI and Computer Science; Marie Schenk, Political Science and Taubman Center for American Politics and Policy; and Cristina Menghini, Computer Engineering, La Sapienza University of Rome and Computer Science, Brown

Week One: Computation and Health

Wednesday, January 27 WATCH VIDEO

Keynote Address: Elizabeth Chen, Interim Director, Brown Center for Biomedical Informatics
Artificial Intelligence in Healthcare

Ruotao Zhang, Postdoctoral Research Associate, Biostatistics Department
Identifying Subgroups with Differential Prediction Accuracy

Friday, January 29 Watch video

Erisa Terolli, Postdoctoral Research Associate, Max Planck Institute
Focused Query Expansion with Entity Cores for Patient-Centric Health Search

Ignacio Segovia-Dominguez, Postdoctoral Research Associate, University of Texas - Dallas
Topological and Geometric Methods for COVID-19 Tracking

Week Two: Computation and Welfare/Policy-Making

Wednesday, February 3  Watch Video

Keynote Address: Daniel Björkegren, Assistant Professor, Brown University Department of Economics 
Manipulation-Proof Machine Learning

Jessica Dai, Undergraduate Student, Brown University Department of Computer Science
Fair Machine Learning Under Partial Compliance

Friday, February 5 (Session 1)  Watch Video

Sanghamitra Dutta, Ph.D. Candidate, Carnegie Mellon University Department of Electrical and Computer Engineering
Towards a Systematic Understanding of Exempt and Non-Exempt Algorithmic Biases

Cyrus Cousins, Ph.D. Candidate, Brown University Department of Computer Science
(Machine) Learning What Policymakers Value

Friday, February 5 (session 2)  Watch Video

Samsun Knight, Ph.D. Candidate, Brown University Department of Economics
(Machine) Learning What Policymakers Value

Mayra Morales Tirado, Postdoctoral Research Associate, University of Manchester 
Let’s Talk Connecting ST&I Studies with Data Science

Kweku Kwegyir-Aggrey, Postdoctoral Research Associate, Brown University Department of Computer Science
Fair Comparisons with Optimal Transport

Week Three: Computation and Democracy

Wednesday, February 10  Watch Video

Keynote Address: Jennifer Forestal, Assistant Professor of Political Science, Loyola University-Chicago
Designing for Democracy: How to Build Community in Digital Environments

Aarushi Kalra, Ph.D. Candidate, Department of Economics, Brown University
Hate Speech on Social Media in India

Friday, February 12 (Session 1)  watch video

Ana-Andreea Stoica, Ph.D. Candidate, Columbia University 
Diversity and Inequality in Social Networks: Recommendation to Information Diffusion

Francesco Fabbri, Ph.D Candidate, Web Science and Social Computing Group, Pompeu Fabra University-Barcelona
The Effect of Homophily on Disparate Visibility of Minorities in People Recommender Systems

Friday, February 12 (Session 2) Watch Video

Suman Bera, Postdoctoral Research Associate, University of California-Santa Cruz 
Fair Algorithms for Clustering

Cristina Menghini, Ph.D. Candidate, Sapienza University
Auditing Wikipedia's Hyperlinks Network on Polarizing Topics

Shahrzad Haddadan, Postdoctoral Research Associate, Data Science Initiative and Department of Computer Science, Brown University
Reducing Structural Bias in Networks by Link Insertion