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MD4SG

Working Groups

Global Perspectives on Inequality


The MD4SG Inequality working group studies how optimization, incentive design, and learning can improve services for vulnerable populations, such as homeless individuals and smallholder farmers. We also study how algorithmic approaches can magnify existing inequalities, and how to design systems to guard against these effects. To address such questions, we draw on techniques from computer science, economics, and operations research, as well as experience in social work and international development.

 

Working Group Organizers

ZoŽ Hitzig Ph.D. Candidate in Economics Harvard University
Samuel Taggart Assistant Professor in Computer Science Oberlin College


Working Group Members

Rediet Abebe Junior Fellow Harvard University
Jerry Anunrojwong Research Affiliate MIT; Chulalongkorn University
Lenore Cowen Professor of Computer Science, and (by courtesy), Mathematics Tufts University
Milan Cvitkovic Ph.D. Student in Computing & Mathematical Sciences California Insitute of Technology
Mutembesa Daniel Researcher in Artificial Intelligence & Data Science Makerere University, Uganda
Sanmay Das Associate Professor of Computer Science & Engineering Washington University in St. Louis
Bikram Datta Assistant Professor of Economics Indian Institute of Technology, Kanpur
Sera Linardi Associate Professor of Economics University of Pittsburgh
George Musumba Lecturer in Computer Science Dedan Kimathi University of Technology, Kenya
Benjamin Otieno Senior Lecturer in Computing & Informatics University of Nairobi, Kenya
Ryan Shi Ph.D. Student in Computer Science Carnegie Mellon University
Eric Sodomka Research Scientist in Economics & Computer Science Facebook Research
Ana-Andreea Stoica Ph.D. Student in Computer Science Columbia University
Angela Zhou Ph.D. Student in Operations Research Cornell Tech