MD4SG

Working Groups

Inequality


The MD4SG inequality working group studies how optimization, incentive design, and machine learning can mitigate or magnify social and economic inequality. We are especially focused on provision and targeting of social programs: when and how should resources be directed specifically to the most vunlerable members of the population? How should these individuals be selected? Beyond these core questions, our research interests are wide-ranging, including both the philosophical underpinnings of economic design and the practical realities of studying institutions that serve vulnerable populations.

 

Representative Projects

   

Fall 2020 Syllabus (PDF)

 

Working Group Organizers

Sera Linardi Associate Professor of Economics University of Pittsburgh
Samuel Taggart Assistant Professor in Computer Science Oberlin College
 

Working Group Members

Rediet Abebe Assistant Professor of Computer Science UC Berkeleey
Lenore J. Cowen Professor of Computer Science Tufts University
Sanmay Das Professor of Computer Science George Mason University
Bikram Datta Assistant Professor of Economics Indian Institute of Technology, Kanpur
Zoë Hitzig PhD Candidate in Economics Harvard University
Maximilian Kasy Associate Professor of Economics University of Oxford
Chika Okafor PhD Candidate in Economics Harvard Economics
Elisabeth Paulson PhD Candidate in Operations Research Massachusetts Institute of Technology
Richard Lanas Phillips Doctoral Student in Computer Science Cornell University
Emmanouil Pountourakis Assistant Professor of Computer Science Drexel University
Amita Shukla Schmidt Futures
Ana-Andreea Stoica Doctoral Student in Computer Science Columbia University
Angela Zhou PhD Candidate in Operations Research Cornell Tech
Juba Ziani Warren Center Postdoctoral Fellow in Computer Science University of Pennsylvania