MD4SG

Working Groups


The MD4SG initiative has been organizing numerous working groups since fall 2016. You can find a list of these working groups along with their webpages below:

Bias, Discrimination, and Fairness Bias, Discrimination, and Fairness

Bias, Discrimination, and Fairness

Organized by Faidra Monachou (Stanford), Jessica Finocchiaro (University of Colorado - Boulder), and Duncan McElfresh (University of Maryland)

We work to better understand issues of bias, discrimination, and fairness that arise when technological systems are deployed in social and economic environments.

Healthcare (Fall 2018 - Spring 2020) Healthcare (Fall 2018 - Spring 2020)

Healthcare (Fall 2018 - Spring 2020)

Organized by Zhaowei She (GATech)

We are a group of academic researchers working on real world healthcare market design problems (e.g. kidney exchange, risk adjustment) using techniques from computer science, operations research and economics.

Housing (Fall 2018 - Spring 2019) Housing (Fall 2018 - Spring 2019)

Housing (Fall 2018 - Spring 2019)

Organized by Daniel Walinger (NYU)

We are a group of academic researchers working on market design problems in affordable housing policy (e.g. affordable housing allocation, fair housing) using techniques from computer science, operations research, and economics.

Online Labor Markets (Fall 2018 - Spring 2020) Online Labor Markets (Fall 2018 - Spring 2020)

Online Labor Markets (Fall 2018 - Spring 2020)

Organized by Sara Kingsley (CMU) and Manish Raghavan (Cornell)

We are a group of academic researchers seeking to apply techniques from mechanism design to problems found in online labor markets, including those related to matching mechanisms, inequality and information asymmetry, and hiring algorithms.

original

Original Reading Group (Fall 2016 - Spring 2018)

Organized by Rediet Abebe (Cornell) and Kira Goldner (University of Washington)

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original

Original Reading Group

We are a multi-institution, interdisciplinary group exploring research directions in various domains where insights from algorithms, optimization, and mechanism design can be used to improve access to opportunity. We have compiled our reading list and detailed discussion notes.

Photos by rawpixel; Ivan Vranic; and freestocks.org; on Unsplash