papers

Publications (25)

stat.AP2017

Applying Machine Learning Methods to Enhance the Distribution of Social Services in Mexico

Kris Sankaran, Diego Garcia-Olano, Mobin Javed +7

cs.CY2024

Preventing Eviction-Caused Homelessness through ML-Informed Distribution of Rental Assistance

Catalina Vajiac, Arun Frey, Joachim Baumann +5

cs.CY2020

A Machine Learning System for Retaining Patients in HIV Care

Avishek Kumar, Arthi Ramachandran, Adolfo De Unanue +7

cs.CY2019

Artificial Intelligence for Social Good

Gregory D. Hager, Ann Drobnis, Fei Fang +8

cs.LG2023

Explainable Machine Learning for Public Policy: Use Cases, Gaps, and Research Directions

Kasun Amarasinghe, Kit Rodolfa, Hemank Lamba +1

cs.AI2025

Towards Automated Scoping of AI for Social Good Projects

Jacob Emmerson, Rayid Ghani, Zheyuan Ryan Shi

cs.LG2019

Aequitas: A Bias and Fairness Audit Toolkit

Pedro Saleiro, Benedict Kuester, Loren Hinkson +5

cs.LG2024

Aequitas Flow: Streamlining Fair ML Experimentation

Sérgio Jesus, Pedro Saleiro, Inês Oliveira e Silva +5

cs.CY2020

Mapping New Informal Settlements using Machine Learning and Time Series Satellite Images: An Application in the Venezuelan Migration Crisis

Isabelle Tingzon, Niccolo Dejito, Ren Avell Flores +7

stat.AP2020

A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services

Harrison Wilde, Lucia Lushi Chen, Austin Nguyen +7

cs.CY2020

Case Study: Predictive Fairness to Reduce Misdemeanor Recidivism Through Social Service Interventions

Kit T. Rodolfa, Erika Salomon, Lauren Haynes +3

stat.AP2018

Using Machine Learning to Assess the Risk of and Prevent Water Main Breaks

Avishek Kumar, Syed Ali Asad Rizvi, Benjamin Brooks +8

cs.CY2026

Toward Third-Party Assurance of AI Systems: Design Requirements, Prototype, and Early Testing

Rachel M. Kim, Blaine Kuehnert, Alice Lai +3

cs.LG2023

Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools

Emily Black, Rakshit Naidu, Rayid Ghani +3

cs.LG2022

Bandit Data-Driven Optimization

Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani +1

cs.CY2018

Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness

Sebastian Vollmer, Bilal A. Mateen, Gergo Bohner +15

cs.LG2025

Breaking the Cycle of Incarceration With Targeted Mental Health Outreach: A Case Study in Machine Learning for Public Policy

Kit T. Rodolfa, Erika Salomon, Jin Yao +9

cs.LG2026

Learning Who to Treat When Treatment is Missing

Johnna Sundberg, Rayid Ghani, Eli Ben-Michael +1

The paper develops efficient estimators for policy learning when treatment assignments are missing, handling both missing-at-random and missing-completely-conditionally-at-random s…

#policy learning#missing data#causal inference#treatment effect estimation
cs.LG2021

Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy

Kit T. Rodolfa, Hemank Lamba, Rayid Ghani

cs.CY2019

A Clinical Approach to Training Effective Data Scientists

Kit T Rodolfa, Adolfo De Unanue, Matt Gee +1

cs.CY2022

A Conceptual Framework for Using Machine Learning to Support Child Welfare Decisions

Ka Ho Brian Chor, Kit T. Rodolfa, Rayid Ghani

cs.LG2021

An Empirical Comparison of Bias Reduction Methods on Real-World Problems in High-Stakes Policy Settings

Hemank Lamba, Kit T. Rodolfa, Rayid Ghani

cs.LG2022

Faking feature importance: A cautionary tale on the use of differentially-private synthetic data

Oscar Giles, Kasra Hosseini, Grigorios Mingas +13

cs.CY2025

Enabling the AI Revolution in Healthcare

Mona Singh, Katie Siek, David Danks +5

cs.LG2023

On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods

Kasun Amarasinghe, Kit T. Rodolfa, Sérgio Jesus +6