AI for Social Impact

Deploying AI systems for maternal health, pediatric care, conservation, and fairness.

A unifying thread across our research is deploying AI where it matters most — in resource-constrained, high-stakes settings where benefits accrue to vulnerable populations or shared public goods.

Application domains:

Maternal and Child Health — Partnering with ARMMAN (India) to schedule health worker outreach for pregnant women, using RMAB-based systems evaluated in randomized control trials.

Pediatric Health — Collaborating with Children’s Healthcare of Atlanta on AI-driven early warning systems and opportunistic screening for Type 2 diabetes.

Wildlife Conservation — Game-theoretic patrol scheduling to protect endangered species from poaching in large protected areas.

Fairness in AI — Polarity-aware fair ranking and bias detection in LLM-based recommender systems to ensure AI does not perpetuate disparities.

Selected publications:

(Jin et al., 2025; Balagopalan et al., 2025; Verma et al., 2023; Xu et al., 2021; Andre et al., 2025)

References

2025

  1. Opportunistic Screening of Type 2 Diabetes with Deep Metric Learning using Electronic Health Records
    Qixuan Jin, Haoran Zhang, Lukasz Szczerbinski, Jiacheng Zhu, Walter Gerych, and 10 more authors
    Scientific Reports, 2025
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  2. What’s in a Query: Polarity-aware Distribution-based Fair Ranking
    Aparna Balagopalan, Kai Wang, Olawale Elijah Salaudeen, Asia Biega, and Marzyeh Ghassemi
    In The Web Conference (WWW), 2025
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  3. Revealing Potential Biases in LLM-Based Recommender Systems in the Cold Start Setting
    Alexandre Andre, Gauthier Roy, Eva Dyer, and Kai Wang
    2025
    EARL 2025 Workshop
    arXiv

2023

  1. Restless Multi-Armed Bandits for Maternal and Child Health: Results from Decision-Focused Learning
    Shresth Verma, Aditya Mate, Kai Wang, Neha Madhiwalla, Aparna Hegde, and 2 more authors
    In International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2023
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2021

  1. Dual-Mandate Patrols: Multi-Armed Bandits for Green Security
    Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, and 1 more author
    In AAAI Conference on Artificial Intelligence (AAAI), 2021
    Best Paper Runner-Up
    arXiv