• Understanding Disparities in Post Hoc Machine Learning Explanation
    Vishwali Mhasawade, Salman Rahman, Zoe Haskell-Craig, Rumi Chunara
    ACM Conference on Fairness, Accountability and Transparency (ACM FAccT), 2024
    [ Paper]

  • A Causal Perspective on Label Bias
    Vishwali Mhasawade, Alexander D’Amour, Stephen Pfohl
    ACM Conference on Fairness, Accountability and Transparency (ACM FAccT), 2024

  • Generalizability Challenges of Mortality Risk Prediction Models: A retrospective Analysis on a Multi-center Database
    Harvineet Singh, Vishwali Mhasawade, Rumi Chunara
    PLOS Digital Health, 2022
    [ Paper]

  • Machine Learning and Algorithmic Fairness in Public and Population Health
    Vishwali Mhasawade, Yuan Zhao, Rumi Chunara
    Nature Machine Intelligence, 2021
    [ Paper]

  • Causal Multi-level Fairness
    Vishwali Mhasawade and Rumi Chunara
    AAAI/ACM Conference on Artifical Intelligence, Ethics, and Society (AIES), 2021
    [ Paper]

  • Fairness Violations and Mitigation under Covariate Shift
    Harvineet Singh, Rina Singh, Vishwali Mhasawade, Rumi Chunara
    ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT), 2021
    Fair Machine Learning in Health Workshop, NeurIPS, 2019
    [ Paper]

  • Population-aware Hierarchical Bayesian Domain Adaptation via Multi-component Invariant Learning
    Vishwali Mhasawade, Nabeel Abdur Rehman, Rumi Chunara
    Proceedings ACM Conference on Health, Inference and Learning (CHIL), 2020
    Machine Learning for Health Workshop, NeurIPS, 2018
    [ Paper]

  • Role of the Built and Online Social Environments on Expression of Dining on Instagram
    Vishwali Mhasawade, Anas Elghafari, Dustin T. Duncan, Rumi Chunara
    International Journal of Environmental Research and Public Health, 2020
    [ Paper]

  • Neural Networks an Quanitifier Conservativity: Does Data Distribution Affect Learnability?
    Vishwali Mhasawade, Ildikó Emese Szabó, Melanie Tosik, Sheng-Fu Wang
    Preprint, 2018
    [ Paper]

  • Explainable Musial Phrase Completion
    Iddo Drori, Gregory W. Johnsen, Ling Lin, Lucia Yu, Andrew Dempsey, Vishwali Mhasawade, Daniel Jaroslawicz
    Joint Workshop on Machine Learning for Music, ICML, 2018