Autodetection and Classification of Hidden Cultural City Districts from Yelp Reviews. - Harini Suresh; Nicholas Locascio (CoRR, 2015)

Approximate compression: enhancing compressibility through data approximation. - Harini Suresh; Shashank Hegde; John Sartori (ESTIMedia, 2017)

Clinical Intervention Prediction and Understanding with Deep Neural Networks. - Harini Suresh; Nathan Hunt; Alistair E. W. Johnson; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (MLHC, 2017)

Clinical Intervention Prediction and Understanding using Deep Networks. - Harini Suresh; Nathan Hunt; Alistair E. W. Johnson; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2017)

The Use of Autoencoders for Discovering Patient Phenotypes. - Harini Suresh; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2017)

Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs. - Matthew B. A. McDermott; Tom Yan; Tristan Naumann; Nathan Hunt; Harini Suresh; Peter Szolovits; Marzyeh Ghassemi (AAAI, 2018)

Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU. - Harini Suresh; Jen J. Gong; John V. Guttag (KDD, 2018)

Racial Disparities and Mistrust in End-of-Life Care. - Willie Boag; Harini Suresh; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (MLHC, 2018)

Modeling Mistrust in End-of-Life Care. - Willie Boag; Harini Suresh; Leo Anthony Celi; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2018)

Approximate Communication: Techniques for Reducing Communication Bottlenecks in Large-Scale Parallel Systems. - Filipe Betzel; S. Karen Khatamifard; Harini Suresh; David J. Lilja; John Sartori; Ulya R. Karpuzcu (ACM Comput. Surv., 2018)

A Framework for Understanding Unintended Consequences of Machine Learning. - Harini Suresh; John V. Guttag (CoRR, 2019)

Image segmentation of liver stage malaria infection with spatial uncertainty sampling. - Ava P. Soleimany; Harini Suresh; Jose Javier Gonzalez Ortiz; Divya Shanmugam; Nil Gural; John V. Guttag; Sangeeta N. Bhatia (CoRR, 2019)

Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making. - Harini Suresh; Natalie Lao; Ilaria Liccardi (WebSci, 2020)

Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs. - Harini Suresh; Steven R. Gomez; Kevin K. Nam; Arvind Satyanarayan (CHI, 2021)

A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle. - Harini Suresh; John V. Guttag (EAAMO, 2021)

Do as AI say: susceptibility in deployment of clinical decision-aids. - Susanne Gaube; Harini Suresh; Martina Raue; Alexander Merritt; Seth J. Berkowitz; Eva Lermer; Joseph F. Coughlin; John V. Guttag; Errol Colak; Marzyeh Ghassemi (npj Digit. Medicine, 2021)

Tech Worker Organizing for Power and Accountability. - William Boag; Harini Suresh; Bianca Lepe; Catherine D'Ignazio (FAccT, 2022)

Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. - Harini Suresh; Rajiv Movva; Amelia Lee Dogan; Rahul Bhargava; Isadora Cruxen; Angeles Martinez Cuba; Guilia Taurino; Wonyoung So; Catherine D'Ignazio (FAccT, 2022)

Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs. - Harini Suresh; Kathleen M. Lewis; John V. Guttag; Arvind Satyanarayan (IUI, 2022)

Beyond Faithfulness: A Framework to Characterize and Compare Saliency Methods. - Angie W. Boggust; Harini Suresh; Hendrik Strobelt; John V. Guttag; Arvind Satyanarayan (CoRR, 2022)

Improved Text Classification via Test-Time Augmentation. - Helen Lu; Divya Shanmugam; Harini Suresh; John V. Guttag (CoRR, 2022)

Underspecification Presents Challenges for Credibility in Modern Machine Learning. - Alexander D'Amour; Katherine A. Heller; Dan Moldovan; Ben Adlam; Babak Alipanahi; Alex Beutel; Christina Chen; Jonathan Deaton; Jacob Eisenstein; Matthew D. Hoffman; Farhad Hormozdiari; Neil Houlsby; et al. (J. Mach. Learn. Res., 2022)

Feminicide and counterdata production: Activist efforts to monitor and challenge gender-related violence. - Catherine D'Ignazio; Isadora Cruxên; Helena Suárez Val; Angeles Martinez Cuba; Mariel García-Montes; Silvana Fumega; Harini Suresh; Wonyoung So (Patterns, 2022)

Kaleidoscope: Semantically-grounded, context-specific ML model evaluation. - Harini Suresh; Divya Shanmugam; Tiffany Chen; Annie G. Bryan; Alexander D'Amour; John V. Guttag; Arvind Satyanarayan (CHI, 2023)

Saliency Cards: A Framework to Characterize and Compare Saliency Methods. - Angie W. Boggust; Harini Suresh; Hendrik Strobelt; John V. Guttag; Arvind Satyanarayan (FAccT, 2023)

Use large language models to promote equity. - Emma Pierson; Divya Shanmugam; Rajiv Movva; Jon M. Kleinberg; Monica Agrawal; Mark Dredze; Kadija Ferryman; Judy Wawira Gichoya; Dan Jurafsky; Pang Wei Koh; Karen Levy; Sendhil Mullainathan; et al. (CoRR, 2023)

Context and Participation in Machine Learning - Harini Suresh (2023)

Participation in the age of foundation models. - Harini Suresh; Emily Tseng; Meg Young; Mary L. Gray; Emma Pierson; Karen Levy (FAccT, 2024)

Sociotechnical AI Governance: Challenges and Opportunities for HCI. - K. J. Kevin Feng; Rock Yuren Pang; Tzu-Sheng Kuo; Amy A. Winecoff; Emily Tseng; David Gray Widder; Harini Suresh; Katharina Reinecke; Amy X. Zhang (CHI Extended Abstracts, 2025)

"Ownership, Not Just Happy Talk": Co-Designing a Participatory Large Language Model for Journalism. - Emily Tseng; Meg Young; Marianne Aubin Le Quéré; Aimee Rinehart; Harini Suresh (FAccT, 2025)

The Malicious Technical Ecosystem: Exposing Limitations in Technical Governance of AI-Generated Non-Consensual Intimate Images of Adults. - Michelle L. Ding; Harini Suresh (CoRR, 2025)