Outnumbered but Well-Spoken: Female Commenters in the New York Times. - Emma Pierson (CSCW, 2015)

Sharing and Specificity of Co-expression Networks across 35 Human Tissues. - Emma Pierson; Daphne Koller; Alexis J. Battle; Sara Mostafavi (PLoS Comput. Biol., 2015)

Algorithmic Decision Making and the Cost of Fairness. - Sam Corbett-Davies; Emma Pierson; Avi Feller; Sharad Goel; Aziz Huq (KDD, 2017)

Denoising genome-wide histone ChIP-seq with convolutional neural networks. - Pang Wei Koh; Emma Pierson; Anshul Kundaje (Bioinform., 2017)

SIMLR: a tool for large-scale single-cell analysis by multi-kernel learning. - Bo Wang 044; Daniele Ramazzotti; Luca De Sano; Junjie Zhu; Emma Pierson; Serafim Batzoglou (CoRR, 2017)

Gender differences in beliefs about algorithmic fairness. - Emma Pierson (CoRR, 2017)

Fast Threshold Tests for Detecting Discrimination. - Emma Pierson; Sam Corbett-Davies; Sharad Goel (AISTATS, 2018)

Modeling Individual Cyclic Variation in Human Behavior. - Emma Pierson; Tim Althoff; Jure Leskovec (WWW, 2018)

Inferring Multi-Dimensional Rates of Aging from Cross-Sectional Data. - Emma Pierson; Pang Wei Koh; Tatsunori B. Hashimoto; Daphne Koller; Jure Leskovec; Nicholas Eriksson; Percy Liang (CoRR, 2018)

Predicting pregnancy using large-scale data from a women's health tracking mobile application. - Bo Liu 042; Shuyang Shi; Yongshang Wu; Daniel Thomas; Laura Symul; Emma Pierson; Jure Leskovec (CoRR, 2018)

Inferring Multidimensional Rates of Aging from Cross-Sectional Data. - Emma Pierson; Pang Wei Koh; Tatsunori B. Hashimoto; Daphne Koller; Jure Leskovec; Nick Eriksson; Percy Liang (AISTATS, 2019)

Predicting pregnancy using large-scale datafrom a women's health tracking mobile application. - Bo Liu 042; Shuyang Shi; Yongshang Wu; Daniel Thomas; Laura Symul; Emma Pierson; Jure Leskovec (WWW, 2019)

Concept Bottleneck Models. - Pang Wei Koh; Thao Nguyen; Yew Siang Tang; Stephen Mussmann; Emma Pierson; Been Kim; Percy Liang (ICML, 2020)

Ethical Machine Learning in Health Care. - Irene Y. Chen; Emma Pierson; Sherri Rose; Shalmali Joshi; Kadija Ferryman; Marzyeh Ghassemi (CoRR, 2020)

WILDS: A Benchmark of in-the-Wild Distribution Shifts. - Pang Wei Koh; Shiori Sagawa; Henrik Marklund; Sang Michael Xie; Marvin Zhang; Akshay Balsubramani; Weihua Hu; Michihiro Yasunaga; Richard Lanas Phillips; Sara Beery; Jure Leskovec; Anshul Kundaje; et al. (CoRR, 2020)

Data science for social equality. - Emma Pierson (2020)

WILDS: A Benchmark of in-the-Wild Distribution Shifts. - Pang Wei Koh; Shiori Sagawa; Henrik Marklund; Sang Michael Xie; Marvin Zhang; Akshay Balsubramani; Weihua Hu; Michihiro Yasunaga; Richard Lanas Phillips; Irena Gao; Tony Lee; Etienne David; et al. (ICML, 2021)

Supporting COVID-19 Policy Response with Large-scale Mobility-based Modeling. - Serina Chang; Mandy L. Wilson; Bryan L. Lewis; Zakaria Mehrab; Komal K. Dudakiya; Emma Pierson; Pang Wei Koh; Jaline Gerardin; Beth Redbird; David Grusky; Madhav V. Marathe; Jure Leskovec (KDD, 2021)

Quantifying Inequality in Underreported Medical Conditions. - Divya Shanmugam; Emma Pierson (CoRR, 2021)

Mobility network models of COVID-19 explain inequities and inform reopening. - Serina Chang; Emma Pierson; Pang Wei Koh; Jaline Gerardin; Beth Redbird; David Grusky; Jure Leskovec (Nat., 2021)

Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysis. - J. D. Zamfirescu-Pereira; Jerry Chen; Emily Wen; Allison Koenecke; Nikhil Garg 001; Emma Pierson (FAccT, 2022)

Human interaction networks reveal that large cities facilitate segregation. - Hamed Nilforoshan; Wenli Looi; Emma Pierson; Blanca Villanueva; Nic Fishman; Yiling Chen; John Sholar; Beth Redbird; David Grusky; Jure Leskovec (CoRR, 2022)

How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions? - Charvi Rastogi; Ivan Stelmakh; Alina Beygelzimer; Yann N. Dauphin; Percy Liang; Jennifer Wortman Vaughan; Zhenyu Xue; Hal Daumé III; Emma Pierson; Nihar B. Shah (CoRR, 2022)

Detecting disparities in police deployments using dashcam data. - Matt Franchi; J. D. Zamfirescu-Pereira; Wendy Ju; Emma Pierson (FAccT, 2023)

Coarse race data conceals disparities in clinical risk score performance. - Rajiv Movva; Divya Shanmugam; Kaihua Hou; Priya Pathak; John V. Guttag; Nikhil Garg 001; Emma Pierson (MLHC, 2023)

Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems. - Smitha Milli; Emma Pierson; Nikhil Garg 001 (CoRR, 2023)

Large language models shape and are shaped by society: A survey of arXiv publication patterns. - Rajiv Movva; Sidhika Balachandar; Kenny Peng; Gabriel Agostini; Nikhil Garg 001; Emma Pierson (CoRR, 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)

Human mobility networks reveal increased segregation in large cities. - Hamed Nilforoshan; Wenli Looi; Emma Pierson; Blanca Villanueva; Nic Fishman; Yiling Chen; John Sholar; Beth Redbird; David Grusky; Jure Leskovec (Nat., 2023)

A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing. - Gabriel Agostini; Emma Pierson; Nikhil Garg 001 (AAAI, 2024)

Annotation alignment: Comparing LLM and human annotations of conversational safety. - Rajiv Movva; Pang Wei Koh; Emma Pierson (EMNLP, 2024)

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

Beyond the Stethoscope: Operationalizing Interactive Clinical Reasoning in Large Language Models via Proactive Information Seeking. - Shuyue Stella Li; Vidhisha Balachandran; Shangbin Feng; Emma Pierson; Pang Wei Koh; Yulia Tsvetkov (ICHI, 2024)

Domain constraints improve risk prediction when outcome data is missing. - Sidhika Balachandar; Nikhil Garg 001; Emma Pierson (ICLR, 2024)

Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers. - Rajiv Movva; Sidhika Balachandar; Kenny Peng; Gabriel Agostini; Nikhil Garg 001; Emma Pierson (NAACL-HLT, 2024)

MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning. - Shuyue Stella Li; Vidhisha Balachandran; Shangbin Feng; Jonathan Ilgen; Emma Pierson; Pang Wei W. Koh; Yulia Tsvetkov (NeurIPS, 2024)

Reconciling the Accuracy-Diversity Trade-off in Recommendations. - Kenny Peng; Manish Raghavan; Emma Pierson; Jon M. Kleinberg; Nikhil Garg 001 (WWW, 2024)

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. - Hyewon Jeong; Sarah Jabbour; Yuzhe Yang 003; Rahul Thapa; Hussein Mozannar; William Jongwon Han; Nikita Mehandru; Michael Wornow; Vladislav Lialin; Xin Liu 034; Alejandro Lozano; Jiacheng Zhu; et al. (CoRR, 2024)

MEDIQ: Question-Asking LLMs for Adaptive and Reliable Clinical Reasoning. - Shuyue Stella Li; Vidhisha Balachandran; Shangbin Feng; Jonathan Ilgen; Emma Pierson; Pang Wei Koh; Yulia Tsvetkov (CoRR, 2024)

Testing for racial bias using inconsistent perceptions of race. - Nora Gera; Emma Pierson (CoRR, 2024)

Shaping AI's Impact on Billions of Lives. - Mariano-Florentino Cuellar; Jeff Dean; Finale Doshi-Velez; John L. Hennessy; Andy Konwinski; Sanmi Koyejo; Pelonomi Moiloa; Emma Pierson; David A. Patterson 001 (CoRR, 2024)

Generative AI in Medicine. - Divya Shanmugam; Monica Agrawal; Rajiv Movva; Irene Y. Chen; Marzyeh Ghassemi; Maia Jacobs; Emma Pierson (CoRR, 2024)

Learning Disease Progression Models That Capture Health Disparities. - Erica Chiang; Divya Shanmugam; Ashley N. Beecy; Gabriel Sayer; Nir Uriel; Deborah Estrin; Nikhil Garg 001; Emma Pierson (CoRR, 2024)

Learning Disease Progression Models That Capture Health Disparities. - Erica Chiang; Divya Shanmugam; Ashley N. Beecy; Gabriel Sayer; Deborah Estrin; Nikhil Garg 001; Emma Pierson (CHIL, 2025)

LLMs Generate Structurally Realistic Social Networks but Overestimate Political Homophily. - Serina Chang; Alicja Chaszczewicz; Emma Wang; Maya Josifovska; Emma Pierson; Jure Leskovec (ICWSM, 2025)

Evaluating multiple models using labeled and unlabeled data. - Divya Shanmugam; Shuvom Sadhuka; Manish Raghavan; John V. Guttag; Bonnie Berger; Emma Pierson (CoRR, 2025)

Sparse Autoencoders for Hypothesis Generation. - Rajiv Movva; Kenny Peng; Nikhil Garg 001; Jon M. Kleinberg; Emma Pierson (CoRR, 2025)

Bayesian Modeling of Zero-Shot Classifications for Urban Flood Detection. - Matt Franchi; Nikhil Garg 001; Wendy Ju; Emma Pierson (CoRR, 2025)

Inferring fine-grained migration patterns across the United States. - Gabriel Agostini; Rachel Young; Maria Fitzpatrick; Nikhil Garg 001; Emma Pierson (CoRR, 2025)

Urban Incident Prediction with Graph Neural Networks: Integrating Government Ratings and Crowdsourced Reports. - Sidhika Balachandar; Shuvom Sadhuka; Bonnie Berger; Emma Pierson; Nikhil Garg 001 (CoRR, 2025)

Use Sparse Autoencoders to Discover Unknown Concepts, Not to Act on Known Concepts. - Kenny Peng; Rajiv Movva; Jon M. Kleinberg; Emma Pierson; Nikhil Garg 001 (CoRR, 2025)

Advancing Science- and Evidence-based AI Policy. - Rishi Bommasani; Sanjeev Arora; Jennifer T. Chayes; Yejin Choi 001; Mariano-Florentino Cuellar; Li Fei-Fei 001; Daniel E. Ho; Dan Jurafsky; Sanmi Koyejo; Hima Lakkaraju; Arvind Narayanan; Alondra Nelson; et al. (CoRR, 2025)