← All authors Cynthia Rudin Duke University (from arXiv:2505.24296, 2025) · ORCID · OpenAlex
54 papers in scope · 50 published · 4 on the econ.EM arXiv · 13,466 citations · h-index 22 (over the papers listed here)
Related authors The 20 authors closest to this one in our weighted citation graph, most related first.
Harsh Parikh Alexander Volfovsky Quinn Lanners Sudeepa Roy Vittorio Orlandi Marco Morucci David Page Melody Huang Caleb H. Miles Trang Quynh Nguyen Louise Xu Carlos Varjao Matthew A. Masten Kara E. Rudolph Elizabeth A. Stuart Alexandre Poirier Nick Huntington-Klein Nicolas Apfel Julia Hatamyar Martin Huber Proximity is measured over citations between two papers we both hold, weighted by how heavily one leans on the other, and is symmetric — it does not distinguish citing from being cited. Authors without a profile here are skipped, and a genuinely close colleague can be missing simply because their work is not in our arXiv corpus. Method: docs/06-citations-pipeline.md .
Papers (4 of 54)
AutoSchA: Automatic Hierarchical Music Representations via Multi-Relational Node Isolation
published 2026 · Proceedings of the AAAI Conference on Artificial Intelligence · first circulated 2025
with Stephen Ni-Hahn, Rico Zhu, Jerry Yin, Yue Jiang, Simon Mak, J. H. Yin
Matching Bounds: How Choice of Matching Algorithm Impacts Treatment Effects Estimates and What to Do About It.
published 2025 · The Journal of Politics · 1 citations · first circulated 2020
Multi-site validation of an interpretable model to analyze breast masses
published 2025 · PLoS ONE · 1 citations
with Luke Moffett, Alina Jade Barnett, Jon Donnelly, Fides R. Schwartz, Hari Trivedi, Joseph Y. Lo
working paper 2025 · arXiv
Dimension Reduction with Locally Adjusted Graphs
published 2025 · Proceedings of the AAAI Conference on Artificial Intelligence · 5 citations · first circulated 2024
with Yingfan Wang, Yiyang Sun, Haiyang Huang
How Your Location Relates to Health: Variable Importance and Interpretable Machine Learning for Environmental and Sociodemographic Data
published 2025 · Proceedings of the AAAI Conference on Artificial Intelligence
with Ishaan Maitra, Raymond Lin, Eric Chen, Jon Donnelly, Sanja Šćepanović
A Double Machine Learning Approach for Combining Experimental and Observational Studies
published 2025 · Observational Studies
dame-flame : A Python Package Providing Fast Interpretable Matching for Causal Inference
published 2025 · Journal of Statistical Software · 3 citations · first circulated 2021
Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference
published 2024 · Proceedings of the AAAI Conference on Artificial Intelligence · 2 citations
Sparse Density Trees and Lists: An Interpretable Alternative to High-Dimensional Histograms
published 2024 · INFORMS Journal on Data Science · first circulated 2015
with Siong Thye Goh, Lesia Semenova
working paper 2023 · arXiv · 1 citations
Optimal Sparse Regression Trees
published 2023 · Proceedings of the AAAI Conference on Artificial Intelligence · 8 citations · first circulated 2022
with Rui Zhang, Rui Xin, Margo Seltzer
working paper 2023 · arXiv · 1 citations
Why black box machine learning should be avoided for high-stakes decisions, in brief
published 2022 · Nature Reviews Methods Primers · 95 citations
A Robust Approach to Quantifying Uncertainty in Matching Problems of Causal Inference
published 2022 · INFORMS Journal on Data Science · 11 citations · first circulated 2018
Fast Sparse Decision Tree Optimization via Reference Ensembles
published 2022 · Proceedings of the AAAI Conference on Artificial Intelligence · 27 citations · first circulated 2021
with Hayden McTavish, Chudi Zhong, Reto Achermann, Ilias Karimalis, Jacques Chen, Margo Seltzer
On the Existence of Simpler Machine Learning Models
published 2022 · 2022 ACM Conference on Fairness, Accountability, and Transparency · 72 citations
with Lesia Semenova, Ronald Parr
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effects
published 2022 · INFORMS journal on computing · 14 citations · first circulated 2017
with Tong Wang
Interpretable machine learning: Fundamental principles and 10 grand challenges
published 2022 · Statistics Surveys · 861 citations · first circulated 2021
with Chaofan Chen, Zhi Chen, Haiyang Huang, Lesia Semenova, Chudi Zhong
A case-based interpretable deep learning model for classification of mass lesions in digital mammography
published 2021 · Nature Machine Intelligence · 149 citations
with Alina Jade Barnett, Fides R. Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo
A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations
published 2021 · Decision Support Systems · 59 citations
with Chaofan Chen, Kangcheng Lin, Yaron Shaposhnik, Sijia Wang, Tong Wang
A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results
published 2021 · Management Science · 15 citations · first circulated 2018
with Beau Coker, Gary King
AI reflections in 2019
published 2020 · Nature Machine Intelligence · 6 citations
Reducing Exploration of Dying Arms in Mortal Bandits
published 2019 · Uncertainty in Artificial Intelligence · 3 citations
with Stefano Tracà, Weiyu Yan
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
published 2019 · Nature Machine Intelligence · 9302 citations · first circulated 2018
An Application of Matching After Learning To Stretch (MALTS) to the ACIC 2018 Causal Inference Challenge Data
published 2019 · Observational Studies · 5 citations
This Looks Like That: Deep Learning for Interpretable Image Recognition
published 2019 · Neural Information Processing Systems · 567 citations · first circulated 2018
with Chaofan Chen, Oscar Li, Xiaohui Tao, Alina Jade Barnett, Jonathan K. Su, Chaofan Tao
Learning Optimized Risk Scores
published 2019 · Journal of Machine Learning Research · 53 citations · first circulated 2016
with Berk Ustun
working paper 2018 · arXiv · 5 citations
The Big Data Newsvendor: Practical Insights from Machine Learning
published 2018 · Operations Research · 524 citations · first circulated 2013
with Gah-Yi Ban, GahhYi Vahn, Gah-Yi Vahn
Deep Learning for Case-Based Reasoning Through Prototypes: A Neural Network That Explains Its Predictions
published 2018 · Proceedings of the AAAI Conference on Artificial Intelligence · 418 citations · first circulated 2017
with Oscar Li, Hao Liu, Chaofan Chen
Direct Learning to Rank And Rerank
published 2018 · International Conference on Artificial Intelligence and Statistics · 4 citations
Modeling recovery curves with application to prostatectomy
published 2018 · Biostatistics · 6 citations · first circulated 2015
Learning Certifiably Optimal Rule Lists for Categorical Data
published 2018 · Journal of Machine Learning Research · 108 citations · first circulated 2017
with Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi, Margo Seltzer
Learning Cost-Effective and Interpretable Treatment Regimes
published 2017 · International Conference on Artificial Intelligence and Statistics · 55 citations · first circulated 2016
with Himabindu Lakkaraju
A Computational Model of Inhibition of HIV-1 by Interferon-Alpha
published 2016 · PLoS ONE · 10 citations · first circulated 2015
with Edward P. Browne, Benjamin Letham
The factorized self-controlled case series method: an approach for estimating the effects of many drugs on any outcomes
published 2016 · Journal of Machine Learning Research · 7 citations
with Ramin Moghaddass, David Madigan
no link
A Bayesian Approach to Learning Scoring Systems
published 2015 · Big Data · 11 citations
with Şeyda Ertekin
Supersparse linear integer models for optimized medical scoring systems
published 2015 · Machine Learning · 328 citations
with Berk Ustun
Learning classification models of cognitive conditions from subtle behaviors in the digital Clock Drawing Test
published 2015 · Machine Learning · 179 citations
with William Souillard-Mandar, Randall Davis, Rhoda Au, David J. Libon, Rodney Swenson, Catherine C. Price, Melissa Lamar, Dana L. Penney
Falling Rule Lists
published 2015 · International Conference on Artificial Intelligence and Statistics · 141 citations · first circulated 2014
with Fulton Wang
Generalization bounds for learning with linear, polygonal, quadratic and conic side knowledge
published 2014 · Machine Learning · 2 citations
On combining machine learning with decision making
published 2014 · Machine Learning · 32 citations · first circulated 2011
Approximating the crowd
published 2014 · Data Mining and Knowledge Discovery · 18 citations
with Şeyda Ertekin, Haym Hirsh
Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing
published 2014 · Big Data · 13 citations
Learning about meetings
published 2014 · Data Mining and Knowledge Discovery · 14 citations · first circulated 2013
with Been Kim
Machine learning for science and society
published 2013 · Machine Learning · 116 citations
with Kiri L. Wagstaff
Growing a list
published 2013 · Data Mining and Knowledge Discovery · 14 citations
with Benjamin Letham, Katherine Heller
Sequential event prediction
published 2013 · Machine Learning · 52 citations
with Benjamin Letham, David Madigan
The rate of convergence of AdaBoost
published 2013 · Journal of Machine Learning Research · 36 citations · first circulated 2011
with Indraneel Mukherjee, Robert E. Schapire
How to reverse-engineer quality rankings
published 2012 · Machine Learning · 13 citations
with Allison Chang, Michael Cavaretta, Robert Thomas, Gloria Chou
An Integer Optimization Approach to Associative Classification
published 2012 · Neural Information Processing Systems · 14 citations
with Allison Chang, Dimitris Bertsimas
no link
A process for predicting manhole events in Manhattan
published 2010 · Machine Learning · 55 citations
with Rebecca J. Passonneau, Axinia Radeva, Haimonti Dutta, Steve Ierome, Delfina Isaac
Analysis of boosting algorithms using the smooth margin function
published 2007 · The Annals of Statistics · 30 citations
with Robert E. Schapire, Ingrid Daubechies
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