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Cynthia D. Rudin

Gilbert, Louis, and Edward Lehrman Distinguished Professor
Computer Science
LSRC D207, Durham, NC 27708

Overview


Cynthia Rudin is a professor of computer science, electrical and computer engineering, statistical science, and biostatistics & bioinformatics at Duke University, and directs the Interpretable Machine Learning Lab. Previously, Prof. Rudin held positions at MIT, Columbia, and NYU. She holds an undergraduate degree from the University at Buffalo, and a PhD from Princeton University. She is the recipient of the 2022 Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI). This award, similar only to world-renowned recognitions, such as the Nobel Prize and the Turing Award, carries a monetary reward at the million-dollar level. She is also a three-time winner of the INFORMS Innovative Applications in Analytics Award, was named as one of the "Top 40 Under 40" by Poets and Quants in 2015, and was named by Businessinsider.com as one of the 12 most impressive professors at MIT in 2015. She is a fellow of the American Statistical Association and a fellow of the Institute of Mathematical Statistics.

She is past chair of both the INFORMS Data Mining Section and the Statistical Learning and Data Science Section of the American Statistical Association. She has also served on committees for DARPA, the National Institute of Justice, AAAI, and ACM SIGKDD. She has served on three committees for the National Academies of Sciences, Engineering and Medicine, including the Committee on Applied and Theoretical Statistics, the Committee on Law and Justice, and the Committee on Analytic Research Foundations for the Next-Generation Electric Grid. She has given keynote/invited talks at several conferences including KDD (twice), AISTATS, CODE, Machine Learning in Healthcare (MLHC), Fairness, Accountability and Transparency in Machine Learning (FAT-ML), ECML-PKDD, and the Nobel Conference. Her work has been featured in news outlets including the NY Times, Washington Post, Wall Street Journal, the Boston Globe, Businessweek, and NPR.

Current Duke Appointments & Affiliations


Gilbert, Louis, and Edward Lehrman Distinguished Professor · 2024 - Present Computer Science, Trinity College of Arts & Sciences
Professor of Computer Science · 2019 - Present Computer Science, Trinity College of Arts & Sciences
Professor of Electrical and Computer Engineering · 2019 - Present Pierre R. Lamond Department of Electrical and Computer Engineering, Pratt School of Engineering
Professor of Mathematics · 2019 - Present Mathematics, Trinity College of Arts & Sciences
Professor of Statistical Science · 2019 - Present Statistical Science, Trinity College of Arts & Sciences
Professor of Biostatistics and Bioinformatics · 2022 - Present Biostatistics & Bioinformatics, Division of Translational Biomedical, Biostatistics & Bioinformatics

Recent News Items


Published May 22, 2026
How a Biologist is Reimagining Agriculture
Published May 20, 2025
A Tool That Helps Predict a Brain-Damaging Seizure
Published March 27, 2025
Six From Duke Named Fellows of the American Association for the Advancement of Science

View All News Items

Recent Scholarly Works


Fast Rashomon Sets of Sparse Rule Sets

Journal article Machine Learning · July 1, 2026 A sparse rule set (SRS) is a small predictive model that is a disjunctive normal form – an “OR of ANDs”. SRS models are understandable to human experts and robust to outliers. Constructing an SRS efficiently has always been one of the fundamental problems ... Full text Cite

Fine Annotation Loss and Top-k Analysis in Interpretable Models for Breast Cancer Prediction

Conference Progress in Biomedical Optics and Imaging Proceedings of SPIE · April 3, 2026 Mammograms provide critical information to radiologists, aiding in the early detection of cancer. We would like to use neural network models to assist radiologists in this challenging and important task, however, these algorithms are “black box” – unable t ... Full text Cite

Second Volume of the Special Issue on: "Artificial Intelligence for Risk Analysis and the Risks of AI".

Journal article Risk analysis : an official publication of the Society for Risk Analysis · March 2026 Full text Cite
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Education


Princeton University · 2004 Ph.D.

External Links


Rudin Lab Website