Cynthia D. Rudin

Gilbert, Louis, and Edward Lehrman Distinguished Professor


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.

Appointments and Affiliations

  • Gilbert, Louis, and Edward Lehrman Distinguished Professor
  • Professor of Computer Science
  • Professor of Electrical and Computer Engineering
  • Professor of Mathematics
  • Professor of Statistical Science
  • Professor of Biostatistics and Bioinformatics

Contact Information

Education

  • Ph.D. Princeton University, 2004

Awards, Honors, and Distinctions

  • AAAS Fellow. American Association for the Advancement of Science. 2024

Courses Taught

  • STA 693: Research Independent Study
  • STA 671D: Theory and Algorithms for Machine Learning
  • STA 393: Research Independent Study
  • MATH 494: Research Independent Study
  • MATH 491: Independent Study
  • ECON 593: Research Independent Study
  • ECE 891: Internship
  • ECE 687D: Theory and Algorithms for Machine Learning
  • ECE 493: Projects in Electrical and Computer Engineering
  • ECE 392: Projects in Electrical and Computer Engineering
  • COMPSCI 671D: Theory and Algorithms for Machine Learning
  • COMPSCI 474: Data Science Competition
  • COMPSCI 394: Research Independent Study
  • COMPSCI 393: Research Independent Study
  • COMPSCI 391: Independent Study

In the News

Representative Publications

  • Karimi Mahabadi, R., D. Lee, A. C. Ogren, C. Daraio, W. Chen, C. Rudin, and L. C. Brinson. “A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching.” Computer Methods in Applied Mechanics and Engineering 449 (February 1, 2026). https://doi.org/10.1016/j.cma.2025.118571.
  • Tang, D., J. Donnelly, A. J. Barnett, L. Semenova, J. Jing, P. Hadar, I. Karakis, et al. “This EEG Looks Like These EEGs: Interpretable Interictal Epileptiform Discharge Detection With ProtoEEG-kNN.” In Lecture Notes in Computer Science, 15973 LNCS:615–25, 2026. https://doi.org/10.1007/978-3-032-05185-1_59.
  • Roumeli, E., S. Azidhak, A. F. Costa, A. Chen, I. Saito, Y. Sun, L. Cate Brinson, C. Rudin, L. S. Schadler, and K. Sprenger. “From biomatter to bioplastics: A perspective on modeling, structure, and data-driven design.” MRS Bulletin 50, no. 11 (November 1, 2025): 1376–90. https://doi.org/10.1557/s43577-025-01001-x.
  • Karimi Mahabadi, R., Z. Chen, A. C. Ogren, H. Zhang, C. Daraio, C. Rudin, and L. C. Brinson. “Graph-based design of irregular metamaterials.” International Journal of Mechanical Sciences 295 (June 1, 2025). https://doi.org/10.1016/j.ijmecsci.2025.110203.
  • Bastawrous, M. V., Z. Chen, A. C. Ogren, C. Daraio, C. Rudin, and L. C. Brinson. “A multiscale design method using interpretable machine learning for phononic materials with closely interacting scales.” Computer Methods in Applied Mechanics and Engineering 440 (May 15, 2025). https://doi.org/10.1016/j.cma.2025.117833.