Cynthia Rudin

22.1k total citations · 4 hit papers
172 papers, 10.1k citations indexed

About

Cynthia Rudin is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Cynthia Rudin has authored 172 papers receiving a total of 10.1k indexed citations (citations by other indexed papers that have themselves been cited), including 92 papers in Artificial Intelligence, 19 papers in Information Systems and 16 papers in Signal Processing. Recurrent topics in Cynthia Rudin's work include Explainable Artificial Intelligence (XAI) (24 papers), Machine Learning and Data Classification (20 papers) and Machine Learning and Algorithms (17 papers). Cynthia Rudin is often cited by papers focused on Explainable Artificial Intelligence (XAI) (24 papers), Machine Learning and Data Classification (20 papers) and Machine Learning and Algorithms (17 papers). Cynthia Rudin collaborates with scholars based in United States, United Kingdom and China. Cynthia Rudin's co-authors include Berk Ustun, Chaofan Chen, Gah‐Yi Ban, David Madigan, Benjamin Letham, Tyler H. McCormick, Joanna Radin, Aaron Fisher, Francesca Dominici and Haiyang Huang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

Cynthia Rudin

161 papers receiving 9.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

2019 4.5k citations Cynthia Rudin Nature Machine Intelligence profile →
Interpretable machine learning: Fundamental principles and 10 grand challenges

2022 440 citations Cynthia Rudin et al. profile →
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model

2015 414 citations Benjamin Letham, Cynthia Rudin et al. profile →
The Big Data Newsvendor: Practical Insights from Machine Learning

2018 301 citations Cynthia Rudin et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Cynthia Rudin United States	38	5.2k	859	728	658	598	172	10.1k
Marco Túlio Ribeiro United States	13	6.4k 1.2×	711 0.8×	1.1k 1.5×	542 0.8×	597 1.0×	22	9.3k
Natalia Díaz-Rodríguez Spain	19	4.2k 0.8×	972 1.1×	782 1.1×	369 0.6×	834 1.4×	49	7.3k
Daniel Molina Spain	26	8.7k 1.7×	666 0.8×	1.2k 1.7×	723 1.1×	651 1.1×	64	13.5k
Siham Tabik Spain	27	3.8k 0.7×	719 0.8×	1.3k 1.8×	275 0.4×	644 1.1×	63	7.6k
Javier Del Ser Spain	47	6.6k 1.3×	1.0k 1.2×	2.1k 2.9×	597 0.9×	852 1.4×	314	14.9k
Andreas Holzinger Austria	54	3.8k 0.7×	1.4k 1.7×	1.0k 1.4×	287 0.4×	551 0.9×	353	11.1k
Grégoire Montavon Germany	23	5.4k 1.0×	530 0.6×	1.7k 2.3×	258 0.4×	240 0.4×	49	10.3k
Sergio Gil-López Spain	21	3.3k 0.6×	654 0.8×	465 0.6×	292 0.4×	635 1.1×	52	6.6k
Raja Chatila France	26	4.1k 0.8×	1.0k 1.2×	1.8k 2.4×	318 0.5×	1.5k 2.5×	102	9.2k
Wojciech Samek Germany	35	5.6k 1.1×	906 1.1×	1.9k 2.7×	259 0.4×	280 0.5×	136	11.7k

Countries citing papers authored by Cynthia Rudin

Since Specialization

Citations

This map shows the geographic impact of Cynthia Rudin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cynthia Rudin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cynthia Rudin more than expected).

Fields of papers citing papers by Cynthia Rudin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cynthia Rudin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cynthia Rudin. The network helps show where Cynthia Rudin may publish in the future.

Co-authorship network of co-authors of Cynthia Rudin

This figure shows the co-authorship network connecting the top 25 collaborators of Cynthia Rudin. A scholar is included among the top collaborators of Cynthia Rudin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Cynthia Rudin. Cynthia Rudin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Zhang, Han, et al.. (2024). Uncertainty quantification of acoustic metamaterial bandgaps with stochastic material properties and geometric defects. Computers & Structures. 305. 107511–107511. 7 indexed citations

Harigaya, Yuriko, David M. Murdoch, David M. Margolis, et al.. (2024). Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation. Genomics Proteomics & Bioinformatics. 22(1). 9 indexed citations

Ding, Cheng, Cynthia Rudin, Ran Xiao, et al.. (2024). Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection Using Eight Million Samples Labeled With Imprecise Arrhythmia Alarms. IEEE Journal of Biomedical and Health Informatics. 28(5). 2650–2661. 3 indexed citations

Ding, Cheng, et al.. (2024). Sparse learned kernels for interpretable and efficient medical time series processing. Nature Machine Intelligence. 6(10). 1132–1144. 4 indexed citations

Banks, David, et al.. (2024). Data Scientists Discuss AI Risks and Opportunities. SHILAP Revista de lepidopterología. 6(3).

Sun, Haoqi, Eric S. Rosenthal, Alexander Volfovsky, et al.. (2024). How many patients do you need? Investigating trial designs for anti‐seizure treatment in acute brain injury patients. Annals of Clinical and Translational Neurology. 11(7). 1681–1690. 2 indexed citations

Zhang, Rui, Rui Xin, Margo Seltzer, & Cynthia Rudin. (2023). Optimal Sparse Regression Trees. Proceedings of the AAAI Conference on Artificial Intelligence. 37(9). 11270–11279. 2 indexed citations

Mak, Simon, et al.. (2023). An Interpretable, Flexible, and Interactive Probabilistic Framework for Melody Generation. 2 indexed citations

Rudin, Cynthia & Joanna Radin. (2019). Why Are We Using Black Box Models in AI When We Don’t Need To? A Lesson From An Explainable AI Competition. SHILAP Revista de lepidopterología. 1(2). 258 indexed citations

10.

Rudin, Cynthia, et al.. (2018). A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results. arXiv (Cornell University). 8 indexed citations

11.

Lakkaraju, Himabindu & Cynthia Rudin. (2017). Learning Cost-Effective and Interpretable Treatment Regimes. International Conference on Artificial Intelligence and Statistics. 166–175. 31 indexed citations

12.

Rudin, Cynthia, et al.. (2015). Falling Rule Lists. International Conference on Artificial Intelligence and Statistics. 1013–1022. 47 indexed citations

13.

Wang, Tong, et al.. (2015). Finding Patterns with a Rotten Core: Data Mining for Crime Series with Cores. Big Data. 3(1). 3–21. 25 indexed citations

14.

Kim, Been, Cynthia Rudin, & Julie Shah. (2014). The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification. DSpace@MIT (Massachusetts Institute of Technology). 27. 1952–1960. 72 indexed citations

15.

Tulabandhula, Theja & Cynthia Rudin. (2014). Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing. Big Data. 2(2). 97–112. 9 indexed citations

16.

Rudin, Cynthia, et al.. (2013). The rate of convergence of AdaBoost. Journal of Machine Learning Research. 14(1). 2315–2347. 21 indexed citations

17.

Ertekin, Şeyda, Haym Hirsh, & Cynthia Rudin. (2012). Selective Sampling of Labelers for Approximating the Crowd. National Conference on Artificial Intelligence. 1 indexed citations

18.

Rudin, Cynthia, et al.. (2012). How to reverse-engineer quality rankings. Machine Learning. 88(3). 369–398. 6 indexed citations

19.

Rudin, Cynthia, et al.. (2011). Sequential Event Prediction with Association Rules. DSpace@MIT (Massachusetts Institute of Technology). 615–634. 29 indexed citations

20.

Rudin, Cynthia, Ingrid Daubechies, & Robert E. Schapire. (2003). On the Dynamics of Boosting. Neural Information Processing Systems. 16. 1101–1108. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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