Noah Simon

9.1k total citations · 4 hit papers
77 papers, 4.5k citations indexed

About

Noah Simon is a scholar working on Statistics and Probability, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Noah Simon has authored 77 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Statistics and Probability, 23 papers in Artificial Intelligence and 10 papers in Molecular Biology. Recurrent topics in Noah Simon's work include Statistical Methods and Inference (26 papers), Statistical Methods in Clinical Trials (11 papers) and Bayesian Methods and Mixture Models (7 papers). Noah Simon is often cited by papers focused on Statistical Methods and Inference (26 papers), Statistical Methods in Clinical Trials (11 papers) and Bayesian Methods and Mixture Models (7 papers). Noah Simon collaborates with scholars based in United States, France and South Africa. Noah Simon's co-authors include Trevor Hastie, Robert Tibshirani, Rob Tibshirani, J. Friedman, Jerome H. Friedman, Daniela Witten, Richard H. Simon, Vladimir Jojic, Rodolphe Thiébaut and Mark M. Davis and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Circulation and Journal of the American Statistical Association.

In The Last Decade

Noah Simon

74 papers receiving 4.4k citations

Hit Papers

Regularization Paths for Cox's Proportional Hazards Model... 2011 2026 2016 2021 2011 2012 2013 2011 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Noah Simon United States 22 1.2k 990 678 602 509 77 4.5k
Jing Lei China 37 900 0.8× 447 0.5× 838 1.2× 804 1.3× 245 0.5× 160 4.8k
Berthold Lausen Germany 34 855 0.7× 496 0.5× 475 0.7× 518 0.9× 366 0.7× 101 5.2k
Mary J. Lindstrom United States 43 1.2k 1.0× 1.0k 1.0× 578 0.9× 725 1.2× 345 0.7× 126 8.9k
Shuangge Ma United States 41 2.3k 1.9× 2.0k 2.0× 826 1.2× 323 0.5× 530 1.0× 334 7.3k
Yufeng Liu China 34 1.0k 0.9× 997 1.0× 997 1.5× 260 0.4× 310 0.6× 281 4.6k
Mei‐Ling Ting Lee United States 29 2.0k 1.7× 878 0.9× 338 0.5× 236 0.4× 1.0k 2.0× 103 5.2k
Balasubramanian Narasimhan United States 30 2.4k 2.0× 296 0.3× 559 0.8× 409 0.7× 733 1.4× 67 5.5k
Donglin Zeng United States 41 603 0.5× 2.4k 2.5× 585 0.9× 289 0.5× 173 0.3× 328 6.2k
Matthias Schmid Germany 42 1.1k 0.9× 773 0.8× 704 1.0× 381 0.6× 155 0.3× 321 6.6k
David Faraggi Israel 32 532 0.4× 720 0.7× 481 0.7× 488 0.8× 249 0.5× 83 4.9k

Countries citing papers authored by Noah Simon

Since Specialization
Citations

This map shows the geographic impact of Noah Simon'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 Noah Simon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Noah Simon more than expected).

Fields of papers citing papers by Noah Simon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Noah Simon. 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 Noah Simon. The network helps show where Noah Simon may publish in the future.

Co-authorship network of co-authors of Noah Simon

This figure shows the co-authorship network connecting the top 25 collaborators of Noah Simon. A scholar is included among the top collaborators of Noah Simon 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 Noah Simon. Noah Simon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Simon, Noah, et al.. (2025). Thrifty wide-context models of B cell receptor somatic hypermutation. eLife. 14. 3 indexed citations
2.
Brody, Jennifer A., Christine T. Fong, Jacob E. Sunshine, et al.. (2024). Predicting Out-of-Hospital Cardiac Arrest in the General Population Using Electronic Health Records. Circulation. 150(2). 102–110. 5 indexed citations
3.
Kiên, Nguyễn Trung, et al.. (2024). Survival Prediction via Deep Attention-Based Multiple-Instance Learning Networks with Instance Sampling. Proceedings of the AAAI Symposium Series. 2(1). 482–489.
5.
6.
Elmer, Jonathan, Michael C. Kurz, Patrick J. Coppler, et al.. (2023). Time to Awakening and Self-Fulfilling Prophecies After Cardiac Arrest. Critical Care Medicine. 51(4). 503–512. 12 indexed citations
7.
Simon, S., Alison E. Fohner, Noah Simon, et al.. (2022). The Impact of Time Horizon on Classification Accuracy: Application of Machine Learning to Prediction of Incident Coronary Heart Disease. JMIR Cardio. 6(2). e38040–e38040. 5 indexed citations
8.
Richie-Halford, Adam, Manjari Narayan, Noah Simon, Jason D. Yeatman, & Ariel Rokem. (2021). Groupyr: Sparse Group Lasso in Python. The Journal of Open Source Software. 6(58). 3024–3024. 3 indexed citations
9.
Moraes, Marcos H. de, FoSheng Hsu, Dustin E. Bosch, et al.. (2021). An interbacterial DNA deaminase toxin directly mutagenizes surviving target populations. eLife. 10. 31 indexed citations
10.
Mayer-Hamblett, Nicole, David P. Nichols, Katherine Odem‐Davis, et al.. (2021). Evaluating the Impact of Stopping Chronic Therapies after Modulator Drug Therapy in Cystic Fibrosis: The SIMPLIFY Clinical Trial Study Design. Annals of the American Thoracic Society. 18(8). 1397–1405. 40 indexed citations
11.
Williamson, Brian D., Peter B. Gilbert, Noah Simon, & Marco Carone. (2021). A General Framework for Inference on Algorithm-Agnostic Variable Importance. Journal of the American Statistical Association. 118(543). 1645–1658. 36 indexed citations
12.
VanDevanter, Donald R., N. Hamblett, Noah Simon, Joseph McIntosh, & Michael W. Konstan. (2020). Evaluating assumptions of definition-based pulmonary exacerbation endpoints in cystic fibrosis clinical trials. Journal of Cystic Fibrosis. 20(1). 39–45. 13 indexed citations
13.
Williamson, Brian D., Peter B. Gilbert, Marco Carone, & Noah Simon. (2020). Nonparametric variable importance assessment using machine learning techniques. Biometrics. 77(1). 9–22. 54 indexed citations
14.
Magaret, Craig A., David Benkeser, Brian D. Williamson, et al.. (2019). Prediction of VRC01 neutralization sensitivity by HIV-1 gp160 sequence features. PLoS Computational Biology. 15(4). e1006952–e1006952. 27 indexed citations
15.
Feng, Jean, Brian D. Williamson, Noah Simon, & Marco Carone. (2018). Nonparametric variable importance using an augmented neural network with multi-task learning. International Conference on Machine Learning. 1496–1505. 2 indexed citations
16.
Genereux, Diane P., Jamie M. Goodson, Noah Simon, et al.. (2017). Epigenetic memory via concordant DNA methylation is inversely correlated to developmental potential of mammalian cells. PLoS Genetics. 13(11). e1007060–e1007060. 13 indexed citations
17.
Witten, Daniela, et al.. (2015). Convex Modeling of Interactions With Strong Heredity. Figshare. 22 indexed citations
18.
Sisternes, Luís de, Noah Simon, Robert Tibshirani, Theodore Leng, & Daniel L. Rubin. (2014). Quantitative SD-OCT Imaging Biomarkers as Indicators of Age-Related Macular Degeneration Progression. Investigative Ophthalmology & Visual Science. 55(11). 7093–7093. 112 indexed citations
19.
Simon, Noah & Richard H. Simon. (2013). Adaptive enrichment designs for clinical trials. Biostatistics. 14(4). 613–625. 131 indexed citations
20.
Bien, Jacob, Noah Simon, & Rob Tibshirani. (2012). A lasso for hierarchical testing of interactions. arXiv (Cornell University). 4 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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