Ryan J. Urbanowicz

4.1k total citations · 1 hit paper
60 papers, 1.6k citations indexed

About

Ryan J. Urbanowicz is a scholar working on Artificial Intelligence, Molecular Biology and Genetics. According to data from OpenAlex, Ryan J. Urbanowicz has authored 60 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 25 papers in Molecular Biology and 12 papers in Genetics. Recurrent topics in Ryan J. Urbanowicz's work include Evolutionary Algorithms and Applications (28 papers), Metaheuristic Optimization Algorithms Research (19 papers) and Viral Infectious Diseases and Gene Expression in Insects (12 papers). Ryan J. Urbanowicz is often cited by papers focused on Evolutionary Algorithms and Applications (28 papers), Metaheuristic Optimization Algorithms Research (19 papers) and Viral Infectious Diseases and Gene Expression in Insects (12 papers). Ryan J. Urbanowicz collaborates with scholars based in United States, United Kingdom and New Zealand. Ryan J. Urbanowicz's co-authors include Jason H. Moore, Randal S. Olson, Nathan Bartley, Patryk Orzechowski, William La Cava, Peter Schmitt, Jeff Kiralis, Melissa Meeker, Will N. Browne and Jonathan Fisher and has published in prestigious journals such as Bioinformatics, CHEST Journal and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

Ryan J. Urbanowicz

56 papers receiving 1.6k 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.

Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science

2016 317 citations Randal S. Olson, Ryan J. Urbanowicz et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ryan J. Urbanowicz United States	19	786	460	243	111	83	60	1.6k
José M. Jerez Spain	22	718 0.9×	351 0.8×	52 0.2×	240 2.2×	66 0.8×	71	1.9k
Abubakar Abid United States	12	808 1.0×	569 1.2×	94 0.4×	156 1.4×	46 0.6×	22	2.0k
J. Sunil Rao United States	20	335 0.4×	497 1.1×	165 0.7×	65 0.6×	36 0.4×	77	1.9k
Jasper Snoek United States	19	664 0.8×	808 1.8×	154 0.6×	337 3.0×	182 2.2×	37	2.2k
David Bednarski United States	8	539 0.7×	1.4k 3.0×	99 0.4×	282 2.5×	120 1.4×	9	2.2k
Wenbin Lu United States	27	335 0.4×	345 0.8×	100 0.4×	38 0.3×	20 0.2×	180	2.4k
Sabri Boughorbel Qatar	15	496 0.6×	231 0.5×	40 0.2×	302 2.7×	80 1.0×	46	1.6k
Ying Ju China	15	527 0.7×	751 1.6×	40 0.2×	71 0.6×	112 1.3×	33	1.8k
Nigel Duffy United States	7	920 1.2×	1.2k 2.5×	61 0.3×	363 3.3×	141 1.7×	14	2.3k
Paolo Cazzaniga Italy	19	457 0.6×	501 1.1×	73 0.3×	247 2.2×	194 2.3×	85	1.4k

Countries citing papers authored by Ryan J. Urbanowicz

Since Specialization

Citations

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

Fields of papers citing papers by Ryan J. Urbanowicz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan J. Urbanowicz. 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 Ryan J. Urbanowicz. The network helps show where Ryan J. Urbanowicz may publish in the future.

Co-authorship network of co-authors of Ryan J. Urbanowicz

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

All Works

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20 of 20 papers shown

Moore, Jason H., et al.. (2024). Survival-LCS: A Rule-Based Machine Learning Approach to Survival Analysis. Proceedings of the Genetic and Evolutionary Computation Conference. 431–439. 1 indexed citations

Wong, Emily, Ryan J. Urbanowicz, Tiffani J Bright, et al.. (2024). Advancing LGBTQ+ inclusion in STEM education and AI research. Patterns. 5(6). 101010–101010. 1 indexed citations

Urbanowicz, Ryan J., et al.. (2023). Toward Predicting 30-Day Readmission Among Oncology Patients: Identifying Timely and Actionable Risk Factors. JCO Clinical Cancer Informatics. 7(7). e2200097–e2200097. 5 indexed citations

Blette, Bryan S., Jude Moutchia, Nadine Al‐Naamani, et al.. (2023). Is low-risk status a surrogate outcome in pulmonary arterial hypertension? An analysis of three randomised trials. The Lancet Respiratory Medicine. 11(10). 873–882. 14 indexed citations

Risacher, Shannon L., Jingxuan Bao, Yanbo Feng, et al.. (2023). Comparing Amyloid Imaging Normalization Strategies for Alzheimer’s Disease Classification using an Automated Machine Learning Pipeline. PubMed Central. 2 indexed citations

Kohn, Rachel, Michael O. Harhay, Gary E. Weissman, et al.. (2023). A Data-Driven Analysis of Ward Capacity Strain Metrics That Predict Clinical Outcomes Among Survivors of Acute Respiratory Failure. Journal of Medical Systems. 47(1). 83–83. 1 indexed citations

Gragert, Loren, et al.. (2023). HLA amino acid Mismatch-Based risk stratification of kidney allograft failure using a novel Machine learning algorithm. Journal of Biomedical Informatics. 142. 104374–104374. 3 indexed citations

McClelland, Robyn L., Jude Moutchia, Dina Appleby, et al.. (2023). Heterogeneity of treatment effects by risk in pulmonary arterial hypertension. European Respiratory Journal. 62(1). 2300190–2300190. 5 indexed citations

Taylor, Deanne, Elizabeth Goldmuntz, Laura E. Mitchell, et al.. (2022). Gene-Interaction-Sensitive enrichment analysis in congenital heart disease. BioData Mining. 15(1). 4–4. 2 indexed citations

10.

Ventetuolo, Corey E., Jude Moutchia, Grayson L. Baird, et al.. (2022). Baseline Sex Differences in Pulmonary Arterial Hypertension Randomized Clinical Trials. Annals of the American Thoracic Society. 20(1). 58–66. 12 indexed citations

11.

Min, Jeff, Dina Appleby, Robyn L. McClelland, et al.. (2021). Secular and Regional Trends among Pulmonary Arterial Hypertension Clinical Trial Participants. Annals of the American Thoracic Society. 19(6). 952–961. 15 indexed citations

12.

Urbanowicz, Ryan J., et al.. (2020). A scikit-learn compatible learning classifier system. 1816–1823. 2 indexed citations

13.

Lo, Yancy, Ryan J. Urbanowicz, Randal S. Olson, et al.. (2019). Using Machine Learning on Home Health Care Assessments to Predict Fall Risk. Studies in health technology and informatics. 264. 684–688. 18 indexed citations

14.

Le, Trang T., Ryan J. Urbanowicz, Jason H. Moore, & Brett A. McKinney. (2018). STatistical Inference Relief (STIR) feature selection. Bioinformatics. 35(8). 1358–1365. 50 indexed citations

15.

Urbanowicz, Ryan J., Randal S. Olson, Peter Schmitt, Melissa Meeker, & Jason H. Moore. (2018). Benchmarking relief-based feature selection methods for bioinformatics data mining. Journal of Biomedical Informatics. 85. 168–188. 154 indexed citations

16.

Verma, Shefali S., Anastasia Lucas, Xinyuan Zhang, et al.. (2018). Collective feature selection to identify crucial epistatic variants. BioData Mining. 11(1). 5–5. 21 indexed citations

17.

Urbanowicz, Ryan J., et al.. (2012). GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures. BioData Mining. 5(1). 16–16. 151 indexed citations

18.

Urbanowicz, Ryan J., Jeff Kiralis, Jonathan Fisher, & Jason H. Moore. (2012). Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection. BioData Mining. 5(1). 15–15. 23 indexed citations

19.

Urbanowicz, Ryan J. & Jason H. Moore. (2010). The application of michigan-style learning classifiersystems to address genetic heterogeneity and epistasisin association studies. 195–202. 26 indexed citations

20.

Urbanowicz, Ryan J., Nate Barney, Bill C. White, & Jason H. Moore. (2008). Mask functions for the symbolic modeling of epistasis using genetic programming. PubMed. 2008. 339–346. 2 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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