Jason Van Hulse

5.7k total citations · 2 hit papers
55 papers, 4.2k citations indexed

About

Jason Van Hulse is a scholar working on Artificial Intelligence, Information Systems and Software. According to data from OpenAlex, Jason Van Hulse has authored 55 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Artificial Intelligence, 26 papers in Information Systems and 12 papers in Software. Recurrent topics in Jason Van Hulse's work include Imbalanced Data Classification Techniques (36 papers), Machine Learning and Data Classification (35 papers) and Software Engineering Research (15 papers). Jason Van Hulse is often cited by papers focused on Imbalanced Data Classification Techniques (36 papers), Machine Learning and Data Classification (35 papers) and Software Engineering Research (15 papers). Jason Van Hulse collaborates with scholars based in United States. Jason Van Hulse's co-authors include Taghi M. Khoshgoftaar, Amri Napolitano, Chris Seiffert, Naeem Seliya, Randall Wald, Andres Folleco, Huanjing Wang, David J. Dittman, Kehan Gao and Lili Zhao and has published in prestigious journals such as Information Sciences, Journal of Systems and Software and IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans.

In The Last Decade

Jason Van Hulse

54 papers receiving 4.0k citations

Hit Papers

RUSBoost: A Hybrid Approach to Alleviating Class Imbalance 2007 2026 2013 2019 2009 2007 400 800 1.2k
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.

  1. RUSBoost: A Hybrid Approach to Alleviating Class Imbalance
    2009 1.3k citations Chris Seiffert, Taghi M. Khoshgoftaar et al. profile →
  2. Experimental perspectives on learning from imbalanced data
    2007 571 citations Jason Van Hulse, Taghi M. Khoshgoftaar et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jason Van Hulse United States 26 2.8k 861 728 468 414 55 4.2k
Amri Napolitano United States 26 2.6k 0.9× 894 1.0× 658 0.9× 484 1.0× 431 1.0× 98 4.0k
Maria Carolina Monard Brazil 17 3.0k 1.1× 768 0.9× 619 0.9× 558 1.2× 109 0.3× 70 4.5k
Ronaldo C. Prati Brazil 17 2.7k 1.0× 568 0.7× 777 1.1× 360 0.8× 102 0.2× 67 4.4k
Victoria López Spain 19 2.5k 0.9× 637 0.7× 567 0.8× 381 0.8× 86 0.2× 70 3.6k
Robert C. Holte Canada 29 3.8k 1.4× 1.0k 1.2× 439 0.6× 1.1k 2.3× 213 0.5× 134 5.5k
Gustavo E. A. P. A. Batista Brazil 20 2.8k 1.0× 466 0.5× 741 1.0× 438 0.9× 100 0.2× 53 4.5k
Mikel Galar Spain 31 4.2k 1.5× 672 0.8× 1.1k 1.5× 1.0k 2.2× 98 0.2× 92 6.5k
Edurne Barrenechea Spain 35 3.6k 1.3× 490 0.6× 687 0.9× 1.1k 2.3× 77 0.2× 91 6.4k
Vasile Palade United Kingdom 34 2.8k 1.0× 420 0.5× 846 1.2× 1.1k 2.4× 70 0.2× 225 5.8k

Countries citing papers authored by Jason Van Hulse

Since Specialization
Citations

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

Fields of papers citing papers by Jason Van Hulse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jason Van Hulse. 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 Jason Van Hulse. The network helps show where Jason Van Hulse may publish in the future.

Co-authorship network of co-authors of Jason Van Hulse

This figure shows the co-authorship network connecting the top 25 collaborators of Jason Van Hulse. A scholar is included among the top collaborators of Jason Van Hulse 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 Jason Van Hulse. Jason Van Hulse 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.
Khoshgoftaar, Taghi M., et al.. (2012). Evaluation of the importance of data pre-processing order when combining feature selection and data sampling. International Journal of Business Intelligence and Data Mining. 7(1/2). 116–116. 8 indexed citations
2.
Hulse, Jason Van, Taghi M. Khoshgoftaar, & Amri Napolitano. (2012). A Novel Noise-Resistant Boosting Algorithm for Class-Skewed Data. 19. 551–557. 4 indexed citations
3.
Khoshgoftaar, Taghi M., et al.. (2011). Robustness of Filter-Based Feature Ranking: A Case Study. The Florida AI Research Society. 12 indexed citations
4.
Wang, Huanjing, Taghi M. Khoshgoftaar, Jason Van Hulse, & Kehan Gao. (2011). METRIC SELECTION FOR SOFTWARE DEFECT PREDICTION. International Journal of Software Engineering and Knowledge Engineering. 21(2). 237–257. 35 indexed citations
5.
Hulse, Jason Van & Taghi M. Khoshgoftaar. (2011). Incomplete-case nearest neighbor imputation in software measurement data. Information Sciences. 259. 596–610. 72 indexed citations
6.
Gao, Kehan, Taghi M. Khoshgoftaar, & Jason Van Hulse. (2010). An Evaluation of Sampling on Filter-Based Feature Selection Methods. The Florida AI Research Society. 6 indexed citations
7.
Khoshgoftaar, Taghi M., Jason Van Hulse, & Amri Napolitano. (2010). Supervised Neural Network Modeling: An Empirical Investigation Into Learning From Imbalanced Data With Labeling Errors. IEEE Transactions on Neural Networks. 21(5). 813–830. 52 indexed citations
8.
Wang, Huanjing, Taghi M. Khoshgoftaar, & Jason Van Hulse. (2010). A Comparative Study of Threshold-Based Feature Selection Techniques. 499–504. 41 indexed citations
9.
Seliya, Naeem, Taghi M. Khoshgoftaar, & Jason Van Hulse. (2009). A Study on the Relationships of Classifier Performance Metrics. 59–66. 167 indexed citations
10.
Hulse, Jason Van, Taghi M. Khoshgoftaar, Amri Napolitano, & Randall Wald. (2009). Feature Selection with High-Dimensional Imbalanced Data. 507–514. 158 indexed citations
11.
Hulse, Jason Van, Taghi M. Khoshgoftaar, & Amri Napolitano. (2009). An empirical comparison of repetitive undersampling techniques. 29–34. 39 indexed citations
12.
Seiffert, Chris, Taghi M. Khoshgoftaar, Jason Van Hulse, & Amri Napolitano. (2008). Building Useful Models from Imbalanced Data with Sampling and Boosting. The Florida AI Research Society. 306–311. 38 indexed citations
13.
Seiffert, Chris, Taghi M. Khoshgoftaar, Jason Van Hulse, & Amri Napolitano. (2008). Improving Learner Performance with Data Sampling and Boosting. 8. 452–459. 5 indexed citations
14.
Seiffert, Chris, Taghi M. Khoshgoftaar, Jason Van Hulse, & Amri Napolitano. (2008). A Comparative Study of Data Sampling and Cost Sensitive Learning. 46–52. 43 indexed citations
15.
Folleco, Andres, Taghi M. Khoshgoftaar, Jason Van Hulse, & Chris Seiffert. (2007). Learning from Software Quality Data with Class Imbalance and Noise.. Software Engineering and Knowledge Engineering. 82(2). 487–94. 2 indexed citations
16.
Hulse, Jason Van, Taghi M. Khoshgoftaar, & Amri Napolitano. (2007). Experimental perspectives on learning from imbalanced data. 935–942. 571 indexed citations breakdown →
17.
Khoshgoftaar, Taghi M., Chris Seiffert, Jason Van Hulse, Amri Napolitano, & Andres Folleco. (2007). Learning with limited minority class data. 348–353. 75 indexed citations
18.
Khoshgoftaar, Taghi M. & Jason Van Hulse. (2006). Multiple Imputation of Software Measurement Data: A Case Study.. Software Engineering and Knowledge Engineering. 220–226. 5 indexed citations
19.
Khoshgoftaar, Taghi M., et al.. (2006). Software Quality Imputation in the Presence of Noisy Data. 484–489. 5 indexed citations
20.
Khoshgoftaar, Taghi M. & Jason Van Hulse. (2005). Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm. Intelligent Data Analysis. 9(6). 589–602. 7 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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