| 2019 | ICMLA | Learning Curve Estimation with Large Imbalanced Datasets. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2019 | ICTAI | Approximating Learning Curves for Imbalanced Big Data with Limited Labels. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2018 | ICTAI | Building and Interpreting Risk Models from Imbalanced Clinical Data. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2017 | IRI | Modernizing Analytics for Melanoma with a Large-Scale Research Dataset. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2016 | IRI | Predicting Cancer Relapse with Clinical Data: A Survey of Current Techniques. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2016 | ICTAI | Predicting Medical Provider Specialties to Detect Anomalous Insurance Claims. | Richard A. Bauder, Taghi M. Khoshgoftaar, Aaron N. Richter, Matthew Herland |
| 2015 | IRI | A Multi-dimensional Comparison of Toolkits for Machine Learning with Big Data. | Aaron N. Richter, Taghi M. Khoshgoftaar, Sara Landset, Tawfiq Hasanin |
| 2015 | ICTAI | Efficient Modeling of User-Entity Preference in Big Social Networks. | Aaron N. Richter, Michael Crawford, Brian Heredia, Taghi M. Khoshgoftaar |