| 2024 | ICAART | Predicting Major Donor Prospects Using Machine Learning. | Greg Lee, Aishwarya Vaishali Sathyamurthi, Mark Hobbs |
| 2024 | ICAART | Deep and Shallow Machine Learning for Predicting Major Donors. | Greg Lee, Aishwarya Vaishali Sathyamurthi, Mark Hobbs |
| 2023 | ICAART | Automatically Generating Image Segmentation Datasets for Video Games. | David Gregory LeBlanc, Greg Lee |
| 2023 | ICAART | Adding Time and Subject Line Features to the Donor Journey. | Greg Lee, Ajith Kumar Veera Raghavan, Mark Hobbs |
| 2023 | ICAART | Effects of Feature Types on Donor Journey. | Greg Lee, Ajith Kumar Veera Raghavan, Mark Hobbs |
| 2021 | AI | General Deep Reinforcement Learning in NES Games. | David Gregory LeBlanc, Greg Lee |
| 2020 | AI | Machine Learning the Donor Journey. | Greg Lee, Ajith Kumar Veera Raghavan, Mark Hobbs |
| 2020 | ICMLA | Improving the Donor Journey with Convolutional and Recurrent Neural Networks. | Greg Lee, Ajith Kumar Veera Raghavan, Mark Hobbs |
| 2010 | ICIDS | Automated Storytelling in Sports: A Rich Domain to Be Explored. | Greg Lee, Vadim Bulitko |
| 2006 | GECCO | Genetic algorithms for action set selection across domains: a demonstration. | Greg Lee, Vadim Bulitko |
| 2005 | GECCO | GAMM: genetic algorithms with meta-models for vision. | Greg Lee, Vadim Bulitko |
| 2004 | CEC | Automated selection of vision operator libraries with evolutionary algorithms. | Greg Lee, Vadim Bulitko, Ilya Levner |
| 1985 | SIGGRAPH | Solid modeling with hardware (panel session). | Pierre J. Malraison, Gershon Kedem, Greg Lee, Donald Meagher |