Yong Ge
- Associate Professor, Management Information Systems
- Member of the Graduate Faculty
Biography
Dr. Yong Ge received his Ph.D. in Information Technology from Rutgers Business School in 2013. He is currently an Assistant Professor in the Department of Management Information Systems at the University of Arizona. Before joining the University of Arizona, he was an Assistant Professor in the University of North Carolina at Charlotte. His research interests include data mining, machine learning and business analytics. He has published prolifically in refereed journals and conference proceedings, such as IEEE TKDE, ACM TOIS, ACM SIGKDD, and ICIS. His research has been supported in part by the National Science Foundation, National Institutes of Health (NIH), ORAU and UoA.
Degrees
- Ph.D. Information Technology, Rutgers Business School
- Rutgers University, Newark, New Jersey, United States
Work Experience
- University of Arizona (2016 - Ongoing)
- University of North Carolina at Charlotte (2013 - 2016)
Awards
- Eller Dean's Research Award to Associate Professor
- Spring 2023
- Dean’s Research Award (awarded to one Assistant Professor across the college)
- Eller, Spring 2020
- NSF CAREER Award
- Spring 2019
- One of the Best Papers of IEEE ICDM 2018
- IEEE ICDM, Fall 2018
- RDI Faculty Seed Grant
- The University of Arizona RDI, Fall 2018
Interests
Teaching
Business IntelligenceData MiningRecommender Systems
Research
Data MiningMachine LearningBusiness Analytics
Courses
No activities entered.
Scholarly Contributions
Journals/Publications
- Ge, Y., Li, H., & Tuzhilin, A. (2020). Route Recommendations for Intelligent Transportation Services. IEEE Transactions on Knowledge and Data Engineering.
- Zhao, H., Jin, B., Liu, Q., Ge, Y., Chen, E., Zhang, X., & Xu, T. (2020). Voice of Charity: Prospecting the Donation Recurrence & Donor Retention in Crowdfunding. IEEE Transactions on Knowledge and Data Engineering.
- Ge, Y. (2018). Scalable Content-Aware Collaborative Filtering for Location Recommendation. IEEE Transactions on Knowledge and Data Engineering (TKDE).
Proceedings Publications
- Fan, W., Liu, K., Liu, H., Wang, P., Ge, Y., & Fu, Y. (2020, Fall). Diversity-aware Interactive Reinforced Feature Selection. In the IEEE International Conference on Data Mining.
- Lian, D., Wu, Y., Ge, Y., Xie, X., & Chen, E. (2020, Fall). Geography-Aware Sequential Location Recommendation. In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
- Liu, N., Ge, Y., Li, L., Hu, X., Chen, R., & Choi, S. H. (2020, Fall). Explainable Recommender Systems via Resolving Learning Representations. In the 29th ACM International Conference on Information and Knowledge Management.
- Wang, H., Lian, D., & Ge, Y. (2019, Fall). Binarized Collaborative Filtering with Distilling Graph Convolutional Network. In The International Joint Conference on Artificial Intelligence.
- Wu, L., Chen, L., Hong, R., & Ge, Y. (2019, Fall). Personalized Multimedia Item and Key Frame Recommendation. In The International Joint Conference on Artificial Intelligence.
