Yong Ge
- Associate Professor, Management Information Systems
- Member of the Graduate Faculty
Contact
- (520) 621-2748
- McClelland Hall, Rm. 430
- Tucson, AZ 85721
- yongge@arizona.edu
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
2024-25 Courses
-
Data Analytics
MIS 464 (Spring 2025) -
Dissertation
MIS 920 (Spring 2025) -
Dsgn Sci Rsrch Methodlgy
MIS 611A (Spring 2025) -
Introduction to Deep Learning
MIS 548 (Spring 2025) -
Dissertation
MIS 920 (Fall 2024)
2023-24 Courses
-
Data Analytics
MIS 464 (Spring 2024) -
Dissertation
MIS 920 (Spring 2024) -
Dsgn Sci Rsrch Methodlgy
MIS 611A (Spring 2024) -
Introduction to Deep Learning
MIS 548 (Spring 2024) -
Dissertation
MIS 920 (Fall 2023) -
Independent Study
MIS 699 (Fall 2023)
2022-23 Courses
-
Dissertation
MIS 920 (Spring 2023) -
Dissertation
MIS 920 (Fall 2022) -
Dsgn Sci Rsrch Methodlgy
MIS 611A (Fall 2022) -
Independent Study
MIS 699 (Fall 2022)
2021-22 Courses
-
Data Analytics
MIS 464 (Spring 2022) -
Dissertation
MIS 920 (Spring 2022) -
Dsgn Sci Rsrch Methodlgy
MIS 611A (Spring 2022) -
Independent Study
MIS 699 (Spring 2022) -
Spcl Top Mngmnt Info Sys
MIS 596A (Spring 2022) -
Dissertation
MIS 920 (Fall 2021) -
Independent Study
MIS 699 (Fall 2021)
2020-21 Courses
-
Business Intelligence
MIS 587 (Spring 2021) -
Data Analytics
MIS 464 (Spring 2021) -
Dissertation
MIS 920 (Spring 2021) -
Dsgn Sci Rsrch Methodlgy
MIS 611A (Spring 2021) -
Dissertation
MIS 920 (Fall 2020)
2019-20 Courses
-
Business Intelligence
MIS 587 (Spring 2020) -
Dissertation
MIS 920 (Spring 2020) -
Big Data Technologies
MIS 584 (Fall 2019) -
Dissertation
MIS 920 (Fall 2019)
2018-19 Courses
-
Business Intelligence
MIS 587 (Spring 2019) -
Dsgn Sci Rsrch Methodlgy
MIS 611A (Fall 2018) -
Master's Report Projects
MIS 696H (Fall 2018)
2017-18 Courses
-
Business Intelligence
MIS 587 (Spring 2018) -
Data Analytics
MIS 464 (Spring 2018) -
Independent Study
MIS 599 (Spring 2018)
2016-17 Courses
-
Business Intelligence
MIS 587 (Spring 2017)
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.
