Yong Zhuang, Ph.D.
Assistant Professor, Department of Information Sciences & Technologies
Email: [email protected]
Phone: (616) 331-4378
Office: MAK D-2-234
Website: Personal Website
Education
Ph.D., Computer Science, University of Massachusetts Boston, 2021
Semester Schedule
Other office hours by appointment only.
|
Day |
Session Title |
Time |
Location |
|---|---|---|---|
|
Monday |
CIS 371 - 02 |
10:00 A.M - 10:50 A.M. |
MAK - B1124 |
|
Tuesday |
|||
|
Wednesday |
CIS 371 - 02 |
10:00 A.M. - 10:50 A.M. |
MAK - B1124 |
|
Thursday |
|||
|
Friday |
CIS 371 - 02 |
10:00 A.M. - 10:50 A.M. |
MAK - B1124 |
Additional Courses:
Asynchronous Courses: CIS 371 - 01
Biography
Dr. Yong Zhuang’s research focuses on machine learning, data mining, spatiotemporal analysis, time series forecasting, causal inference, and their applications in predictive modeling and decision support. He actively contributes to the academic community as a member of IEEE and ACM and serves on program committees and as a reviewer for leading journals and conferences in data mining and machine learning. At GVSU, he mentors graduate research and has earned several accolades, including an NSF Standard Grant for student travel to IEEE BigData 2024, a College of Computing Seed Funding Award, and a Special Projects Graduate Assistantship (SPGA) Program Funding Award.
Dr. Zhuang teaches courses in web application programming and knowledge discovery and data mining. Outside of his professional work, he enjoys traveling, hiking, photography, and music composition.
Recent Publications
- Thakuria, M., & Zhuang, Y. (2024). Deep Learning Models for Diabetic Retinopathy Detection: A Comparative Study. IEEE International Conference on Big Data, BigData 2024, Washington, DC, USA, December 15-18, 2024, 5078–5081. https://doi.org/10.1109/BIGDATA62323.2024.10825434
- Zhuang, Y., Small, D. L., Flynn, P. D., Palash, W., Islam, S., Chen, P., & Ding, W. (2023). CASTLE: A Cascaded Spatio-Temporal Approach for Long-lead Streamflow Forecasting. IEEE International Conference on Big Data, BigData 2023, Sorrento, Italy, December 15-18, 2023, 1031–1038. https://doi.org/10.1109/BIGDATA59044.2023.10386528
- Zhuang, Y., Almeida, M., Ding, W., Flynn, P. D., Islam, S., & Chen, P. (2022). Widening the Time Horizon: Predicting the Long-Term Behavior of Chaotic Systems. IEEE International Conference on Data Mining, ICDM 2022, Orlando, FL, USA, November 28 - Dec. 1, 2022, 833–842. https://doi.org/10.1109/ICDM54844.2022.00094
- Almeida, M., Zhuang, Y., Ding, W., Crouter, S. E., & Chen, P. (2021). Mitigating Class-Boundary Label Uncertainty to Reduce Both Model Bias and Variance. ACM Trans. Knowl. Discov. Data, 15(2), 27:1-27:18. https://doi.org/10.1145/3429447