Staff Research Scientist
Research Areas: Data Analytics, Machine Learning, and Deep Learning
Dr. Zhongfang Zhuang joined Visa Research as a Staff Research Scientist in May 2019. Prior to joining Visa, Zhongfang was a Research Assistant at Worcester Polytechnic Institute (WPI). Zhongfang received his Ph.D. in Computer Science from Worcester Polytechnic Institute in 2019. His Ph.D. dissertation titled, “Deep Learning on Attributed Sequences,” focused on modeling user behaviors in the travel business.
As a member of the Data Analytics team, his research interests are in scalable data processing, analytics systems, deep learning and sequence mining. Dr. Zhuang has published papers in several international conferences and journals, including Diabetes Meeting (SDM), Very Large Data Bases (VLDB) and others.
- Zhuang, Z., Kong, X., & Rundensteiner, E. (2019). AMAS: Attention Model for Attributed Sequence Classification. SIAM International Conference on Data Mining, 109-117.
- Zhuang, Z. Kong, X., Rundensteiner, E., Zouaoui, J., & Arora, A. (2019). Attributed Sequence Embedding. IEEE International Conference on Big Data.
- Zhuang, Z., Kong, X., & Rundensteiner, E. (2018). One-Shot Learning on Attributed Sequences. IEEE International Conference on Big Data, 921-930.
- Zhuang, Z., Lei, C., Rundensteiner, E., & Eltabakh, M. (2016). PRO: Preference-Aware Recurring Query Optimization. ACM International on Conference on Information and Knowledge Management, 2191-2196.
- Lei, C., Zhuang, Z., Rundensteiner, E. A., & Eltabakh, M. (2015). Shared execution of recurring workloads in MapReduce. Proceedings of the VLDB Endowment, 8(7), 714–725.
- Lei, C., Zhuang, Z., Rundensteiner, E. A., & Eltabakh, M. Y. (2014). Redoop infrastructure for recurring big data queries. Proceedings of the VLDB Endowment, 7(13), 1589–1592.