Xingquan (Hill) Zhu
- Ph.D., Computer Science, Fudan University, China
- Data Mining and Machine Learning
- Information Retrieval
Current Sponsored Research
- RAPID: COVID-19 Coronavirus Testbed and Knowledge Base Construction and Personalized Risk Evaluation
- National Science Foundation (IIS-2027339)
Xingquan Zhu (PI), Michael DeGiorgio
(Co-PI), and Massimo Caputi (Co-PI)
- Amount: $90,000, Duration: 2020-2021
III: Medium: Collaborative Research: KMELIN: Knowledge Mining and Embedding Learning for Complex Dynamic Information Networks
- National Science Foundation (IIS-1763452)
Ankur Agarwal (Co-PI), and Dingding Wang (Co-PI)
- Amount: $599,983, Duration: 2018-2022
MRI: Acquisition of Artificial Intelligence & Deep Learning (AIDL) Training and Research Laboratory
- National Science Foundation (CNS-1828181).
(PI), Taghi Khoshgoftaar (Co-PI), Dimitris Pados (Co-PI), Hanqi Zhuang (Co-PI), and Laurent Cherubin (Co-PI)
- Amount: $652,850, Duration: 2018-2021
- FAU Bidtellect Laboratory - Industry Research Collaboration
- Bidtellect Inc.
- Lead Lab Director: Xingquan Zhu
- Amount: $300,000, Duration: 2017-2022
previous sponsored research
Journal Articles (Peer Reviewed)
Xingquan Zhu, Haicheng Tao, Zhiang Wu, Jie Cao, Kris Kalish, and Jeremy Kayne, "Fraud Prevention in Digital Advertising, Springer Briefs in Computer Science", ISBN 978-3-319-56792-1, 2017.
- Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, "Multiple Structure-View Learning for Graph Classification, IEEE Transactions on Neural Networks and Learning Systems," Accepted, In Press.
- Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Xindong Wu, "Towards Multi-instance Learning with Discriminative Bag Mapping. IEEE Transactions on Knowledge and Data Engineering, Accepted," In Press.
- Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, and Xingquan Zhu, "A Novel Consistent Random Forest Framework: Bernoulli Random Forests, IEEE Transactions on Neural Networks and Learning Systems," Accepted, In Press.