Xingquan (Hill) Zhu

Education

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)
- Xingquan Zhu (PI), 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).
- Xingquan Zhu (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

Book

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.

Journal Articles (Peer Reviewed)

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.