Education

• Ph.D., Computer Science, Fudan University, China

Research Interests

• Data Mining and Machine Learning
• Information Retrieval
• Bioinformatics

Research Sites

• Bidtellect Laboratory
• Personal Site

Current Sponsored Research

1. 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
2. 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
3. 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
4. FAU Bidtellect Laboratory - Industry Research Collaboration
   • Bidtellect Inc.
   • Lead Lab Director: Xingquan Zhu
   • Amount: $300,000, Duration: 2017-2022

previous sponsored research

Recent Publications

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)

1. 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.
2. 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.
3. 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.

read more

Sponsored Research

USA Funding Agencies

1. RAPID: COVID-19 Coronavirus Testbed and Knowledge Base Construction and Personalized Risk Evaluation
   Xingquan Zhu (PI), Michael DeGiorgio  (Co-PI), and Massimo Caputi (Co-PI)
   Sponsor: National Science Foundation (IIS-2027339)
   Duration: 2020-2021, Amount: $90,000
    
2. III: Medium: Collaborative Research: KMELIN: Knowledge Mining and Embedding Learning for Complex Dynamic Information Networks
   Xingquan Zhu (PI),  Ankur Agarwal (Co-PI), and Dingding Wang (Co-PI)
   Sponsor: National Science Foundation (IIS-1763452)
   Duration: 2018-2022, Amount: $599,983
    
3. MRI: Acquisition of Artificial Intelligence & Deep Learning (AIDL) Training and Research Laboratory
   Xingquan Zhu (PI), Taghi Khoshgoftaar (Co-PI), Dimitris Pados (Co-PI), Hanqi Zhuang (Co-PI), and Laurent Cherubin (Co-PI)
   Sponsor: National Science Foundation (CNS-1828181)
   Duration: 2018-2021, Amount: $652,850
    
4. FAU Bidtellect Laboratory - Industry Research Collaboration
   Xingquan Zhu (Founding Lab Director)
   Sponsor: Bidtellect Inc.
   Duration: 2017-2022, Amount: $300,000
    
5. Real-Time Bidding Price Optimization
   Xingquan Zhu (PI)
   Sponsor: Bidtellect, Inc.
   Duration: 2016 – 2019, Amount: $90,000
    
6. NSF I/UCRC: Application of Common Machine Learning Algorithms for Uses Cases in Auto Industry – Phase 2
   Dingding Wang (PI), Xingquan Zhu (Co-PI), and Borko Furht (Co-PI)
   Sponsor: National Science Foundation (NSF I/UCRC, JM Family Enterprises, Inc.)
   Duration: 2017-2018, Amount: $60,087
     
7. NSF I/UCRC: Machine Learning Algorithms for Uses Cases in Auto Industry
   Xingquan Zhu (PI) and Borko Furht
   Sponsor: National Science Foundation (NSF I/UCRC, JM Family Enterprises, Inc.)
   Duration: 2016 – 2017, Amount: $39,809
    
8. MRI: Acquisition of Big Data Training and Research Laboratory
   Taghi Khoshgoftaar (PI), Ramesh Teegavarapu, Hari Kalva, Xingquan Zhu (Co-PI), and Pierre-Philippe Beaujean
   Sponsor: National Science Foundation (CNS: 1427536)
   Duration: 2014-2017, Amount: $600,000
    
9. PFI:AIR - TT: A Clinical Predictive Model Based Smart Decision Support System for Congestive Obstructive Pulmonary Disease (COPD) related Re-hospitalization
   Ankur Agarwal (PI), Andrew Duffell, Ravi Behara, and Xingquan Zhu (Co-PI)
   Sponsor: National Science Foundation (IIP: 1444949)
   Duration: 2014 – 2016, Amount: $199,594
    
10. RED-CAKE: Novel Data Mining Approaches for Knowledge Based Skill Matching for Employers (research study)
    Xingquan Zhu (PI) and Borko Furht (Co-PI)
    Sponsor: National Science Foundation (NSF I/UCRC, incVersity Inc.)
    Duration: 2014, Amount: $5,000
     
11. Database-centric data analysis of molecular simulations
    Xingquan Zhu (PI)
    Sponsor: National Institutes of Health (subcontract NIH 1R01GM086707-01A1)
    Duration: 2010 – 2015, Amount: $56,319
     
12. Comparative Pancreatic Cancer Study Using Discriminative Gene Regulatory Network
    Xingquan Zhu (PI)
    Sponsor: American Cancer Society Institute Research Grants (ACS-IRG)
    Duration: 2009, Amount: $30,000
     
13. US Army Research, Travel grant
    Xingquan Zhu (PI)
    Sponsor: US Army Research (W911NF-06-1-0270)
    Duration: 2007, Amount: $8,000
     
14. ICHECK: Identifying Deception Data with Impact-Sensitive Instance Ranking
    Xingquan Zhu (PI) and Xindong Wu (Co-PI)
    Sponsor: NSF-EPSCoR (subcontract EPS-0236976)
    Duration: 2005, Amount: $25,000
     
15. Pattern Matching with Wildcards and Length Constraints
    Xindong Wu (PI), Abdullah N. Arslan, and Xingquan Zhu (Co-PI)
    Sponsor: NSF (CCF-0514819)
    Duration: 2005-2008, Amount: $200,000
     

Teaching

Undergraduate Courses   

• ENG 4906 Honors Directed Independent Study
• COT 4900 DIS Independent Study
• STA 4821 Stochastic Models for Computer Science
• CAP 4770 Intro. to Data Mining and Machine Intelligence
• CAP 4630 Intro. to Artificial Intelligence
• CAP 4613 Intro. to Deep Learning
• COT 4400 Design and Analysis of Algorithms
• COP 3813 Intro. to Internet Computing
• CDA 3201 Introduction to Logic Design

Graduate Courses

• COT 7980 Dissertation – Computer Science
• ECM 7980 Dissertation – Computer Engineering
• ECM 6971 Masters’ Thesis - CE
• COT 6970 Masters’ Thesis – Computer Science
• COT 6930 High Performance Computing and Bioinformatics
• COT 6930 Advanced Data Science Capstone
• COT 6905 DIS – Independent Study
• COT 6900 DIS – Independent Study
• CAP 6807 Computational Advertising and Real-Time Data Analytics
• CAP 6777 Web Mining
• CAP 6619 Deep Learning
• CAP 6547 Reinforcement Learning
• CAP 6315 Social Network and Big Data Analytics
• CAP 5615 Introduction to Neural Networks