Jie Xu, Ph.D.
Assistant Professor
On This Page
About Jie Xu
My research interests are focused on the intersection of machine learning and health informatics, with a particular emphasis on disease progression subtyping, predictive modeling, and federated learning techniques. Prior to joining UF, I conducted postdoctoral research at Weill Cornell Medicine, working closely with Dr. Fei Wang and Dr. Jyotishman Pathak. I earned my Ph.D. in Electrical Engineering from Xidian University in 2018, during which I participated in a joint doctoral program at the University of Pittsburgh and the University of Texas at Arlington from 2016 to 2018. I am enthusiastic about continuing my research at UF and contributing to healthcare advancement through innovative machine learning approaches.
Accomplishments
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2023 Global Top 80 Chinese Young Female Scholars in Artificial Intelligence
Baidu Talent Program Committee
Teaching Profile
Courses Taught
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GMS7858 – Causal Artificial Intelligence for Health Research
College of Medicine
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GMS6806 – Security and Privacy for Clinical Research
College of Medicine
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PHC7744 – Causal Artificial Intelligence for Health Research
College of Public Health and Health Professions
Research Profile
I have been working on developing novel computational algorithms, including advanced AI methods for analyzing various kinds of healthcare data, including Electronic Health Records (EHRs), medical and pharmacy claims data, and medical imaging data. One research direction that I am pursuing in fundamental AI methods development is patient similarity evaluations, i.e., assessing the clinical similarity between patients based on their medical histories. Such AI-driven approaches can be applied to advance disease surveillance, disease sub-phenotyping, and comparative effectiveness research. I also have strong expertise in predictive modeling, including developing models for various risk predictions, such as mortality, disease onset, and disease state change. Furthermore, I am actively investigating federated learning (FL) techniques, which allow for training an algorithm across multiple decentralized institutions without sharing their data samples. My research has yielded over 30 peer-reviewed publications in both machine learning and health informatics venues, with papers appearing at top-tier artificial intelligence and machine learning conferences such as NeurIPS, AAAI, KDD, IJCAI, at health informatics conferences such as AMIA, as well as at journals such as JHIR, JMIR.
0000-0001-5291-5198
Areas of Interest
- Machine learning and applications
Publications
Academic Articles
Grants
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Artificial Intelligence Passport for Biomedical Research (AIPassportBMR ): Digital Experiential Learning Community for Upskilling in Artificial Intelligence for Biomedical, Behavioral and Clinical Research
Active
- Role:
- Co-Investigator
- Funding:
- NATL INST OF HLTH NIGMS
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Identifying pediatric asthma subtypes using novel privacy-preserving federated machine learning methods
Active
- Role:
- Principal Investigator
- Funding:
- NATL INST OF HLTH NHLBI
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Post-Acute Sequelae of SARS-CoV-2 Infection and Subsequent Disease Progression in Individuals with Alzheimer’s Disease (AD) and Its Related Dementias (ADRD): Influence of the Social and Environmental Determinants of Health
- Role:
- Co-Investigator
- Funding:
- BRIGHAM AND WOMENS HOSPITAL via NATL INST OF HLTH NIA
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Artificial Intelligence and Counterfactually Actionable Responses to End HIV (AICARE-HIV)
Active
- Role:
- Co-Investigator
- Funding:
- NATL INST OF HLTH NIAID
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Utilizing Data from the Electronic Health Record to Understand the Progression Pathway of Alzheimers Disease and Related Dementias
Active
- Role:
- Principal Investigator
- Funding:
- FL DEPT OF HLTH ED ETHEL MOORE ALZHEIMER
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Clinical Characteristics, including History of MI and Stroke, among US Post-Menopausal Women Initiating Treatment with Romosozumab and Other Anti-Osteroporosis Therapies
Active
- Role:
- Principal Investigator
- Funding:
- BENDCARE
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Computational Drug Repurposing for AD/ADRD with Integrative Analysis of Real-World Data and Biomedical Knowledge
- Role:
- Co-Investigator
- Funding:
- WEILL MED COLLEGE OF CORNELL UNIV via NATL INST OF HLTH NIA
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RESEARCHING COVID TO ENHANCE RECOVERY (RECOVER) INITIATIVE
- Role:
- Co-Investigator
- Funding:
- WEILL MED COLLEGE OF CORNELL UNIV via NATL INST OF HLTH NHLBI
Education
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Ph.D.
Xidian University
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M.S.
Xidian University
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B.S.
Xidian University
Contact Details
- Business:
- (352) 627-9467
- Business:
- xujie@ufl.edu
- Business Mailing:
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PO Box 100147
GAINESVILLE FL 32610 - Business Street:
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1889 Museum Rd, Suite 7000
Gainesville FL 32611