Jie Xu

Jie Xu, Ph.D.

Assistant Professor

Department: MD-HOBI-GENERAL
Business Phone: (352) 627-9467
Business Email: xujie@ufl.edu

About Jie Xu

My research interests are machine learning, health informatics, and the intersection of both, with a particular focus on metric learning, federated learning, and privacy-preserving techniques.

Teaching Profile

Courses Taught
2022-2023
GMS7858 Causal Artificial Intelligence for Health Research

Research Profile

I have been working on developing novel computational algorithms for analyzing various kinds of healthcare data, including Electronic Health Records (EHRs), medical and pharmacy claims data, medical imaging data, etc. One specific research direction that I am pursuing is metric learning. It aims to automatically learn a task-specific distance function to effectively calculate the similarity between the input data. One key aspect I have been working on is evaluating the clinical similarity between pairwise patients according to their historical EHR in a federated environment. Besides this, I also work on privacy-preserving technology like differential privacy in order to further protect patients’ information. Another major research topic that I am working on is to identify the potential subtypes of Alzheimer’s disease and use machine learning models to predict the future incidence of AD using administrative EHR in individuals.

Open Researcher and Contributor ID (ORCID)

0000-0001-5291-5198

Areas of Interest
  • Machine learning and applications

Publications

2023
Early prediction of Alzheimer’s disease and related dementias using real‐world electronic health records
Alzheimer's & Dementia. [DOI] 10.1002/alz.12967.
2023
Impact of Contextual-Level Social Determinants of Health on Newer Antidiabetic Drug Adoption in Patients with Type 2 Diabetes
International Journal of Environmental Research and Public Health. 20(5) [DOI] 10.3390/ijerph20054036.
2022
Algorithmic fairness in computational medicine
eBioMedicine. 84 [DOI] 10.1016/j.ebiom.2022.104250. [PMID] 36084616.
2022
Protocol for the development of a reporting guideline for causal and counterfactual prediction models in biomedicine
BMJ Open. 12(6) [DOI] 10.1136/bmjopen-2021-059715. [PMID] 35725267.
2021
A (DP)\^{} 2SGD: Asynchronous Decentralized Parallel Stochastic Gradient Descent with Differential Privacy
IEEE Transactions on Pattern Analysis and Machine Intelligence.
2021
Federated learning for healthcare informatics
Journal of Healthcare Informatics Research. 5(1)
2021
Federated learning of electronic health records to improve mortality prediction in hospitalized patients with COVID-19: Machine learning approach
JMIR medical informatics. 9(1) [PMID] 33400679.
2020
Data-driven discovery of probable Alzheimer’s disease and related dementia subphenotypes using electronic health records
Learning Health Systems. 4(4) [PMID] 33083543.
2020
Federated patient hashing
. 34(04)
2020
Order-Preserving Metric Learning for Mining Multivariate Time Series
.
2020
Subphenotyping depression using machine learning and electronic health records
Learning health systems. 4(4) [PMID] 33083540.
2019
Orthogonality-Promoting Dictionary Learning via Bayesian Inference
. 33(01)
2019
Robust metric learning on grassmann manifolds with generalization guarantees
. 33(01)
2018
Bilevel distance metric learning for robust image recognition
Advances in neural information processing systems. 31
2018
Compressed multi-scale feature fusion network for single image super-resolution
Signal processing. 146
2018
Multi-Level Metric Learning via Smoothed Wasserstein Distance
.
2018
New robust metric learning model using maximum correntropy criterion
.
2017
Multi-class support vector machine via maximizing multi-class margins
.
2017
Predicting Alzheimer’s disease cognitive assessment via robust low-rank structured sparse model
. 2017
2015
Coupled fisher discrimination dictionary learning for single image super-resolution
.
2015
Similarity constraints-based structured output regression machine: An approach to image super-resolution
IEEE transactions on neural networks and learning systems. 27(12)
2014
Image super-resolution based on sparse representation with joint constraints
.
2014
Image super-resolution using multi-layer support vector regression
.
2013
Image super resolution using Gaussian Process Regression with patch clustering
.
Algorithmic Fairness in Computational Medicine
. [DOI] 10.1101/2022.01.16.21267299.
Development of a federated learning approach to predict acute kidney injury in adult hospitalized patients with COVID-19 in New York City
. [DOI] 10.1101/2021.07.25.21261105. [PMID] 34341802.
Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach (Preprint)
. [DOI] 10.2196/preprints.24207.
Protocol for Development of a Reporting Guideline for Causal and Counterfactual Prediction Models
. [DOI] 10.1101/2021.11.19.21266604.

Grants

Mar 2022 ACTIVE
Clinical Characteristics, including History of MI and Stroke, among US Post-Menopausal Women Initiating Treatment with Romosozumab and Other Anti-Osteroporosis Therapies
Role: Principal Investigator
Funding: BENDCARE
Mar 2022 ACTIVE
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
Oct 2021 ACTIVE
RESEARCHING COVID TO ENHANCE RECOVERY (RECOVER) INITIATIVE
Role: Co-Investigator
Funding: WEILL MED COLLEGE OF CORNELL UNIV via NATL INST OF HLTH NHLBI

Education

Ph.D.
2018 · Xidian University
M.S.
2015 · Xidian University
B.S.
2012 · Xidian University

Contact Details

Phones:
Business:
(352) 627-9467
Emails:
Business:
xujie@ufl.edu
Addresses:
Business Mailing:
2004 MOWRY RD
GAINESVILLE FL 32611