PROFILE

• Experience in large language models and foundation models

• Proven scientific record in developing and applying natural language processing (NLP) and machine learning (ML) methods to retrieve and analyze electronic health records

• Hands on experience of applying Descriptive Statistics, Linear Regression, Logistic Regression, Survival Analysis, Decision Tree, Principal Component Analysis, and Clustering Analysis in biomedicine

• Demonstrated leadership and  teamwork in multidisciplinary collaborations with outcomes researchers, epidemiologists, economists, statisticians, programmers and IT professionals

• Proficient programming skills in Python, Java, SQL, SAS, and R

• Systematic training in medicine with understanding of clinical practice

• Lifelong learner, continuously expanding knowledge and stay updated with the latest advancements in AI, machine learning, statistics, and health informatics

PROFESSIONAL APPOINTMENTS

May 2025 – present  School of Public Health and Emergency Management, Southern University of Science and Technology ,  Associate Professor

May 2022 – April 2025  Department of Biomedical Informatics, School of Medicine, University of Pittsburgh,Tenure-track Assistant Professor

February 2019 – April 2022  Department of Biomedical Informatics, School of Medicine, University of Pittsburgh,Postdoctoral Associate

July 2011 – August 2017  Department of Biomedical Informatics, School of Medicine, University of Pittsburgh,Graduate Student Researcher (20 hours per week)

EDUCATION

August 2011 – December 2018  Intelligent Systems Program, School of Computing and Information, University of Pittsburgh,Ph.D., Intelligent Systems

August 2009 – May 2011  Department of Biostatistics & Bioinformatics, School of Public Health, Emory University,MSPH, Public Health Informatics

September 2006 –  July 2008  Department of Epidemiology & Biostatistics, School of Public Health, Peking University,MS, Epidemiology and Health Statistics

September 2001– July 2006  Health Science Center, Peking University,Bachelor of Medicine, Preventive Medicine

RESEARCH EXPERIENCE

May 2020 – April 2022 (K99), May 2022 – April 2025 (R00)  University of Pittsburgh, School of Medicine, Department of Biomedical Informatics,K99/R00 LM013383 Transfer Learning to Improve the Re-usability of Computable Biomedical Knowledge, Principal Investigator

August 2021 – January 2025  NIH R01LM013509 Automated Surveillance of Overlapping Outbreaks and New Outbreak Diseases, Collaborator (Key personnel)

September 2024 – June 2029  R24GM153920  Models of Infectious Disease Agent Study (MIDAS) Coordination Center, Collaborator

February 2019 – August 2026  CDC U24 OH009077 National Mesothelioma Virtual Bank, Collaborator

August 2013 – August 2017  NIH R01 LM011370 Probabilistic Disease Surveillance, Graduate Student Researcher

January 2013 – March 2017  System for Hospital Adaptive Readmission Prediction and Management, Research Assistant

September 2010 – May 2011  Emory University, School of Public Health, Department of Biostatistics & Bioinformatics,Combining Internal and External Validation Data to Correct for Misclassifications, Research Assistant

June 2010  – August 2010  Centers for Disease Prevention and Control, Atlanta, GA,Actionable Public Health Alerts for Electronic Medical Record Systems, Intern

September 2006 –  January 2009  Peking University, School of Public Health, Beijing, China,Graduate Student Researcher

PUBLICATIONS

Peer-reviewed Journal Articles (* also serve as the corresponding author)

1. John M. Aronis, Ye Ye, Jessi Espino, Harry Hochheiser, Marian G. Michaels, and Gregory F. Cooper. A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases: Algorithm Development and Validation. JMIR Public Health and Surveillance 10 (2024): e57349.

2. Seemran Barapatre, Yuhe Gao, Michael John Becich, Uma R. Chandran, Waqas Amin, Yaming Li, and Ye Ye*. Multiple institutions’ research findings using the National Mesothelioma Virtual Bank. F1000Research. 2024 Sep 11;11:1343.

3. Yuhe Gao, Jacek M. Mazurek, Yaming Li, David Blackley, David N. Weissman, Shirley V. Burton, Waqas Amin, Douglas Landsittel, Michael J. Becich, and Ye Ye*. Industry, occupation, and exposure history of mesothelioma patients in the U.S. National Mesothelioma Virtual Bank, 2006-2022. Environ Res. 2023 Aug 1;230:115085. doi: 10.1016/j.envres.2022.115085. Epub 2023 Mar 23. PMID: 36965810.

4. Ye Ye, Seemran Barapatre, Michael K. Davis, et al. Open-source software sustainability models: Initial white paper from the informatics technology for cancer research sustainability and industry partnership working group. Journal of Medical Internet Research 23, no. 12 (2021): e20028.

5. Ye Ye, Michael M. Wagner, Gregory F. Cooper, et al. A study of the transferability of influenza case detection systems between two large healthcare systems. PLoS One. 2017 April 5; 12(4): e0174970.

6. Ye Ye, Fuchiang Tsui, Michael M. Wagner, et al. Influenza detection from emergency department reports using natural language processing and Bayesian network classifiers. Journal of the American Medical Informatics Association. 2014; 21(5):815-23.

7. Arturo López Pineda, Ye Ye, Shyam Visweswaran, et al. Comparison of machine learning classifiers for influenza detection from emergency department free-text reports. Journal of Biomedical Informatics. 2015; 58:60-9.

8. Fuchiang Tsui, Ye Ye, Victor Ruiz, et al. Automated influenza case detection for public health surveillance and clinical diagnosis using dynamic influenza prevalence method. Journal of Public Health. 2017 Oct 20.

9. Jeffrey P. Ferraro, Ye Ye, Per H. Gesteland, et al. The effects of natural language processing on cross-institutional portability of influenza case detection for disease surveillance. Applied Clinical Informatics. 2017; 8(2):560-80.

10. Jackson, Brian R., Ye Ye, James M. Crawford, et al. The ethics of artificial intelligence in pathology and laboratory medicine: Principles and practice. Academic Pathology.  2021; 8: 2374289521990784.

11. Li Tang, Robert H. Lyles, Ye Ye, et al. Extended matrix and inverse matrix methods utilizing internal validation data when both disease and exposure status are misclassified. Epidemiological Methods. 2013; 2(1):49-66. 2014 Centers for Disease Control and Prevention Best Statistical Science Theoretical Paper

12. John M. Aronis, Nicholas E. Millett, Michael M. Wagner, Fuchiang Tsui, Ye Ye, et al. A Bayesian System to Detect and Characterize Overlapping Outbreaks. Journal of Biomedical Informatics. 2017; 73:171-181. 

13. Elmer V. Bernstam, Paula K. Shireman, Funda Meric-Bernstam, Meredith Zozus, Xiaoqian Jiang, Bradley B. Brimhall, Ashley K. Windham, Susanne Schmidt, Shyam Visweswaran, Ye Ye et al. Artificial intelligence in clinical and translational science research: successes, challenges and opportunities. Clinical and Translational Science (2021).

14. John M. Aronis, Jeffrey P. Ferraro, Per H. Gesteland, Fuchiang Tsui, Ye Ye, et al. A Bayesian approach for detecting a disease that is not being modeled. PLoS one 15, no. 2 (2020): e0229658.

15. Nicholas E. Millett, John M. Aronis, Michael M. Wagner, Fuchiang Tsui, Ye Ye, et al. The design and evaluation of a Bayesian system for detecting and characterizing outbreaks of influenza. Online Journal of Public Health Informatics. 2019; 11(2).

16. Ruhsary Rexit, Fuchiang Tsui, Jeremy Espino, Panos K. Chrysanthis, Sahawut Wesaratchakit, and Ye Ye. An analytics appliance for identifying (near) optimal over-the-counter medicine products as health indicators for influenza surveillance. Information Systems. 2015; 48:151-63.

17.Yanhui Shen, Quanyi Wang, Jiang Wu, Ting Gao, Ye Ye, et al. Analysis on epidemiologic characteristics of scarlet fever from 1949 to 2006 in Beijing. Strait Journal of Preventive Medicine. 2008; 14(2):30-1. 

18.Ye Ye, Hongyuan Wang, and Ying Ji. A study of correlation between infant mortality rate and neonatal death ratio. Maternal and Child Health Care of China. 2009; 31.

Peer-reviewed Conference Papers (* also serve as the corresponding author)

19. Yuhe Gao, Runxue Bao, Yuelyu Ji, Yiming Sun, Chenxi Song, Jeffrey P. Ferraro, Ye Ye*. Transfer Learning with Clinical Concept Embeddings from Large Language. AMIA Summits on Translational Science Proceedings 2025 (2025): 167.

20. Yiming Sun, Runlong Yu, Runxue Bao, Yiqun Xie, Ye Ye and Xiaowei Jia. Domain-Adaptive Continual Meta-Learning for Modeling Dynamical Systems: An Application in Environmental Ecosystems. Proceedings of the 2025 SIAM International Conference on Data Mining (SDM). Pages 297 – 306. https://doi.org/10.1137/1.9781611978520.29

21. Yiming Sun, Yuhe Gao, Runxue Bao, Gregory F. Cooper, Jessi Espino, Harry Hochheiser, Marian G. Michaels, John M. Aronis, Ye Ye*. Online Transfer Learning for RSV Case Detection. In IEEE 12th International Conference on Healthcare Informatics (ICHI), 2024 June (512-521). Best Paper Award (Analyst Track)

22. Yuelyu Ji, Yuhe Gao, Runxue Bao, Qi Li, Disheng Liu, Yiming Sun, and Ye Ye*. Prediction of COVID-19 Patients' Emergency Room Revisit using Multi-Source Transfer Learning. In IEEE 11th International Conference on Healthcare Informatics (ICHI) 2023 June (138-144).

23. Sisi Lu, Ye Ye, Rich Tsui, et al. Feature selection for 30-day heart failure readmission prediction using clinical drug data. NIPS Workshop on Machine Learning for Clinical Data Analysis and Healthcare, Harrahs and Harveys, Lake Tahoe, 2013.

24. Sisi Lu, Ye Ye, Rich Tsui, et al. Domain ontology-based feature reduction for high dimensional drug data and its application to 30-day heart failure readmission prediction. 9th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, Austin, Texas, 2013.

25. Fuchiang Tsui, Lingyun Shi, Victor Ruiz, Amie D. Barda, Ye Ye, et al. Detection of Adverse Drug Reaction from Twitter Data. SMM4H: 2nd Social Media Mining for Health Applications Workshop & Shared Task, Washington, DC, Nov. 4, 2017. http://ceur-ws.org/Vol-1996/paper12.pdf

26. Ruhsary Rexit, Fuchiang Tsui, Jeremy Espino, Sahawut Wesaratchakit, Ye Ye, et al. Using a distributed search engine to identify optimal product sets for use in an outbreak detection system. 8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, Pittsburgh, Pennsylvania, Oct 2012.

Accepted and Working Papers (* also serve as the corresponding author)

1. Runxue Bao, Yiming Sun, Yuhe Gao, Jindong Wang, Qiang Yang, Zhi-Hong Mao, Ye Ye*. A Recent Survey of Heterogeneous Transfer Learning. 2024. Submitted to the Knowledge-Based Systems Journal (Under Revision).  https://arxiv.org/abs/2310.08459 

Peer-reviewed Conference Abstracts (* also serve as the corresponding author)

1. Chenxi Song, Yuhe Gao, RunXue Bao, Yiming Sun, Julianys Tirado Alicea, Ye Ye*, Probabilistic Disease Surveillance Using Large Language Model. Poster abstract accepted and presented at the AMIA 2025 Informatics Summit.

2. John Chenxi Song, Karthika Venugopalan, Yuhe Gao, Michael Becich, Rashidi Hooman, Yingci Liu, Ye Ye*. Assessing the Diagnostic Potential of the Foundation Model Prov-GigaPath for Mesothelioma. Poster abstract accepted by the 2025 Pathology Informatics Summit.

3.Ye Ye*, Qi Li, Andrew Gu, et al. An Empirical Analysis of Deep Transfer Learning for Infectious Disease Case Detection. Nov 2023. AMIA podium abstract.

4. Ye Ye*, Michael Wagner, Gregory Cooper, et al. Bayesian network transfer learning to improve re-usability of computable biomedical knowledge for public health. Poster abstract accepted by Mobilizing Computable Biomedical Knowledge 2nd Annual Meeting in National Institutes of Health - Bethesda, MD, July, 2019.

5. Douglas Hartman, Jean-Eudes Le Douget, Ye Ye, et al. Application of deep learning models on whole slide images uncover new histological markers related to high-risk malignant pleural mesothelioma. 2022 ASCO Annual Meeting I. Journal of Clinical Oncology.

6. John M. Aronis, Nicholas E. Millett, Michael M. Wagner, Fuchiang Tsui, Ye Ye, et al. A method for detecting and characterizing multiple outbreaks of infectious diseases. Online Journal of Public Health Informatics. 2016; 8(1):e5.

7. John M. Aronis, Nicholas E. Millett, Michael M. Wagner, Fuchiang Tsui, Ye Ye, et al. Detecting overlapping outbreaks of influenza. International Society for Disease Surveillance (ISDS) conference, Atlanta, GA, 2016.

8. Victor M. Ruiz, Amie J. Draper, Ye Ye, et al. Use of diagnosis-related groups to predict all-cause pediatric hospital readmission within 30 days after discharge. 2015 AMIA, San Francisco, CA. AMIA Distinguished Poster Award

9. Amie J. Draper, Ye Ye, Victor M. Ruiz, et al. Using laboratory data for prediction of 30-day hospital readmission of pediatric seizure patients. 2014 AMIA, Washington, DC. AMIA Distinguished Poster Award