Data Science, Health Informatics
Predictive Modeling: Supervised Machine Learning, Feature Selection, Applied Statistics
Knowledge Extraction and Representation: Semantic Web and Ontologies, Applied Natural Language Processing
Quantification of Data Quality
AI Agents and Intelligent Systems
AI-Powered Software and Toolkit Development
To me, data science is a challenge-oriented field. I am interested in discovering research challenges and leveraging cutting-edge technologies or developing new methods to solve real-world problems. I am currently focusing on healthcare-related challenges, especially in transferring data into knowledge and the generalization of health informatics approaches. Meanwhile, I am open to exploring other areas that could be improved from a data perspective.
Shi, J., Zhang, J., & Ge, Y. (2019). CASMI—An Entropic Feature Selection Method in Turing’s Perspective. Entropy, 21(12), 1179. https://doi.org/10.3390/e21121179
Zhang, J., & Shi, J. (2024). Nonparametric clustering of discrete probability distributions with generalized Shannon’s entropy and heatmap. Statistics & Probability Letters, 208, 110070. https://doi.org/10.1016/j.spl.2024.110070
Guo, Y., & Shi, J. (2024). Factors associated with psychological wellbeing in home care older adults with Alzheimer’s disease: A longitudinal analysis. Journal of Applied Gerontology, 43(8), 1069-1081. https://doi.org/10.1177/07334648241231406
Alabbas, M., Shi, J., Guo, Y., Wu, H., Oshobu, I., Castano, M., ... & Sims, O. T. (2025). Prevalence and Trends in Active Smoking Among Adults Living with HCV in the US over the Last Decade: A Population-Level Analysis. Journal of Clinical Medicine, 14(18), 6671. https://doi.org/10.3390/jcm14186671
Liu, L., May, N. S., Hou, Y., Shi, J., Gracely, E. J., Frank, A. L., & Eisen, H. J. (2026). The US diabetes belt and factors explaining the excess risk: Multifactorial modeling and machine learning analysis. Primary care diabetes, 20(1), 99-105. https://doi.org/10.1016/j.pcd.2025.12.001
Shi, J., Zheng, M., Yao, L., & Ge, Y. (2018). Developing a healthcare dataset information resource (DIR) based on Semantic Web. BMC medical genomics, 11(Suppl 5), 102. https://doi.org/10.1186/s12920-018-0411-5
"CASMI" in CRAN: https://cran.r-project.org/package=CASMI
External:
Data Science Core, Mississippi INBRE (5-year, subaward PI)
Developing Innovative Methods for Rapid Characterization of PVS and NVS Function at the Neural Level (Co-PI)
Natural History and Machine Learning-Based Predictive Modeling of PBC-Related Osteoporosis (Consultant)
Risk Stratification and Prognosis of Metabolic Bone Disease in Primary Biliary Cholangitis (Consultant)
A Combined Propensity Score Matching and Machine Learning Approach to Demonstrate the Safety and Efficacy of Statins in Patients with Decompensated Cirrhosis (Consultant)
MSU Internal:
Developing a Machine Learning Tool for Mining Factor Combinations (PI)
Developing Automatic Pipelines and Algorithms to Enable Rapid Learning of COVID-19 Publications (PI)
Mapping Adolescent Emotional Reactivity and Risk for Depression and Anxiety Using Fast Periodic Visual Stimulation (Co-PI)
Peer-reviewed conference papers/abstracts: 9