Assistant Professor in St.Francis College NLP & Biomedical Informatics Researcher

About me

I am currently an Assistant Professor in the Department of Computer Science and Cybersecurity at St. Francis College, where I teach and mentor students in areas such as data science, artificial intelligence, and software engineering. I earned my Ph.D. in Computer Science from the New Jersey Institute of Technology (NJIT), where I conducted research in the Structural Analysis of Biomedical Ontologies Center (SABOC). SABOC, part of NJIT’s Department of Computer Science, is devoted to exploring the structural and conceptual foundations of biomedical ontologies, including widely used systems such as SNOMED CT, NCIt, NDF-RT, and ChEBI.

My research bridges computer science, biomedical informatics, and artificial intelligence. I focus on applying data mining, natural language processing, and large language models to uncover meaningful patterns and knowledge from biomedical and healthcare datasets. Beyond data-driven approaches, my work also involves ontology engineering—particularly quality assurance methodologies, ontology summarization techniques, change analysis, and the structural study of families of ontologies.

Ultimately, my long-term goal is to advance AI-driven methods that can enhance knowledge discovery, improve healthcare decision-making, and support high-quality biomedical data management. I am passionate about both research and teaching, and I enjoy inspiring students to explore how computing can solve complex, real-world problems in science and medicine.

Publications

2026

• Zhou, S., Voit, C., Zgombic, T. WeLift: An Integrated Bodybuilding and Social Training Mobile Application. IEEE ISAIA 2026, under review
• Zgombic, T., Voit, C., Zhou, S. WeLift: A Smart Fitness Tracking and Social Training Hub. MSCHE Student Poster, under review
• S. Zhou, M. Dehkordi, W. Yao, H. Liu, P. Sen, F. Deek, and Y. Perl, “Enhancing Electronic Health Records Annotation with a Cluster-Focused Combination Algorithm and Interface Terminologies,” in HEALTHINF 2025, Springer, Under Processing.
• M. K. H. Dehkordi, S. Zhou, Y. Perl, F. Deek, H. Zhe, Vipina K Keloth, H. Liu, G. Elhanan, L. Luke, and A.J. Einstein. Curation of a Cardiology Interface Terminology for Highlighting Electronic Health Records Using Machine Learning. BMC Medical Informatics and Decision Making. 2026.

2025

• Zhou, S., Liu, H., Sen, P., Perl, Y., & Dehkordi, M.K. (2025). CFC Annotator: A Cluster-Focused Combination Algorithm for Annotating Electronic Health Records by Referencing Interface Terminology. BIOSTEC : HEALTHINF.

2024

• Kollapally, N.M., Dehkordi, M.K., Perl, Y., Geller, J., Deek, F.P., Liu, H., Keloth, V.K., Elhanan, G., Einstein, A.J., & Zhou, S. (2024). Using clinical entity recognition for curating an interface terminology to aid fast skimming of EHRs. 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 6427-6434.
• Dehkordi, M.K., Zhou, S., Perl, Y., Deek, F.P., Einstein, A.J., Elhanan, G., He, Z., & Liu, H. (2024). Enhancing patient Comprehension: An effective sequential prompting approach to simplifying EHRs using LLMs. 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 6370-6377.
• Liu, H., Zhou, S., Chen, Z., Perl, Y., & Wang, J. (2024). Using Generative Large Language Models for Hierarchical Relationship Prediction in Medical Ontologies. 2024 IEEE 12th International Conference on Healthcare Informatics (ICHI), 248-256.

2023

• Dehkordi, M.K., Zhou, S., Einstein, A.J., Elhanan, G., Perl, Y., Keloth, V.K., Geller, J., & Liu, H. (2023). Using annotation for computerized support for fast skimming of cardiology electronic health record notes. 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 4043-4050. Site-wide configuration
• Keloth, V.K., Zhou, S., Lindemann, L., Zheng, L., Elhanan, G., Einstein, A.J., Geller, J., & Perl, Y. (2023). Mining of EHR for interface terminology concepts for annotating EHRs of COVID patients. BMC Medical Informatics and Decision Making, 23.

2020

• Keloth, V.K., Zhou, S., Einstein, A.J., Elhanan, G., Chen, Y., Geller, J., & Perl, Y. (2020). Generating Training Data for Concept-Mining for an ‘Interface Terminology’ Annotating Cardiology EHRs. 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1728-1735.
• Keloth, V.K., Zhou, S., Lindemann, L., Elhanan, G., Einstein, A.J., Geller, J., & Perl, Y. (2020). Mining Concepts for a COVID Interface Terminology for Annotation of EHRs. 2020 IEEE International Conference on Big Data (Big Data), 3753-3760.

Patent

• “Curating an interface terminology for effective annotation of electronic health records (ehrs) of a medical discipline”, US20230061239A1

For more info

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