About Me

I am a biostatistics and epidemiology Ph.D. student at Case Western Reserve University in the department of Population and Quantitative Health Sciences, advised by Dr. Satya Sahoo. Broadly, I specialize in the use of machine learning applications in the analysis of noisy and heterogeneous clinical data. I have experience with constructing databases, developing web applications, and exploring ontologies for standardizing data in machine learning applications. My research focuses on characterizing aberrant brain network states using algebraic topology in statistical and machine learning workflows. In my current work, we develop learning features using persistent homology applied to high resolution intracranial electroencephalogram (iEEG) data from patients with refractory epilepsy.

Education

Publications

2025
  • Golnari P, Prantzalos K, Hood V, Meskis MA, Isom LL, Wilcox K, Parent JM, Lal D, Lhatoo SD, Goodkin HP, Wirrell EC, Knupp KG, Patel M, Loeb JA, Sullivan JE, Harte-Hargrove L, Fureman BE, Buchhalter J, Sahoo SS. Ontology accelerates few-shot learning capability of large language model: A study in extraction of drug efficacy in a rare pediatric epilepsy. Int J Med Inform. 2025 Sep;201:105942. doi: 10.1016/j.ijmedinf.2025.105942. Epub 2025 Apr 21. PMID: 40311258.
  • Golnari, P., Prantzalos, K., Upadhyaya D., Buchhalter, J., Sahoo S.S. Human in the Loop: Embedding Medical Expert Input in Large Language Models for Clinical Applications. MEDINFO 2025. (Accepted)
  • Prantzalos, K., Golnari, P., Upadhyaya D., Thyagaraj S., Fernandez Baca-Vaca, G., Luders H., Sahoo S.S. Standardized Epilepsy Data Collection and Analysis Leveraging the Four-Dimensional Epilepsy Classification (4D-EC) Framework. MEDINFO 2025. (Accepted)
2024
  • Upadhyaya, D.P., Tarabichi, Y., Prantzalos, K., Ayub, S., Kaelber, D.C. and Sahoo, S.S. Machine learning interpretability methods to characterize the importance of hematologic biomarkers in prognosticating patients with suspected infection. Computers in Biology and Medicine, 183, p.109251.
  • Sivagnanam, S., Yeu, S., Lin, K., Sakai, S., Garzon, F., Yoshimoto, K., Prantzalos, K., Upadhyaya, D.P., Majumdar, A., Sahoo, S.S. and Lytton, W.W. Towards building a trustworthy pipeline integrating Neuroscience Gateway and Open Science Chain. Database, 2024, p.baae023.
  • Prantzalos, K., Upadhyaya, D.P., Golnari, P., Fernandez-BacaVaca, G., Aispuro, G.P., Salehizadeh, S., Thyagaraj, S., Gurski, N. & Sahoo, S.S. Neural mosaics: detecting aberrant brain interactions using algebraic topology and generative artificial intelligence. AMIA 2024 Annual Symposium, November 9–13, San Francisco, CA. (Accepted)
  • Upadhyaya, D.P., Shaikh, A.G., Cakir, G.B., Prantzalos, K., Golnari, P., Ghasia, F.F. & Sahoo, S.S. A 360° view for large language models: Early detection of amblyopia in children using multi-view eye movement recordings. In: Finkelstein J., Moskovitch R., Parimbelli E. (eds) Artificial Intelligence in Medicine. AIME 2024. Lecture Notes in Computer Science, vol 14845. Springer, Cham.
  • Upadhyaya, D.P., Shaikh, A., Prantzalos, K., Golnari, P., Ghasia, F.F. & Sahoo, S.S. Helios: a platform for early childhood amblyopia detection using fixation eye movements. AMIA 2024 Annual Symposium, November 9–13, San Francisco, CA (Poster). (Accepted)
2023
  • Prantzalos, K., Upadhyaya, D., Shafiabadi, N., Fernandez-BacaVaca, G., Gurski, N., Yoshimoto, K., Sivagnanam, S., Majumdar, A. and Sahoo, S.S. MaTiLDA: an integrated machine learning and topological data analysis platform for brain network dynamics. In: PACIFIC SYMPOSIUM ON BIOCOMPUTING 2024 (pp. 65–80).
  • Upadhyaya, D.P., Prantzalos, K., Thyagaraj, S., Shafiabadi, N., Fernandez-BacaVaca, G., Sivagnanam, S., Majumdar, A. and Sahoo, S.S. Machine Learning Interpretability Methods to Characterize Brain Network Dynamics in Epilepsy. medRxiv. 2023.
2022
  • Sahoo, S.S., Kobow, K., Zhang, J., Buchhalter, J., Dayyani, M., Upadhyaya, D.P., Prantzalos, K., Bhattacharjee, M., Blumcke, I., Wiebe, S. and Lhatoo, S.D. Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records. Scientific Reports, 12(1), p.19430.
2021
  • Prantzalos, K., Zhang, J., Shafiabadi, N., Fernandez-BacaVaca, G. and Sahoo, S.S. Epilepsy-Connect: An Integrated Knowledgebase for Characterizing Alterations in Consciousness State of Pharmacoresistant Epilepsy Patients. AMIA Annual Symposium Proceedings, 2021:1019–1028. PMID: 35308974; PMCID: PMC8861706.

Under Review


Theses and Non-Peer-Reviewed Publications

Presentations

Professional Experience

Teaching Experience

Skills

Contact

Email: Katrina.prantzalos@case.edu

Location: Cleveland, OH