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.
Case Western Reserve University, Cleveland, OH8/2020 - present
Doctorate of Philosophy in Epidemiology and Biostatistics
Advisor: Dr. Satya Sahoo
Wayne State University, Detroit, MI8/2018 - 12/2019
Master of Science in Biomedical Engineering
Advisor: Dr. Liying Zhang
Eastern Michigan University, Ypsilanti, MI8/2014 – 8/2018
University Honors, Departmental Honors in Statistics and Psychology, and Highest Honors
Bachelor of Science in Psychology and Mathematics with a concentration in Statistics
Sahoo SS, Kobow K, Zhang J, Buchhalter J, Dayyani M, Upadhyaya DP, Prantzalos K, Bhattacharjee M, Blumcke I, Wiebe S, Lhatoo SD. Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records. Scientific Reports, 2022.
Gupta DK, Prantzalos K, Hiller AL, Lobb BM, Chan K, Boyd J, Sahoo SS. Ontology-based, Real-time, Machine learning Informatics System for Parkinson Disease (ORMIS-PD). International Congress of Parkinson’s Disease and Movement Disorders 2022 (poster), 2022.
Prantzalos K, Zhang J, Shafiabadi N, Fernandez-BacaVaca G, Sahoo SS. Epilepsy-Connect: An Integrated Knowledgebase for Characterizing Alterations in Consciousness State of Pharmacoresistant Epilepsy Patients. AMIA Annual Symposium Proceedings, 2022. Feb 21; 2021:1019-1028. PMID: 35308974; PMCID: PMC8861706.
Prantzalos K, Bauman R, Shafiabadi N, Gurski N, Miller J, Fernandez-BacaVaca G, Sahoo SS. Distinguishing Aberrant Brain Network States using Persistent Homology in a Machine Learning Workflow. (In progress)
Theses and Non-Peer-Reviewed Publications
Prantzalos, Katrina, "A machine learning exploration of Human Connectome data" (2018). Senior Honors Theses and Projects. 632. https://commons.emich.edu/honors/632
Prantzalos, Katrina, "The sweet truth: Initial and post-ingestive effects of sugar and protein on taste preferences in rats" (2018). Senior Honors Theses and Projects. 633. https://commons.emich.edu/honors/633
Prantzalos K, Zhang J, Shafiabadi N, Fernandez- BacaVaca G, Sahoo SS. Epilepsy-Connect: An Integrated Knowledgebase for Characterizing Alterations in Consciousness State of Pharmacoresistant Epilepsy Patients. AMIA Annual Symposium Proceedings, 2021.
Zhang J, Bauman R, Shafiabadi N, Gurski N, Fernandez-BacaVaca G, Sahoo SS. Characterizing Brain Network Dynamics using Persistent Homology in Patients with Refractory Epilepsy. AMIA Annual Symposium Proceedings, 2021.
Prantzalos K, A machine learning exploration of Human Connectome data. Eastern Michigan University 38th Annual Undergraduate Symposium, 2018.
Prantzalos K, The sweet truth: Initial and post-ingestive effects of sugar and protein on taste preferences in rats. Eastern Michigan University 38th Annual Undergraduate Symposium, 2018.
Prantzalos K, The Independent and Interactive Effects of Group Size and Activity Level on Metabolic Rate of Gromphadorhina portentosa. Eastern Michigan University 38th Annual Undergraduate Symposium, 2018.
Prantzalos K, Statistical Analysis of a Mouse Olfactory Test. Eastern Michigan University 36th Annual Undergraduate Symposium, 2016.
Teaching Assistant: Computing in Biomedical Health Informatics [Graduate]Spring 2023
Department of Population and Quantitative Health Sciences, Case Western Reserve University
Professor: Dr. Satya Sahoo
American Medical Informatics Association
Women in Machine Learning
- Statistical programming
- Database design and management
- Data management & analysis
- Research/Analysis Methods
- Machine learning
- Statistical learning
- Data mining
- Natural language processing
- Algebraic topology
- Mental health
- Brain-machine interfaces
- Medical robotics
- Computational & Network neuroscience
- Digital Art