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

Case Western Reserve University, Cleveland, OH

8/2020 - present

Doctorate of Philosophy in Epidemiology and Biostatistics

Advisor: Dr. Satya Sahoo

Wayne State University, Detroit, MI

8/2018 - 12/2019

Master of Science in Biomedical Engineering

Advisor: Dr. Liying Zhang

Eastern Michigan University, Ypsilanti, MI

8/2014 – 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

Publications

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.


In Progress

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

Presentations

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 Experience

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

Professional Organizations

American Medical Informatics Association

Women in Machine Learning

Skills

Python | R | Java | MATLAB | SAS | Git | HTML | CSS | JavaScript | LATEX | Microsoft Office

Research Interests

  • Data
    • Statistical programming
    • Database design and management
    • Data management & analysis
    • Ontologies
  • Research/Analysis Methods
    • Machine learning
    • Statistical learning
    • Data mining
    • Natural language processing
    • Algebraic topology
  • Topics
    • Mental health
    • Brain-machine interfaces
    • Medical robotics
    • Computational & Network neuroscience

Hobbies

  • Crochet
  • Painting
  • Digital Art