John Rick Manzanares

John Rick is a mathematics major specializing in Topological Data Analysis (TDA). With a strong foundation in TDA and Data Science, he has contributed to projects like twelve-lead electrocardiogram classification, integrating topological features into classical machine learning methods, and macroplastic object detection using deep learning. John Rick is dedicated to leveraging algebraic topology and machine learning with an intersection to non-mathematical disciplines to develop innovative solutions for real-world challenges. In his free time, he enjoys solving sudoku puzzles, exploring nature, and staying up-to-date with the latest advancements in data science and artificial intelligence.

He is a Marie Skłodowska-Curie Actions Fellow in Doctoral Networks for the GAP Project. This project aims to address the fragility fracture crisis in Europe.

Personal Information

Room 16
Dioscuri Centre in Topological Data Analysis
Institute of Mathematics, PAN
ul. Sniadeckich 8, 00-656 Warsaw
E-mail: jdolormanzanares[at]impan[dot]pl

Other Links

Personal Website: Website
Repository: GitHub
Research Identifier: ORCID
Curriculum Vitae: CV

Publications

1. Ignacio, P.S., Bulauan, J.-A., & Manzanares, J.R. (2020). A Topology Informed Random Forest Classifier for ECG Classification. In 2020 Computing in Cardiology Conference (CinC). 2020 Computing in Cardiology Conference. Computing in Cardiology. https://doi.org/10.22489/cinc.2020.297

Preprints

1. Manzanares, J. R. D. , & Ignacio, P. S. P. (2022). Stable Homology-Based Cycle Centrality Measures for Weighted Graphs. arXiv preprint arXiv:2208.05565.