Evguenia Kopylova is the Data Analysis Lead at our company, where she plays a key role in the development of algorithms and graphics tools to identify important relationships within complex omics data, making these insights accessible and valuable to clients. She brings valuable experience in software development for analyzing clinical microbiome and metabolome data, and collaborates with consumer products, pharmaceutical, and biotech companies in microbiome research, providing expertise in longitudinal microbiome-metabolome interactions analysis.
Evguenia is also actively involved in open-source software development for microbiome research. She holds a Doctor of Philosophy (Ph.D.) degree in Computer Science from the University of Lille 1 Sciences and Technology and the National Institute for Research in Digital Science and Technology (Inria), where she developed algorithms for short read sequence alignment using approximate seeds and created SortMeRNA, a widely-used tool for filtering ribosomal RNA from next-generation sequencing (NGS) data.
Prior to her doctoral studies, Evguenia completed a Master’s degree in Computer Science from the Faculty of Engineering at McMaster University, focusing on mathematical models for pattern repetitions and text compression algorithms. She also holds a Bachelor of Science (Honors) degree in Mathematics and Computer Science from McMaster University.
As the Data Analysis Lead, Evguenia combines her skills in computational biology, software development, and data analysis to contribute to our ongoing efforts in microbiome and metabolomics research. Her work helps our team advance in diagnostic analytics and predictive modeling using complex microbiome-metabolome data.
