Jonas Coelho Kasmanas


Jonas Coelho Kasmanas
PhD student

Working Group Microbial Data Science

Department of Environmental Microbiology
Helmholtz Centre for Environmental Research - UFZ
Permoserstr. 15, 04318 Leipzig, Germany

Phone +55 11 95493 2664

Jonas Coelho Kasmanas

Scientific Career

03/2019 present

PhD student - Double-degree in Computer Science between University of Sao Paulo (USP, Sao Paulo, Brazil) and University of Leipzig (Leipzig, Germany).

03/2018 12/2018

Scientific Internship - Bio-inspired computation group Department of Computer Science, Institute of Mathematical and Computer Sciences – ICMC, University of Sao Paulo – USP, Sao Carlos, Brazil.

08/2017 03/2018

Exchange Student - Department of Computer Science, University of Leeds, Leeds, United Kingdom

06/2016 07/2017

Scientific Internship - Medicinal and Computational Chemistry group, Department of Physics and Interdisciplinary Sciences, Sao Carlos Institute of Physics – IFSC, University of Sao Paulo – USP, Sao Carlos, Brazil

02/2014 12/2018

BSC in Physics and Biomolecular Sciences - Sao Carlos Institute of Physics – IFSC, University of Sao Paulo – USP, Sao Carlos, Brazil

Research interests

I am interested in the detection o novel bio-indicators for human dysbiosis based on metagenomic samples from the human microbial Big Data. As a way of identifying the patterns of interest from the microbial Big Data, my work starts with the collection of the human metagenomic samples, and the standardization of its metadata, from public repositories. Once with the relevant dataset, my research involves the development of novel bioinformatics pipelines for the recovery of metagenome-assembled genomes from the raw metagenomic samples. The identification of the bio-indicators is then made by meta-analysis and the creation of Machine Learning classification models optimized through the development of Automated Machine Learning pipelines.


  • T. Brito-Sarracino, M. Rocha dos Santos, E. Freire Antunes, I. Batista de Andrade Santos, J. Coelho Kasmanas and A. C. Ponce de Leon Ferreira de Carvalho, "Explainable Machine Learning for Breast Cancer Diagnosis," 2019 8th Brazilian Conference on Intelligent Systems (BRACIS), Salvador, Brazil, 2019, pp. 681-686, doi: 10.1109/BRACIS.2019.00124.