Robson Parmezan Bonidia: University of Sao Paulo, Brazil Host supervisor and host laboratory: Dr. Ulisses da Rocha, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany Dates: 4 June to 31 August 2023 FEMS Member Society Membership: International Biodeterioration and Biodegradation Society ''I'm a Ph.D. candidate in Computer Science and Computational Mathematics at the University of São Paulo - USP, Brazil. I also have a degree in Information Security Technology from the Faculdade Estadual de Tecnologia de Ourinhos - SP (FATEC - Centro Paula Souza - Brazil), a specialist in Computer Networks and a Master's in Bioinformatics, both from the Federal University of Technology - Paraná (UTFPR), Brazil. Furthermore, I have experience in Computer Science, with an emphasis on artificial intelligence, pattern recognition, metaheuristics, computational biology, and data mining. My objectives are to contribute to society by generating Artificial Intelligence (AI) solutions that directly impact the lives of people who need them. Currently, I have been working on building solutions to democratize AI, specifically Machine Learning (ML) in biology. So far, our studies have generated results applicable to the analysis of biological sequences, demonstrating the considerable potential for substantially decreasing the expertise needed to operate AI/ML pipelines. This support aids researchers in addressing diverse issues, including diseases that profoundly affect human lives, giving biologists and other stakeholders an opportunity for the widespread use of these techniques. During my time in Germany at the Helmholtz Centre for Environmental Research - UFZ, Leipzig, under the guidance of Dr. Ulisses da Rocha, I continued to refine the BioAutoML project. I conducted tests using real-world problems to fine-tune its functionalities, adapting them to address the practical challenges encountered by biologists, microbiologists, and virologists in their everyday work. Supported by the Research & Training Grant from FEMS, I had the valuable opportunity to immerse myself in laboratory settings, working with authentic data and tangible issues. This hands-on experience not only significantly enriched my technical and scientific skills, but also led to the development of a tool that promises to make AI and ML accessible to biologists, microbiologists, virologists, and other stakeholders who lack specialized knowledge in computing, mathematics, and programming.’’ |
