Rafael Kingeski received his Bachelor’s degree in Electrical Engineering in 2017 and his Master’s degree in Electrical Engineering in 2019, both from the Santa Catarina State University (UDESC). He is currently a professor in the Department of Computer Science at UDESC. His research interests include feature selection methods, machine learning, and applied signal processing.

Dr. Elisa Henning currently works as Associate Professor at the Santa Catarina State University (UDESC). She holds a Master’s degree in Environmental Engineering and a Ph.D. in Production Engineering from the Federal University of Santa Catarina (UFSC). She also has a Master’s degree in Statistics from Universidade Aberta (UAb) in Portugal. Her research interests are in Water Statistics, Applied Statistics, and Statistical Quality Control.

Aleksander S. Paterno received his Bachelor's degree in Electronic and Telecommunications Industrial Engineering from the Federal University of Technology–Paraná (1999) and His Master's and Doctoral degrees in Electrical Engineering and Industrial Informatics from the same university in 2003 and 2007, respectively. He is an associate professor in the Department of Electrical Engineering and a member of its graduate program. In administrative roles, he served as the head of the Department of Electrical Engineering during the management period of 2013–2015. Additionally, he was the Dean of Undergraduate Studies at the Center for Technological Sciences during the management periods of 2016–2020 and pro tempore during 2020–2021. His research focuses on optoelectronic instrumentation systems and their applications, digital signal processing with applications in biomedical engineering, and instrumentation, as well as telecommunications and higher education pedagogy. He is dedicated to the development of fiber optic sensing systems, starting from the design and simulation of sensors to their fabrication in optical fibers. This involves the development of electronic sensors with industrial applications that can be integrated into industrial automation and biomedical engineering environments.