Angelo M. Tusset | Dynamics | Best Researcher Award

Assoc. Prof. Dr. Angelo M. Tusset | Dynamics | Best Researcher Award

Assoc. Prof. Dr. Angelo M. Tusset, Federal University of Technology ā€“ ParanĆ”, Brazil

Prof. Angelo Marcelo Tusset, born on April 14, 1969, in UniĆ£o da VitĆ³ria, Brazil, is an esteemed academic and researcher with a strong background in mathematics, engineering, and applied sciences. He holds a B.Sc. in Sciences, Mathematics, and Automation Engineering, along with a Masterā€™s degree in Mathematical Modeling and a Ph.D. in Mechanical Engineering. He is currently an Associate Professor at the Federal University of Technology – ParanĆ” (UTFPR), where he contributes to teaching, research, and academic administration. Throughout his career, he has published over 450 articles and made significant contributions to academic journals as an editor and reviewer. He has mentored numerous Ph.D. and Masterā€™s students, making an impact in various fields of engineering, control systems, and mathematical modeling. Prof. Tusset’s diverse expertise and leadership within academia have made him a pivotal figure in Brazil’s higher education landscape. šŸ“ššŸ‘Øā€šŸ«šŸ”¬

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Summary of Suitability for the “Best Researcher Awards”

Prof. Angelo Marcelo Tusset is a highly suitable candidate for the “Best Researcher Awards,” given his extensive contributions to mathematical modeling, optimal control systems, and applied engineering. His prolific academic output, leadership in research, and impactful mentorship align perfectly with the criteria for recognizing outstanding researchers.

EducationĀ 

Prof. Angelo Marcelo Tusset’s educational journey is marked by his diverse academic background in sciences, mathematics, and engineering. He earned his Bachelor’s degrees in Sciences (1995), Mathematics (1996), and Engineering of Automation and Control (2007) from the State Faculty of Philosophy Science and Letters (FAFI) and the University of Contestado (UNC) in Brazil. In 2004, he completed a Master’s degree in Mathematical Modeling at the Northwestern Regional University of the State of Rio Grande do Sul (UNIJUƍ). Prof. Tusset further advanced his studies by obtaining a Ph.D. in Mechanical Engineering from the Federal University of Rio Grande do Sul (UFRGS) in 2008, specializing in optimal control applied to nonlinear vehicle suspension models. His educational path reflects a strong foundation in mathematics and engineering, which has fueled his research and teaching career. šŸŽ“šŸ“ŠšŸ”§

Experience

Prof. Angelo Marcelo Tusset has built an impressive academic career with extensive teaching and research experience. Starting as an Assistant Professor at the University of Contestado (UNC) from 1998 to 2010, he was responsible for teaching a wide range of engineering subjects, including calculus, linear algebra, and statistics. Since 2010, he has been an Associate Professor at the Federal University of Technology – ParanĆ” (UTFPR), where he has contributed to the development of various graduate programs and research projects. He has served as a coordinator for the Graduate Programs in Electrical Engineering (2017-2020) and Production Engineering (2022-present) at UTFPR. He has also guided and mentored numerous Master’s and Ph.D. students, contributing significantly to the academic community. Additionally, he has held important editorial roles, including Associate Editor for prominent journals. šŸ“…šŸ–‹ļøšŸ‘Øā€šŸ’»

Awards and HonorsĀ 

Prof. Angelo Marcelo Tussetā€™s career has been recognized with multiple awards and honors for his exceptional contributions to academia and research. His prolific publishing record, with over 450 articles, has earned him respect in the scientific community. He has been acknowledged for his leadership roles as an academic advisor, guiding numerous successful Ph.D. and Master’s candidates. Prof. Tussetā€™s editorial work, including his involvement with prestigious journals such as the Journal of Mathematics in Engineering, Science, and Aerospace and International Journal of Nonlinear Dynamics and Control, highlights his standing in the field. Furthermore, his recognition extends to his work on the executive committees of the Brazilian Association of Engineering and Sciences Mechanics (ABCM). His expertise in mathematical modeling and control systems has also earned him recognition from funding agencies, including the AraucĆ”ria Foundation. šŸ…šŸ†šŸ“œ

Research FocusĀ 

Prof. Angelo Marcelo Tusset’s research is centered around mathematical modeling, optimal control, and their applications in engineering, particularly in nonlinear systems. His Ph.D. focused on the application of optimal control theory to nonlinear vehicle suspension systems, a field where he has contributed to developing advanced models for improving vehicle dynamics. He has continued to explore nonlinear dynamics, chaos theory, and control systems throughout his career, with applications ranging from automation and robotics to industrial processes. Prof. Tusset’s work also delves into clean technologies for industrial energy management, blending environmental concerns with engineering solutions. He has published extensively in these areas, demonstrating his expertise in both theoretical and applied aspects of engineering. His research serves as a bridge between mathematical theory and practical applications, influencing a wide range of industries. šŸ”¬šŸ§ āš™ļø

Publication Top Notes:

1. Title: Statements on chaos control designs, including a fractional order dynamical system, applied to a ā€œMEMSā€ comb-drive actuator
Year: 2012
Citations: 111
2. Title: A novel strategy for road lane detection and tracking based on a vehicleā€™s forward monocular camera
Year: 2018
Citations: 101
3. Title: An intelligent controller design for magnetorheological damper based on a quarter-car model
Year: 2009
Citations: 98
4. Title: On elimination of chaotic behavior in a non-ideal portal frame structural system, using both passive and active controls
Year: 2013
Citations: 76
5. Title: Chaos control and sensitivity analysis of a double pendulum arm excited by an RLC circuit based nonlinear shaker
Year: 2016
Citations: 75