Dr. Luis Alberto Rabanal Ramirez | Optical Networks Awards | Best Researcher Award

Dr. Luis Alberto Rabanal Ramirez, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Brazil

Dr. Luis Alberto Rabanal Ramirez is an Associate Professor at Universidade Estadual do Norte Fluminense Darcy Ribeiro in Brazil, specializing in engineering and computing. He holds a Degree in Physical Sciences and Mathematics from the National University of Trujillo, Peru, and both a Master’s and PhD in Electrical Engineering from the Pontifical Catholic University of Rio de Janeiro. With post-doctorates from the same institution and the Instituto Militar de Engenharia, Dr. Rabanal has extensive teaching experience, including roles at Centro Universitário Unigama and Universidade Federal Fluminense. His expertise spans Computer Graphics, Programming Languages, Networks, Artificial Intelligence, Genetic Algorithms, Neural Networks, Data Science, and Parallel Programming with CUDA.

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🎓 Academic Background:

Dr. Luis Alberto Rabanal Ramirez holds a Degree in Physical Sciences and Mathematics from the National University of Trujillo, Peru (1999). He earned his Master’s degree (2002) and PhD (2008) in Electrical Engineering from the Pontifical Catholic University of Rio de Janeiro, Brazil. He completed post-doctorates at the same institution (2011) and at the Instituto Militar de Engenharia – IME (2019) in Brazil.

👨‍🏫 Teaching Experience:

Dr. Rabanal has extensive teaching experience, having served as an Undergraduate Professor at Centro Universitário Unigama (2011-2022) and as a Substitute Professor at the Institute of Science and Technology – Computer Sciences, Universidade Federal Fluminense (2023). He is currently an Associate Professor at Universidade Estadual Fluminense Darcy Ribeiro since April 2024.

💻 Professional Expertise:

Dr. Rabanal is experienced in various fields of engineering and computing. His areas of expertise include Computer Graphics, Computer Architecture, Programming Languages (Julia, C++, Python), Networks, Artificial Intelligence, Genetic Algorithms, Neural Networks, Databases, Data Science, Numerical Methods, Mathematical Modeling, and Parallel Programming of GPUs with CUDA.

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