20242024

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Weslley Pereira applies his expertise in numerical methods and scientific software development to enhance the accuracy and performance of numerical algorithms. At NREL, he focuses on energy-efficient computing through mixed-precision algorithms and strategic use of linear algebra, with a particular emphasis on artificial intelligence (AI) applications. He has also been developing innovative software at NREL, including BBOpt, a library for solving black-box global optimization problems. Weslley joined NREL in 2023, bringing with him experience in designing, developing, and maintaining numerical linear algebra software.

Research Interests

Scientific software

High-performance computing

Mixed precision

Energy-efficient computing

Green AI

Optimization

Professional Experience

Research Associate, University of Colorado Denver (2021–2023)

Education/Academic Qualification

PhD, Computational Modeling, Laboratório Nacional de Computação Científica

Master, Mathematics, Universidade Federal de Juiz de Fora

Bachelor, Computational Science and Engineering, Universidade Federal de Juiz de Fora

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