Advisory Board

Carlos R. B. Azevedo

Carlos R. B. Azevedo, MSc is a Computer Scientist and Owner of
Carlos is an experienced Computational Intelligence specialist in neural and evolutionary computation having researched and developed efficient self-adaptive algorithms for a range of problems such as time series forecasting, image vector quantization, and portfolio optimization.
Since undergraduation, he has authored several research papers and presented them orally at top international and Brazilian conferences in areas such as genetic and evolutionary computation, neural networks, artificial intelligence, and intelligent vision systems.
He coauthored Adaptive Terrain-based Memetic Algorithms, Improving Image Vector Quantization with a Genetic Accelerated K-Means Algorithm, The Application of Qubit Neural Networks for Time Series Forecasting with Automatic Phase Adjustment Mechanism, and Time Series Forecasting with Qubit Neural Networks.
Carlos earned his Bachelor of Computer Science at Universidade Catóica de Pernambuco, Brazil in 2009. He graduated Singularity University in Artificial Intelligence and Robotics, Future Studies and Forecasting, and Biotechnology in 2010. He was a member of the Space Team Project at Singularity University, specifically of the subgroup which researched how to augment robotic autonomy for space exploration through Artificial General Intelligence. He also earned his Certificate of Proficiency in English at the University of Michigan in 2010. He earned his Master of Computer Science at Universidade Federal de Pernambuco, Brazil in 2011 with the Dissertation titled Diversity Generation in Dynamic Multiobjective Optimization by Non-Dominance Landscapes (Portuguese). He is completing his Ph.D. in Computer Engineering at Universidade Estadual de Campinas, Brazil where his research field is natural and biologically-inspired computing.
Watch Ignite Presentation: The Future of Scientific Research. Visit his Facebook page. Read his Google profile, his LinkedIn profile, and his Singularity University profile. Read his blog. Follow his Twitter feed.