Roger Figueroa Quintero
Electronic Engineer with more than 3 years of experience in computer vision research and back-end software development. Solid mathematical knowledge in convolutional networks, recurrent networks, classification based on sparse representation and classic learning methods as boosting, CART, random forest, cascade classification and support vector machines. Expert in design and development of algorithms that require memory optimization, vectorization and parallelization (or concurrence) using low level languages as C/C ++ and cpython and parallel programming models as CUDA, OpenMP, POSIX Threads and SIMD. Strong knowledge in libraries such as OpenCV, CAFFE, Darknet, Eigen3 and QT. Enthusiastic to learn new things. Ability to work independently and as a member of a team.