I am an Electronic Engineer with a Master's Degree in Engineering and more than three years of experience in computer vision research and back-end software development. I have a solid background in convolutional networks, recurrent networks, classification based on sparse representation, and classic learning methods such as boosting, CART, random forest, cascade classification, and support vector machines. Also, I have experience developing algorithms that require memory optimization, vectorization, and parallelization (or concurrence) by using parallel programming models as CUDA, OpenMP, POSIX Threads, and SIMD. My programming skills include C/C++, Python, Matlab, OpenCV, Caffe, TensorFlow, Darknet (YOLO), and some BLAS libraries. I am always enthusiastic about learning new skills as well as gaining new knowledge.