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. I also have experience developing algorithms that require memory optimization, vectorization, and parallelization (or concurrence) by using parallel programming models such as CUDA, OpenMP, POSIX Threads, and SIMD. My programming skills include C/C++, Python, Matlab, OpenCV, Caffe, TensorFlow, PyTorch, Darknet (YOLO), and some BLAS libraries. I also have experience working with cloud computing on EC2 instances, Docker, data transmission by means of SQS and S3, and video streaming using Amazon Kinesis WebRTC. I am always enthusiastic about learning new skills as well as gaining new knowledge.