Smart devices keep getting smarter and are demanding more and more out of the hardware. How can we make sure that these devices are compatible with the artificial intelligence needed to keep them functioning, without having to increase the hardware capacity? This is what Nesma Rezk, Ph.D. in Computer Science and Engineering, has been researching in her dissertation. Nesma Rezk's thesis is about implementing deep learning applications on embedded platforms, which is any type of computer system with a dedicated function, such as a smart watch or an autonomous car. Deep learning is a type of artificial intelligence (AI) technique that teaches computers to learn by example.