Summary
Roilhi Hernández is an Associate Professor at UNAM with 11 years of experience applying machine learning and deep reinforcement learning to next-generation wireless networks and reconfigurable intelligent surfaces. He holds a PhD in Electronics and Telecommunications and completed postdoctoral work developing PyTorch-based ML pipelines for wireless communications, alongside research on heart sound signal classification using sparse decompositions. Equally comfortable in academia and production, he has led DevOps and full-stack initiatives—containerized deployments with Docker/Kubernetes, CI/CD, and microservices—while building desktop and web apps for institutional automation. His background spans signal processing, MIMO-OFDM communications, and embedded/firmware testing, reflecting a rare blend of theoretical research and hands-on systems engineering. Notably, his interdisciplinary projects include animal behavior detection from audio and international research internships at INRIA and the University of Manitoba, highlighting a track record of collaborative, applied research.
11 years of coding experience
2 years of employment as a software developer
Licenciatura en Ingeniería, Comunicaciones y Electrónica, Licenciatura en Ingeniería, Comunicaciones y Electrónica at Universidad Autónoma de Zacatecas
Electrical and computer engineering., Electrical and computer engineering. at University of Manitoba
Educación Primaria, Interpretación musical, general, Educación Primaria, Interpretación musical, general at CEBAARE
Doctor of Philosophy - PhD, Ingeniería eléctrica, electrónica y de comunicaciones, Doctor of Philosophy - PhD, Ingeniería eléctrica, electrónica y de comunicaciones at Centro de Investigación Científica y de Educación Superior de Ensenada
English, French