Muhammad Azaz Farooq

I am a PhD student supervised by Prof. Paolo Bellavista, focusing on autoencoding based anomaly detection real-time IoT, edge and cloud environments. My research addresses the off-the-shelf ML systems in industry by developing tailored, intelligent solutions for real-time monitoring and automation.

I collaborated with Marposs, where I successfuly deployed a real-world version of my system in an industrial environment. My work combines machine learning, data science, edge and cloud computing and domain specific AI to enable faster, scalable, and smarter decision making in a IoT-Edge-Cloud Continuum.