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Building AI-enabled Digital Twin frameworks for Industry 4.0 that also used MLOps practices to automate and monitor the real-time analystics and predict anomalies. 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 S.p.A., where I successfuly deployed my proposed Digital Twin framework. 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.
My research focuses on autoencoding techniques for anomaly detection in real-time edge, cloud, and IoT environments.My research focuses on autoencoding techniques for anomaly detection in real-time edge, cloud, and IoT environments.
Vai al Curriculum
