
About
Andrea Morichetta is a University Assistant (Postdoc) at the Institute of Information Systems Engineering, Technische Universität Wien, Austria. He leads research in distributed systems, focusing on the intersection of machine learning and systems design. His work emphasizes edge computing, cloud-native systems, and AI-driven resource management.
Education: PhD in Electrical, Electronics, and Communications Engineering (Politecnico di Torino, 2020), supervised by Prof. Marco Mellia. Visiting researcher at Cisco (2017), AIT (2019).
Research Interests: ML for cloud/edge systems, federated learning, predictive scaling, cybersecurity in distributed environments, and intent-based systems management. Recent work explores multi-dimensional elasticity in stream processing, asynchronous federated learning, and self-referential digital anatomies.
Teaching: Courses include Distributed Systems (VO), Distributed Systems Technologies (VU), and project/seminar courses (SE/PR). Actively supervises bachelor/master theses on topics like federated learning, edge computing, and serverless architectures.
Key Contributions: Developed Polaris scheduler for SLO-aware edge scheduling, FL-SERENADE for network anomaly detection, and RainCloud for IoT swarm coordination. Co-authored over 50 peer-reviewed papers in top venues (IEEE Cloud, SOSE, ICSOC).
Awards: 2019 Best Poster Runner-Up (TMA Paris), 2018 Best Student Paper (ITC Vienna).
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