Deligiannakis Antonios

Antonios Deligiannakis is a Professor at the Department of Electronic and Computer Engineering, Technical University of Crete. His research focuses on databases, sensor networks, online analytical processing (OLAP), approximate query processing, and distributed systems. He holds a Ph.D. in Computer Science from the University of Maryland (2005), an M.Sc. from the same institution (2001), and a Diploma in Electrical & Computer Engineering from the National Technical University of Athens (1999).

His career includes postdoctoral work at the University of Athens (2006–2007), a lecturer position there (2007), and an internship at AT&T Labs-Research (2003). He leads the Software Technology and Network Applications Laboratory, contributing to projects like extreme-scale analytics platforms (INFORE) and federated learning systems.

Research areas span IoT workflow optimization, communication-efficient distributed learning, and real-time maritime event detection. His work emphasizes scalability, efficiency, and practical implementations for big data challenges. Courses taught include Structured Programming.

Notable contributions include DAG* algorithms for IoT workflows, federated learning frameworks, and systems for proactive streaming analytics at scale. He has pioneered methods for outlier detection in sensor networks and efficient query processing over distributed streams.