PANAGIOTIS KONTOPOULOS

Short Bio

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Work

He is currently working as a Research Associate in SCAN with focus on the implementation of Artificial Intelligence to 5G and beyond (5G+) networks. During his career, he has participated in many EU-funded H2020 Projects in the field of Networking, such as 5G-CroCo, 5Growth and CASPER RISE. Namely, in 5Growth he was actively involved in the design and development of AI/ML algorithms towards providing solutions to dynamic resource allocation optimization problems for 5G Networks. Furthermore, he was part of the ESPA-founded project of Pan-Hellenic experimental infrastructure (HELNET), as well as, in 2 cooperation projects concerning distributed AI solutions at the edge of 5G and Beyond Networks, between NKUA and Huawei Technologies Duesseldorf (HWDU) named ‘Distributed pQoS prediction for future wireless networks’ and ‘Beyond 5G, Computation-oriented Communications towards Heterogeneous, Green, AI-aware Networks. Additionally, he participated in the writing of numerous European research proposals for several EU funding programs such as H2020, ELIDEK, ESPA.

Apart from his studies, he takes an interest in traveling, finding new experiences and gaining knowledge when possible.

Welcome to my Personal Page


Fields of Interest

His main fields of interest are Software-Defined Networking (SDN), Software-Defined Wireless Local Area Networking (SDWLAN), distributed systems, mobile communication systems and services in future networks. That is reflected from his background in AI – Reinforcement Learning solutions for resource allocation and management in Radio Access Network in conjunction with Distributed AI solutions for IoT scenarios. Finally, Mr. Panagiotis technical skills include programming languages Java, C++, C, Javascript, AngularJS, React, PHP, Scala, Python and libraries like Scikit-Learn, Pandas, NumPy, SciPy, Tensorflow, Keras, OpenAI-Gym. Also, he has an excellent knowledge of the Discrete Network Simulator 3 (NS-3) with the use of OpenAI-Gym and NR-module, as well as the multi-modal traffic simulator of urban mobility (SUMO).