Biography
Dr. Andreas Menychtas is an Assistant Professor at the Department of Digital Systems, School of Information and Communication Technologies, University of Piraeus.
He graduated from the School of Electrical and Computer Engineering of the National Technical University of Athens in 2004 and continued his postgraduate and doctoral studies at the same institution. In 2009, he completed his Ph.D. thesis, which focused on the design and implementation of systems, architectures and methodologies for Quality-of-Service assurance in distributed systems and cloud computing environments.
He has taught undergraduate and postgraduate courses related to distributed computing, programming, and information systems development at the University of Piraeus, the National Technical University of Athens, the University of West Attica, and the Hellenic Open University.
His research interests lie in the broader area of modern information system infrastructures, software development, and the Internet of Things. Specifically, his work focuses on the development of cloud-native applications, DevOps practices, as well as the integration and orchestration of autonomous artificial intelligence systems. Dr. Menychtas has participated as a principal investigator, researcher, and engineer in numerous European and national research projects. Within the scope of his research work, he has been extensively involved in Edge Computing, smart cities, software modeling and optimization, machine learning, and the design of innovative e-health solutions, successfully bridging academic research with industrial applications.
The results of his research have been presented in more than 120 publications in scientific journals, international scientific conferences, and book chapters, receiving over 2,500 citations.
Recent publications
69 publications in the lab library
Conversational Agent with Emotional Intelligence for Foreign Language Learning
In 2026 14th International Conference on Information and Education Technology (ICIET). IEEE, pp. 115–119.
Fatigue and Burnout Management in Nursing Staff Using Wearable Data
In 2026 IEEE 39th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, pp. 348–353.
A Methodology for Producing Recursive Medical Forensic Image Analysis Responses Using VLMs
In Digital Forensics and Cyber Crime. Springer Nature Switzerland, pp. 142–157.
Multimodal Affective Modeling in an LLM-based Intelligent Tutoring System for Foreign Language Learning
In Proceedings of Computational Affective Science (CAS) @ LREC 2026. European Language Resources Association (ELRA), pp. 190–200.
A Multimodal Course Digital Twin for Adaptive Academic Planning: Integrating Physiological Stress, Self-Reports, and Academic Context
Computers, 15(6), p. 338.
A Lightweight Machine Learning Framework for Post-Stroke Gait Abnormality Classification Using Wearable Gyroscope Features
Sensors, 26(10), p. 3143.