Biography

Demetris’ research project is on active neural learning for control coordination for transmission and distribution grid operation stability. He is a member of the AI energy lab and the IEPG group, of the EEMCS department of TU Delft. His research is part of the MEGAMIND program which aims at measuring, gathering, mining, and integrating data for self-management in the edge of the electricity system.

Demetris obtained his master’s degree in robotics, systems, and control from ETH Zurich. His master’s thesis was in optimal learning task paths for neural networks. His bachelor’s degree in electrical engineering was obtained from the University of Cyprus (UCY). His bachelor’s thesis, which received the best thesis of the UCY ECE department 2018 award, was in AC interference on a DESFA natural gas pipeline due to the operation of a 20.8 MW Wind Park.

His work experience includes being a research and development intern at the ABB cyber-physical systems group, developing an AI-assisted chatbot for security testing automation. Additionally, he has worked as a research assistant at the PSM laboratory of UCY, where he created a technical report on the assessment of the loss-of-mains/anti-islanding protection for the Cyprus distribution system.

His journal publications are:

• Chrysostomou, M., Christofides, N., & Chrysostomou, D. (2021). A Novel Machine Learning-Based Load-Adaptive Power Supply System for Improved Energy Efficiency in Datacenters. IEEE Access, 9, 161898-161908.
• Markovic, U., Chrysostomou, D., Aristidou, P., & Hug, G. (2021). Impact of inverter-based generation on islanding detection schemes in distribution networks. Electric Power Systems Research, 190, 106610.
• Chrysostomou, D., Dimitriou, A., Kokkinos, N. D., & Charalambous, C. A. (2020). Short-term electromagnetic interference on a buried gas pipeline caused by critical fault events of a wind park: A realistic case study. IEEE Transactions on Industry Applications, 56(2), 1162-1170.

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