George Exarchakos is an Assistant Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), affiliated with the EAISI High Tech Systems and the Center for Wireless Technology. His research focuses on P2P computing, data mining, machine learning, network optimization, and swarm intelligence. He holds an MSc in Advanced Computing from Imperial College London and a PhD in P2P Computing from the University of Surrey (2008). Prior to his current role, he conducted postdoctoral research on autonomous networks at TU/e before becoming an Assistant Professor in 2011. Key projects include HiCONNECTS: Heterogeneous Integration for Connectivity and Sustainability (2023–2025) and RHIADA: Reliable Hybrid Intra Aircraft Datanetwork Architectures (2021–2025). His work contributes to UN Sustainable Development Goals related to innovation and infrastructure (Goal 9). Research interests span predictive networks, gossip protocols, overlay networks, and network complexity. Notable publications include studies on beyond-5G networks, avionics communication protocols, and edge computing resource management.
Nikolaos Paterakis is an Assistant Professor of Power System Optimization and Electricity Markets with the Electrical Energy Systems research group at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e). He is the founder and principal investigator of the Electricity Markets & Power System Optimization Laboratory (EMPSOLab) established in 2019, and a member of the Cyber-Physical Systems Center Eindhoven (CPSe). His research focuses on applying optimization and machine learning techniques to power system and electricity market problems, particularly regarding renewable energy integration and smart grid technologies. Dr. Paterakis received his Dipl.Eng. from Aristotle University of Thessaloniki in 2013, followed by a PhD in Industrial Engineering and Management (cum laude) from the University of Beira Interior in 2015. After serving as a post-doctoral fellow at TU/e from 2015-2017 and working as a consultant for the Energy Market Regulatory Authority of Turkey, he was appointed Assistant Professor at TU/e in April 2017. His research spans power system optimization, electricity market design, renewable energy integration, and the application of machine learning techniques to grid management problems. Recent work emphasizes distributed energy resource integration, local electricity markets, congestion management in low-voltage grids, and real-time grid control using advanced optimization techniques. His publications demonstrate a clear trajectory toward increasingly sophisticated methods for managing grid constraints while enabling market participation of distributed energy resources. Dr. Paterakis has received several prestigious awards including IEEE SEGE'15, SEST 2019, and SEST 2020 Best Paper Awards, and recognition as a Best Reviewer for IEEE Transactions on Smart Grid (2015, 2017) and IEEE Transactions on Sustainable Energy (2016). He serves as Associate Editor for multiple journals including IET Renewable Power Generation, IEEE Systems Journal, IEEE Transactions on Intelligent Transportation Systems, and Elsevier's e-Prime. He leads multiple research projects including MEGAMIND (NWO-funded), P2P-TALES (NWO-funded), and the Electricity Markets Game series (TU/e BOOST!-program). His educational contributions include teaching courses on power system analysis and optimization, electricity markets modeling, and developing innovative educational tools for power systems education. In 2021, he was elevated to Senior Member of the IEEE Power & Energy Society.
D.H.J. Epema is a full Professor at the Faculty of Electrical Engineering, Mathematics, and Computer Science at Delft University of Technology (TU Delft), specializing in Data-Intensive Systems . His research focuses on resource management, scheduling algorithms, performance analysis, trust/reputation systems, and blockchain applications in distributed systems. Research Interests: Distributed Systems, Blockchain, IoT, and Trust Management Notable Awards: Best Paper Awards at CCGrid (2010, 2014), MASCOTS (2013), and LCN (2021) Recent Publications emphasize blockchain integration in IoT, energy trading platforms, and decentralized identity systems. His work bridges theoretical frameworks with practical implementations in large-scale systems. Editorial Roles: Editor for ACM (2013–present) and Lecture Notes in Computer Science (2009–present)
Valentin Robu is a Full Professor of Artificial Intelligence for Decentralized Energy Systems at Eindhoven University of Technology (TU/e). He is a Senior Researcher at CWI (National Research Institute for Mathematics and Computer Science, Amsterdam) and holds a visiting appointment at Princeton University's ECE department. His core expertise lies in multi-agent systems and distributed AI, with a focus on applying AI to energy challenges like smart grids, electric vehicle coordination, and renewable integration. He has authored over 150 peer-reviewed publications and won awards such as the 2019 UK Innovation of the Year Award and the 2018 Low Carbon Transport Award. Education and Career: Robu earned his PhD from TU Eindhoven and CWI (2009). Before his current roles, he was an Associate Professor at Heriot-Watt University (UK), a Senior Research Fellow at the University of Southampton, and held visiting roles at Harvard and MIT. He collaborates globally with institutions like MIT, Harvard, and TU Delft. Research Interests: His work addresses challenges in decentralized energy systems, including AI-driven grid optimization, game-theoretic models for renewable integration, and blockchain applications in energy trading. He focuses on ensuring grid stability, fair resource sharing, and sustainable energy access. Awards: In addition to his Innovation and Low Carbon Transport awards, he has been recognized as a 'Best Reviewer' in 2018. His research impacts UN Sustainable Development Goals related to affordable energy and climate action. Grants and Projects: He leads projects like CESI (UK Energy Systems Integration), CEDRI (India Demand Reduction), and ORCA (Offshore Robotics Hub). His work is featured in media outlets like the BBC, Economist, and World Economic Forum. Labs and Teams: He contributes to TU/e's EAISI (Eindhoven AI Systems Institute) and CWI's Intelligent and Autonomous Systems Group. Collaborations span academia and industry, including Scottish Power Energy Networks and Microsoft Research.
Eliya Buyukkaya is a researcher active in the fields of Computer Science , Big Data , and Distributed Computing . Their work focuses on scalable systems, environmental informatics, and data compression techniques. 2025: Crop growth simulations using big data 2021: Bit Plane Slicing for clustering 2018: Video streaming optimization for games 2017: Clustering anomaly detection 2015: Cloud resource selection for HPC Research spans Big Data Analytics , Collaborative Algorithms , and Latency Optimization , emphasizing scalability and efficiency. Their work impacts Environmental Informatics , Game Networking , and High-Performance Computing . Collaborations include experts in Earth Observation and Computer Science , with publications in top-tier venues like Computers and Electronics in Agriculture and PLoS ONE .
Dipti Kapoor Sarmah is a Lecturer specializing in cybersecurity, steganography, and cryptography. Her work bridges theoretical and applied aspects of secure data transmission, digital forensics, and cyber threat mitigation. Current role: Lecturer in Semantics, Cybersecurity & Services Key research areas: Cryptography, Steganography, Phishing analysis, IoT security Her research explores hybrid cryptographic-steganographic systems, gamified cybersecurity education, and innovative approaches to combat MageCart e-skimming attacks using reverse proxy architectures. She has systematically analyzed zero-knowledge protocols (zk-SNARK, zk-STARK, Bulletproofs) for privacy-preserving authentication. Recent publications address pandemic-era phishing trends, consumer IoT security standards, and data mining applications in insurance fraud detection. Her work frequently intersects with artificial intelligence and machine learning techniques for secure image processing. Notable recognition includes the EMMSAD 2025 Best Paper Award for collaborative research on phishing attack ontologies. Her activity spans diverse formats including peer-reviewed journal articles, conference contributions, and systematic literature reviews. With a Scopus h-index of 5 and over 128 citations, her research output spans 2008-2025, showing consistent contributions to cybersecurity, particularly in steganography optimization algorithms and digital forensics.
