SecReSy4You: Young researcher network for security & resilience of critical cyber-physical systems

Marie Skłodowska-Curie Actions (MSCA) Doctoral Network (ID: 101227389)

Role: co-PI. UCY has the coordination of the project.

Critical infrastructures and cyber-physical systems face increasing risks from cyberattacks exploiting vulnerabilities in digital communication networks, embedded hardware, and software. These attacks have far-reaching consequences, including the potential to collect sensitive information, cause physical damage, and endanger human lives. According to the World Economic Forum, the threat of cyberattacks ranks as the second greatest global risk, following environmental disasters. Yet current security measures often address cyber and physical aspects separately, overlooking their interconnection and resulting in limited effectiveness. Academic research, meanwhile, frequently fails to capture real-world industry challenges, with proposed solutions rarely validated in practice. Control systems are essential for critical infrastructures such as electricity and transportation. The main goal of the SecReSy4You project is to train a new generation of researchers-10 Doctoral Candidates (DCs) in cybersecurity and resilience for Cyber-Physical Systems. The DCs will collaborate on modeling threat actors, developing scalable AI-based monitoring and control systems, and designing strategies to ensure long-term CPS protection. Through a comprehensive training program combining technical expertise with transferable skills, they will be well-prepared for careers in this rapidly evolving field. SecReSy4You will drive innovation in CPS security through cutting-edge research, industry collaboration, and the development of practical tools tailored to real-world challenges.

See more details in the project's website.

EDEM: Efficient Distributed Energy Management

Research and Innovation Foundation (RIF) of Cyprus: RESTART Programmes 2016-2020, PHD IN INDUSTRY/1124/0090

Awarded to my PhD student, Evagoras Makridis, to complete his PhD thesis in collaboration with Eletoyia.

The primary objective of EDEM is to foster the creation of energy communities that are resilient and efficient in their integration of distributed energy resources (DERs) into the market. Towards this goal, EDEM aims at developing an operational and market framework that ensures the stability and reliability of the power grid under normal or abnormal conditions. This framework involves the design and development of innovative distributed control and coordination mechanisms, by exploiting advanced intelligence, communication, and control capabilities, under several practical constraints such as communication limitations, computational capabilities, and physical constraints within the system, as well as uncertainties related to generation, demand, and other system parameters.

PV-CLEAN: Advanced Photovoltaic Module Maintenance in Urban Environments

Research and Innovation Foundation (RIF) of Cyprus: RESTART Programmes 2016-2020, BRIDGE2HORIZON (BRIDGE2HORIZON/0823B/0012)

Role: PI.

What if solar panels could take care of themselves? PV-CLEAN is developing smarter and more sustainable ways to keep urban solar panels clean, cool, and performing at their best. The project combines intelligent sensing, automated cleaning, and advanced surface technologies with an innovative idea: reusing water collected from air-conditioning systems instead of relying on fresh water and chemical cleaners. By making photovoltaic installations easier to maintain, more resource-efficient, and better suited to cities, PV-CLEAN aims to help turn every rooftop into a more reliable source of clean energy.

LOVELACE: Advanced Photovoltaic Module Maintenance in Urban Environments

University of Cyprus: Internal research funding

Role: PI

Machine learning (ML) is envisioned to be an important technology in the near future. Traditional ML methods require to collect and train data centrally. However, due to limited wireless communication resources and privacy concerns, devices on the edge often cannot send the collected data to a central agent. Distributed systems have become vital in handling large-scale machine-learning tasks due to their ability to divide workload across multiple agents and complete the tasks within the time limitations imposed by the application (e.g., traffic management in urban areas). However, classical distributed optimization methods often overlook the communication limitations and costs imposed by the communication between these agents, leading to solutions that have suboptimal performance (thus, introducing latency and reducing overall efficiency) or are even infeasible to implement. Integrating communication mechanisms directly into the distributed optimization process can alleviate the detrimental effects of communication limitations, and significantly improve the efficiency of such systems. The main focus of LOVELACE aims to develop efficient algorithms for distributed coordination and optimization that are explicitly designed to be aware of communication constraints. This involves creating methods that can optimize performance in distributed (and decentralized) systems where communication overhead can be a significant bottleneck, particularly in large-scale machine-learning applications.

6G-LEADER: Advancing the physical and Radio Access Network aspects of 6G, such as machine learning-empowered algorithms and disaggregated RAN implementation

Horizon Europe Smart Networks and Services Joint Undertaking (SNS JU) (ID: 101192080)

Role: Technical coordinator.

6G-LEADER is exploring technologies that will make future wireless networks faster, smarter, more reliable, and better able to adapt to the world around them. The project brings together advanced wireless communications, artificial intelligence, smart antenna technologies, and new ways of coordinating connected devices. A key goal is to help networks react intelligently to changing conditions, such as user movement, congestion, interference, or limited connectivity, rather than simply transmitting more data. By combining terrestrial infrastructure with emerging technologies such as reconfigurable smart surfaces and advanced radio techniques, 6G-LEADER aims to enable seamless and efficient connectivity for future applications ranging from autonomous systems and smart cities to industry, transportation, and immersive digital services. In short, the project is helping lay the technological foundations for a more intelligent, flexible, and dependable 6G world.

See more details in the project's website.

MINERVA: Emerging cooperative autonomous systems: Information for control and estimation

HORIZON ERC Grants: ERC-2021-COG (ID: 101044629)

Role: PI

MINERVA studies how teams of intelligent machines, such as robots, drones, vehicles, and other connected autonomous systems, can cooperate effectively when communication is limited and conditions are constantly changing. Instead of treating communication and decision-making as separate problems, MINERVA asks a more fundamental question: which information is actually useful for the task at hand? By developing new methods that tightly connect sensing, communication, estimation, and control, the project aims to help autonomous systems exchange the right information at the right time, rather than simply sending as much data as possible. The long-term vision is to enable smarter, more efficient, and more reliable cooperation among autonomous systems, with potential applications in robotics, transportation, energy systems, and future intelligent infrastructures.

See more details in the project's website.

FINEST TWINS: Smart Cities Centre of Excellence as a joint project between Tallinn University of Technology and Aalto

European Union's Horizon 2020 research and innovation program

Role: Consortium Partner

FINEST TWINS brings researchers, cities, companies, and citizens together to develop and test new solutions for the urban challenges of tomorrow. Built around a close partnership between Tallinn University of Technology (TalTech) and Aalto University, the project established a cross-border FinEst Centre for Smart Cities connecting Estonia and Finland. Its work spans areas that affect urban life every day, including mobility, energy, buildings, governance, and the intelligent use of urban data. Rather than developing technology only in the laboratory, FINEST TWINS emphasizes testing research-based ideas in real cities and turning promising concepts into solutions that can eventually be used elsewhere. The broader vision is simple: to help create cities that are more sustainable, efficient, connected, and people-friendly, while building a lasting bridge between research and real-world urban innovation.

ODYSSEY: Co-design of control and communication systems for wireless networked control systems

Academy of Finland: Research Fellowship for 5 years (acceptance rate: 12%)

Role: PI

ODYSSEY explores how communication and control can be designed together, rather than as two separate systems. In real applications, wireless links can be slow, unreliable, congested, or affected by interference, and these communication problems can directly influence how safely and effectively an autonomous system behaves. ODYSSEY develops new methods that allow connected machines to adapt their decisions to the quality of the communication available, while also allowing the communication network to prioritize the information that matters most for the task. A key application is connected and autonomous vehicles, where cars must exchange information quickly and reliably to coordinate safely at intersections and in traffic. The broader vision is to enable smarter, safer, and more efficient networks of connected machines.

LoLiTA: Low Latency in Time-critical Applications

Aalto University internal seed funding

Role: PI

Develop STEM project on building and controlling a mini Segway in high school

Control Systems Society (CSS) Outreach Fund: Financial resources for projects that will benefit CSS and the controls community in general.

Joint proposal with the University of Uppsala (Sweden) and Norwegian University of Science and Technology (Norway).

Role: co-PI