Research

My research

My research asks when advanced control algorithms and data-driven methods can rely on simplified models and when real applications require richer representations. I develop optimal-control frameworks and data-driven methods for cyber-physical and hybrid systems at both device and system levels, and evaluate them through simulation and application-focused studies. This work spans hydrogen production and storage, renewable energy systems, energy management, smart cities, transportation, and industrial processes, bringing together energy systems, systems and control, and data science and AI. My current interests center on advanced control synthesis for energy and power systems. I am particularly interested in combining optimal control with AI to improve resilience, constraint handling, and decision-making in large-scale energy systems, supporting green-energy management and decarbonization across power generation, transportation, hydrogen infrastructure, and industrial production. This agenda connects control theory with practical decisions for complex energy infrastructure.

Research framework connecting multi-energy systems, data science and AI, systems and control, optimization, and intelligent power infrastructure.

Research themes

Three connected themes organize my work across modelling and data-driven control synthesis, cyber-physical adaptive energy systems, energy-system integration, intelligent transport, and industrial decarbonization. The first develops model-predictive, robust, stochastic, economic, and data-informed control architectures that connect long-term scheduling with real-time adaptation. The second examines integrated electricity, hydrogen, gas, and thermal networks, with emphasis on modular modelling, co-optimization, market constraints, and reliable sustainable infrastructure. The third focuses on hydrogen production, heterogeneous storage, refuelling and charging demand, transport logistics, and electric and fuel-cell mobility. Across all three themes, I examine operational feasibility, economic and environmental performance, resilience, user and market demand, and operating constraints. Together, they connect control theory with the infrastructure decisions required for a safe and practical transition to net-zero energy.

Explore the research themes

Multi-agent traffic-control scenario with two autonomous vehicles and an ambulance balancing collision avoidance, traffic rules, travel time, and comfort.

Optimal and data-driven control

I develop predictive, optimal, robust, stochastic, and data-informed control methods that coordinate decisions across physical systems and timescales while preserving constraints, resilience, and measurable performance.

Integrated renewable energy system linking storage, hydrogen production, electric mobility, loads, and the power grid through coordinated control.

Integrated energy and industrial systems

I connect electricity, hydrogen, storage, thermal processes, markets, and industrial demand through coordinated modelling and control for reliable infrastructure and practical decarbonization.

Hydrogen production, storage, delivery, refuelling, and mobility system connected to renewable generation and the utility grid.

Hydrogen and electric mobility

I study resilient planning and coordinated scheduling for hydrogen and electric mobility, linking renewable supply, heterogeneous storage, refuelling demand, delivery delays, markets, and transport infrastructure.