Professor of Big Data Cybernetics & Artist
Pioneering research in Digital Twins, Hybrid Analysis and Modeling, Machine Learning, and Computational Fluid Dynamics. Bridging the gap between academic innovation and real-world industrial applications across autonomous systems, wind energy, and urban environments.
My research spans multiple domains, combining fundamental research with practical applications to solve real-world challenges in energy, autonomous systems, and smart infrastructure.
Creating virtual replicas of physical systems for real-time monitoring, simulation, and optimization in wind energy, autonomous vessels, and urban infrastructure.
Learn MoreCombining physics-based models with data-driven machine learning to create more accurate, interpretable, and robust predictive systems.
Learn MoreApplying cybernetic principles to big data analytics for intelligent decision-making and adaptive control in complex dynamic systems.
Learn MoreDeep reinforcement learning, explainable AI, physics-informed neural networks, and trustworthy AI for safety-critical applications.
Learn MoreHigh-fidelity numerical methods for simulating complex fluid flows, turbulence modeling, and reduced-order modeling for real-time applications.
Learn MoreWind Energy, Autonomous Ships, Urban Environment, Oil & Gas, Aviation, Aquaculture, Health, and Smart Infrastructure.
View ProjectsDigital twin framework for wind farms enabling real-time monitoring and predictive maintenance.
Situational awareness systems for autonomous ships using AI and sensor fusion.
Developing explainable machine learning methods for industrial applications.
Beyond research, I express creativity through painting and photography. With 30+ awards in fine arts and exhibitions across Europe and Asia.
I'm always open to discussing research collaborations, PhD opportunities, and industry partnerships in the areas of digital twins, AI/ML, and computational engineering.
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