Our research in Product and Process Systems Engineering and AI Applications focuses on product design, process modeling and simulation, optimization of chemical processes, AI-driven predictive analytics, supply chain for energy resources, and data-driven product and process design to advance intelligent manufacturing, process efficiency, and sustainable industrial systems.
Product design and engineering
Systematic frameworks for designing high-performance chemical and industrial products
AI-driven predictive analytics
Machine learning and data-driven methods for real-time process intelligence and control
Process modelling and simulation
Digital twins and computational models for predicting and optimizing process behavior
Optimization of industrial processes
Mathematical programming and heuristic methods for large-scale process optimization
Data-driven process design
Integrating experimental data with computational frameworks for accelerated design cycles
Supply chain systems engineering
Modelling and optimizing energy and resource supply chains for resilience and efficiency
