معرفی
Sunith Bandaru is a Professor of Industrial Engineering at the University of Skövde, affiliated with the School of Engineering Science. He holds administrative roles such as Subject Coordinator for Informatics at Research Level and has contributed to program management for M.Sc. Industrial Systems Engineering. His research focuses on multi-objective optimization, digital twins, and knowledge-driven decision support in manufacturing systems.
Bandaru's work bridges advanced algorithms with industrial applications, emphasizing optimization techniques (e.g., evolutionary algorithms) and their integration with AI-driven tools like digital twins. He has pioneered frameworks for bottleneck detection in production systems and develops interactive decision support systems using data mining and simulation-based methods.
He has led projects like LITMUS (transitioning to Industry 5.0) and Virtual Engineering initiatives, aiming to enhance production sustainability and human-centric design. His contributions include tools like Mimer for knowledge discovery and optimization of maintenance prioritization via deep reinforcement learning.