AI for Optimization

Application of artificial intelligence techniques—especially reinforcement learning—to solve complex optimization problems, with a focus on real-world systems subject to practical constraints and dynamic environments. Research includes algorithm development, efficiency, generalization, and real-world adaptability.

Driving Behavior Prediction

Development of data-driven models for driving behavior prediction using cloud-integrated and real-time information sources. Research includes multimodal data fusion, behavior modeling, and predictive analytics to support intelligent vehicle systems and decision-making in dynamic environments.

Explainable and Trustworthy AI

Research on improving the transparency, interpretability, and reliability of AI systems in real-world applications. The work focuses on developing methods that enable experts from non-AI fields to understand, evaluate, and trust AI-driven decisions, supporting safe and robust decision-making in complex environments.