Stochastic Systems and Control Laboratory

Many practical problems in control engineering, communication systems, and statistical machine learning domains involve random phenomena or require handling randomized algorithms. We investigate such problems by applying rigorous probability theory. Particular application scenarios range from wireless networked control, Internet of Things, and cyber-security of control systems to artifical intelligence, data analysis, and automated driving systems.

Control theory, Statistical machine learning, Communication systems, Probability

Research on cybersecurity of networked control systems, Research on learning-based and data-driven control, Research on randomized algorithms in control and learning

E-mail: ahmet[at]shibaura-it.ac.jp