Kazuki Mizuta

My research is centered at the intersection of machine learning and control theory, with the ultimate goal of enabling autonomous robots to operate alongside humans in uncertain and dynamically changing environments. Currently, my work focuses on developing robot planning algorithms that leverage deep generative models—such as diffusion models and conditional flow matching techniques—to capture multimodal trajectory distributions while employing control-theoretic approaches to ensure safety and other essential performance criteria.