Mihailo Radović

I'm an MSc student in Applied Mathematics at the University of Belgrade, School of Electrical Engineering. I also work as a Data Engineer at Nordeus.

My research focuses on generative models, such as diffusion and flow models, and their applications to robot motion planning and control. I'm also interested in reinforcement learning and world models. I also keep a blog, where I write about what I'm learning and share notes from my research.

I completed my BSc in Computer Science at Union University, School of Computing, in 2025. My bachelor's thesis, supervised by Prof. Nemanja Ilić, focused on flow matching for pixel-art character generation.

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PhD search: I'm currently looking for a PhD position in generative models, world models, reinforcement learning, and robotics. My long-term goal is to help build general-purpose autonomous agents that understand the physical world, learn from experience, and act in it safely, and I'm open to research directions that move toward that goal. If you think I'd be a good fit for your group, I'd love to hear from you by email.

Research

I'm interested in generative modeling, imitation and reinforcement learning, and robot learning. Most of my work is on flow matching: using continuous-time generative models both to generate images and to learn expressive, multi-modal policies for continuous control. Representative papers are highlighted.

Modeling a behavioral cloning policy as a continuous-time flow captures the multi-modal behavior in diverse offline datasets, matching or outperforming Gaussian and diffusion policies on standard continuous-control benchmarks.

A flow matching model with a time-conditioned U-Net that transforms Gaussian noise into 128×128 RGBA pixel-art characters.

Miscellanea

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