Max Robotics — Global Service Robot Directory + US Certification

About

Ryan Kortvelesy is a researcher at the forefront of multi-robot systems and collective intelligence, tackling one of the field’s most persistent challenges: scaling coordination algorithms to large robot teams. His work centers on developing learning-based methods that overcome the “curse of dimensionality” in multi-robot planning. In his influential paper, “The Holy Grail of Multi-Robot Planning” (2021–2022, 12 citations), Kortvelesy proposes a framework that learns to generate online-scalable solutions from offline-optimal experts, bridging the gap between theoretical optimality and real-world scalability. This approach enables robot swarms to make efficient decisions in real time, even as team sizes grow. Kortvelesy is also the creator of VMAS (Vectorized Multi-Agent Simulator), introduced in 2022 and 2024 (15 citations total), a high-performance simulation environment that accelerates collective robot learning by vectorizing multi-agent interactions. VMAS has become a valuable tool for the MARL community, enabling faster experimentation and benchmarking. With a growing citation record and contributions that directly address the scalability bottleneck in multi-robot systems, Kortvelesy is shaping the future of autonomous robot coordination.