Max Robotics — Global Service Robot Directory + US Certification

About

Montserrat Gonzalez Arenas is a leading roboticist whose work sits at the intersection of large language models (LLMs) and robot manipulation, pioneering new ways to make robots more intelligent, adaptable, and useful in the real world. Her research focuses on using LLMs as general-purpose pattern machines for task planning, developing novel prompting strategies for code-as-policies, and creating systems that learn from human corrective feedback to generalize across novel environments. She has made major contributions to scaling deep reinforcement learning for real-world deployment, most notably in a landmark system that used a fleet of mobile manipulators to sort waste in office buildings—a practical demonstration of deep RL at scale. Her highly cited works, including “Large Language Models as General Pattern Machines” (33 citations) and “How to Prompt Your Robot” (25 citations), have helped define how language models can bridge semantic reasoning and physical action. She also contributed to Gemini Robotics, a Google DeepMind initiative bringing multimodal AI into the physical world. With over 100 citations across her most impactful papers, Gonzalez Arenas is shaping the future of generalizable, language-guided robot manipulation.