Max Robotics — Global Service Robot Directory + US Certification

About

Jensen Gao is an emerging robotics researcher whose work sits at the intersection of robot learning, large-scale data collection, and vision-language models for robotic manipulation. His most impactful contributions center on building the foundational datasets and model architectures needed to advance generalizable robotic systems. Gao was a key contributor to the landmark **Open X-Embodiment** project (119 citations), a landmark collaborative effort demonstrating that large, diverse robotic datasets can train high-capacity models—analogous to foundation models in NLP and vision—that transfer effectively across tasks and embodiments. He also played a significant role in **DROID** (108 citations), one of the largest and most diverse in-the-wild robot manipulation datasets to date, addressing the critical challenge of scalable, real-world data collection. His work on **physically grounded vision-language models** (83 citations) pushes VLMs beyond passive perception toward actionable physical reasoning in manipulation contexts. Earlier work on **ASHA** explored assistive teleoperation through human-in-the-loop reinforcement learning, reflecting a consistent thread of making robots more adaptable to real human needs. Across these projects, Gao's research is helping lay the infrastructure for the next generation of generalizable, data-driven robotic intelligence.