Coco Robotics hires UCLA professor Bolei Zhou to lead new physical AI lab

Coco Robotics has established a new physical AI research lab led by UCLA professor Bolei Zhou, who also joins the startup as chief AI scientist. The move represents the company’s strategic pivot from human-operated delivery robots to fully autonomous systems, leveraging five years of real-world data collected from its last-mile delivery fleet.

What you should know: Coco Robotics has accumulated millions of miles of operational data from urban delivery routes, positioning the company to accelerate AI automation research.

• The startup launched in 2020 using teleoperators—remote human controllers—to help robots navigate obstacles during deliveries, but CEO Zach Rash says the company always intended to achieve full autonomy to reduce delivery costs.
• “We have millions of miles of data collected in the most complicated urban settings possible, and that data is incredibly important for training any sort of useful and reliable real world AI systems,” Rash explained.

Why Zhou matters: The UCLA professor brings specialized expertise in computer vision, robotics, and micromobility research that directly aligns with Coco’s operational challenges.

• Zhou’s research focus on smaller-scale vehicles rather than full-size autonomous cars makes him particularly suited for last-mile delivery applications.
• “He’s one of the leading researchers in the whole world on robot navigation, reinforcement learning, and a lot of the technologies and areas of research that are highly relevant for us,” Rash noted.
• The collaboration builds on existing ties—both Coco co-founders are UCLA alumni and have already donated a robot to the university’s research lab.

Separate from OpenAI partnership: The new research lab operates independently from Coco’s existing collaboration with OpenAI, which involves data sharing in exchange for access to AI models.

• Coco plans to keep the research findings proprietary for now, focusing on improving its own automation and efficiency rather than selling data to competitors.
• The company will share relevant infrastructure insights with cities where it operates to help address obstacles that slow down delivery robots.

The big picture: Success for the lab centers on delivering higher-quality service at dramatically lower costs through improved automation.

• Research will primarily focus on enhancing the local AI models that run directly on Coco’s delivery robots.
• “How do we get our costs lower? How do we make this much more affordable for businesses and customers? I think that’s going to create a tremendous amount of growth in this ecosystem,” Rash said.