Meet the Treners: Shirin Kumra

As a Staff Vision Systems Engineer, Shirin brings extensive experience in robotic perception to the Trener Robotics team. With over a decade of work in computer vision and machine learning, her career has centered on real time vision pipelines and multimodal sensor fusion. She most recently worked at Siemens where she developed agentic AI frameworks to automate industrial workflows.

Why Trener Robotics?

Shirin was drawn to Trener Robotics by the core belief that robots should not need reprogramming every time something changes on the factory floor. For over a decade, she has worked on giving robots the ability to see and understand their surroundings, but she kept running into the same limitation: even the best perception system is only as useful as the platform it sits on.

“Acteris is that platform,” Shirin explains. “It combines vision, language, and action into a single intelligence layer where robots learn pre-trained skills instead of following rigid scripts. That approach, turning standard industrial robots into adaptive, intelligent teammates, is exactly the kind of problem I want to spend my time solving.”

Mission Focus: Intelligence Through Perception

Shirin’s focus as Staff Vision Systems Engineer is on the capabilities that allow Acteris to understand what is happening in and around the robot cell. She is building the systems that let robots identify parts, detect changes in their environment, and adapt to the variability common in high-mix production.

Shirin is applying her experience to create a perception module that powers pre-trained AI skills on real factory floors, across different robot brands, and under real world conditions. Her goal is a system that works in production rather than just in a lab setting.