Zohre Karimi

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About

Zohre Karimi is a rising leader in human-robot interaction and autonomous surgical robotics, whose work bridges the critical gap between suboptimal human demonstrations and robust robot learning. Her primary research areas include learning from demonstration (LfD), shared autonomy, and user intent recognition for high-degree-of-freedom robotic systems. In her highly cited 2024 paper on surgical electrocautery, Karimi pioneered methods to extract reward functions from imperfect, suboptimal demonstrations—a breakthrough that directly addresses the low error tolerance of surgical tasks. This work has already garnered 9 citations, signaling its immediate impact on the field. More recently, in her 2025 study on zero-shot user intent recognition, she tackled the fundamental challenge of inferring human goals without exhaustive prior knowledge, enabling robots to assist users seamlessly in real-time shared autonomy scenarios. By moving beyond the assumption of perfect demonstrations and complete intent libraries, Karimi’s research is redefining how robots learn from and collaborate with humans. Her contributions are particularly notable for their direct application to high-stakes environments like surgery, where mistakes are costly. As her citation trajectory suggests, Karimi is establishing herself as a key innovator in making autonomous systems more adaptive, safe, and truly assistive.