Santiago Donaher

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About

Santiago Donaher is a leading researcher in computer vision and robotics, specializing in the contactless estimation of object properties for safe human-robot interaction. His work addresses the critical challenge of enabling robots to perceive and manipulate containers—including opaque, transparent, and variably shaped vessels—during handovers. Donaher’s most cited paper, "The CORSMAL Benchmark for the Prediction of the Properties of Containers" (2022, 9 citations), introduces a standardized framework for estimating container weight and content volume from visual data alone, a foundational step for autonomous robotic grasping. This benchmark has become a key resource for advancing sensorless perception in robotics. Beyond this, Donaher’s contributions span multi-modal sensing and machine learning, with his research directly impacting assistive robotics and industrial automation. His work is notable for bridging the gap between theoretical computer vision and practical robotic systems, earning recognition for its rigor and real-world applicability. With a growing citation record, Donaher continues to shape how robots interpret and interact with complex, everyday objects.