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About

Monica Bordegoni is a leading researcher in human-robot interaction, assistive robotics, and virtual prototyping, whose work bridges the gap between machine learning and real-world applications. Her most influential contribution, "Learning Robot Behaviour and Skills Based on Human Demonstration and Advice," has garnered 119 citations, establishing a foundational paradigm for robots to acquire complex tasks through human guidance. She has pioneered the use of Virtual Reality to test human-robot collaboration in manufacturing, as seen in her 2019 study, which emphasizes the critical role of operator psychophysiological responses in designing efficient collaborative systems. Bordegoni’s research also extends to inclusive technology, notably developing a Multimodal Guidance System that provides robotic assistance to persons with disabilities for manual tasks like drawing and foam-cutting. Her recent work on a simplified 3D-printed underactuated hand and context-aware industrial robot testing demonstrates her commitment to low-cost, accessible solutions for human-robot cooperation. Through her innovative integration of machine learning, VR, and assistive robotics, Bordegoni has significantly advanced the safety, efficiency, and inclusivity of human-robot systems, making her a pivotal figure in modern robotics research.