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About

Hongjing Lu is a leading researcher at the intersection of human-robot interaction and cognitive science, whose work fundamentally advances how machines build trust and coordinate with humans. Her primary research areas include human-robot collaboration, explainable AI, and bidirectional value alignment. In her highly influential 2019 paper, "A tale of two explanations" (132 citations), Lu pioneered a framework for enhancing human trust by systematically analyzing what forms of robot behavior explanations are most effective—a critical contribution as AI systems become more autonomous. She further advanced the field with her 2022 work on "in situ bidirectional human-robot value alignment" (74 citations), which established that effective human-robot teamwork requires both partners to simultaneously act as receptive listeners and expressive speakers, especially when navigating complex, multi-goal scenarios. More recently, Lu has developed innovative approaches for calibrating human perception of robot capabilities, such as through reachable workspace visualization, and has extended her research into rehabilitation robotics with motion intent recognition algorithms. Her work is essential reading for anyone interested in creating AI systems that can truly collaborate with humans by understanding, explaining, and aligning with human values and expectations.