Yulei Li

Durham University, Northumbria University

Papers

Total Citations

151

H-Index

About

Yulei Li is a pioneering researcher at the intersection of artificial intelligence, human-robot interaction, and consumer behavior analytics. His most impactful work, "Customer Emotions in Service Robot Encounters: A Hybrid Machine-Human Intelligence Approach" (2022), has garnered 144 citations and fundamentally reshaped how we understand and predict consumer adoption of service robots. Li developed a novel hybrid methodology that combines the depth of qualitative analysis with the scalability of machine learning, enabling automated extraction of nuanced emotional signals from online reviews of robot-customer interactions. This breakthrough addresses a critical gap: while traditional qualitative methods yield rich insights, they are labor-intensive and impractical at scale. Li’s hybrid approach makes it possible to forecast consumer intentions toward service robots with unprecedented accuracy, directly informing the design of more empathetic and effective robotic systems. His broader portfolio includes work on ensemble learning for news popularity prediction (XiaoA, 2018) and advancing visual question answering through fine-grained object localization (Detect2Interact, 2024). By bridging machine intelligence with human emotional understanding, Li is helping to create a future where robots can genuinely connect with people—a contribution that resonates deeply in our increasingly automated world.