Lichen Wang

Northeastern University, Yuan Ze University

Papers

Total Citations

H-Index

About

Lichen Wang is a researcher whose work bridges artificial intelligence and human-centered technologies, with a primary focus on pedestrian trajectory prediction and interactive learning systems. His most impactful contribution is the development of adaptive trajectory prediction using transferable Graph Neural Networks (GNNs), a method that addresses a critical limitation in autonomous driving and robotics: the assumption that training and testing motion patterns are identical. By accounting for distribution differences—such as varying crowd behaviors in shopping malls versus streets—Wang’s approach significantly improves prediction accuracy in real-world scenarios, earning 86 citations for his 2022 paper. Beyond AI for autonomous systems, Wang explores technology’s role in education, co-developing an AR-assisted interactive learning system with a companion robot to support children’s learning and parent-child interaction in dual-income families. This work, published in 2025, highlights his commitment to applying AI to social challenges. Wang’s research demonstrates a dual impact: advancing core machine learning techniques while creating practical tools for everyday life, making him a notable figure in both technical and applied AI domains.