Jianming Wu

Papers

Total Citations

H-Index

About

Jianming Wu is a researcher working at the intersection of human-computer interaction, conversational AI, and social computing. Their work focuses on developing intelligent systems that enhance human communication and social connection, with a particular emphasis on dialogue robots and deep learning applications for understanding interpersonal dynamics. Wu's research has explored two notable directions: the design of socially engaging companion robots and the computational modeling of group behavior. Their 2021 paper introducing "KACTUS," a TV-watching companion robot powered by an open-domain chatbot, addresses the growing concern that digital media consumption is eroding meaningful social interaction, proposing an AI-driven solution to restore communicative engagement in everyday leisure contexts. Complementing this, their 2020 work on the Linguistic Knowledge Injectable Deep Neural Network (LDNN) tackles the challenging problem of group cohesiveness understanding — developing a model capable of interpreting the subtle emotional and social bonds between people in group settings, a capability critical for advancing empathetic dialogue systems. While Wu's published work is still accumulating citations, the themes they pursue — loneliness mitigation, social AI, and affective computing — address increasingly urgent challenges in modern society, positioning their research as relevant and forward-looking for the broader HCI and AI communities.