Intent Recognition for Human-Machine Interactions / SpringerBriefs in Computer Science (PDF)

Hua Xu is a leading expert on multi-modal natural interaction for service robots, evolutionary learning, and intelligent optimization. He is currently a tenured associate professor at Tsinghua University, editor-in-chief of Intelligent Systems with Applications, and associate editor of Expert Systems with Application. Prof. Xu has authored the Chinese books "Data Mining: Methodology and Applications" (2014), "Data Mining: Methods and Applications-Application Cases" (2017), "Evolutionary Machine Learning" (2021), "Data Mining: Methodology and Applications" (2nd edition) (2022), "Natural Interaction for Tri-Co Robots (1) Human-machine Dialogue Intention Understanding" (2022) and "Natural Interaction for Tri-Co Robots (2) Sentiment Analysis of Multimodal Interaction Information" (2023), and published more than 140 papers in top-tier international journals and conferences. He is a core expert of the No. 3 National Science and Technology Major Project of the Ministry of Industry and Information Technology of China, senior member of CCF, member of CAAI and ACM, vice chairman of Tsinghua Collaborative Innovation Alliance of Robotics and Industry, and recipient of numerous awards, including the Second Prize of National Award for Progress in Science and Technology, the First Prize for Technological Invention of CFLP, and First Prize for Science and Technology Progress of CFLP.



Hanlei Zhang obtained his BS degree from the Department of Computer Science and Technology at Beijing Jiaotong University in 2020. He is currently pursuing a PhD in the Department of Computer Science and Technology at Tsinghua University. His research goal focuses on analyzing human intentions in real-world scenarios. Hanlei has published five first-authored peer-reviewed papers in top-tier international conferences and journals, including AAAI, ACM MM, ACL, and IEEE/ACM TASLP. His research interests encompass various areas such as intent analysis, open world classification,