Yanjing Chen

Indiana University Bloomington, ShanghaiTech University

Papers

Total Citations

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About

Yanjing Chen is a researcher whose work bridges the frontiers of human interaction analysis and intelligent control systems. Her primary research areas include multimodal data mining, temporal pattern recognition, and model-based reinforcement learning. In her highly cited 2011 paper, Chen pioneered a novel sequential pattern mining method for analyzing multimodal data streams in dyadic interactions, moving beyond simple temporal ordering to extract exact quantitative temporal relationships—a significant contribution to understanding complex human communication dynamics. This work has garnered 20 citations and laid groundwork for more nuanced interaction analysis. More recently, Chen has tackled the challenge of data efficiency in reinforcement learning. Her 2021 paper on Risk-Aware Model-Based Control introduced a novel MBRL algorithm that addresses the performance gap between model-based and model-free methods in high-dimensional problems, earning 7 citations. This work demonstrates her ability to advance fundamental algorithmic approaches while maintaining practical applicability. Chen’s research trajectory shows a consistent focus on extracting meaningful patterns from complex, temporal data—whether from human interactions or autonomous systems—making her contributions valuable across cognitive science, robotics, and artificial intelligence.