Xinwei Deng

Virginia Tech

Papers

1

Total Citations

19

H-Index

1

About

Xinwei Deng is a leading researcher in generative modeling, artificial intelligence, and human behavior analysis. His most notable contribution is the development of abductive reasoning frameworks for modeling social interactions, a novel approach that bridges computational inference with complex human dynamics. In his highly influential 2018 paper, "Generative Modeling of Human Behavior and Social Interactions Using Abductive Analysis," Deng pioneered the use of abduction—reasoning from observed data to the most plausible explanations—to model human behavior, an area previously dominated by applications in robotics and genetics. This work, which has garnered 19 citations, opened new pathways for AI systems to interpret and predict nuanced social cues. Deng’s research is distinguished by its interdisciplinary reach, integrating principles from cognitive science, machine learning, and social computing. His achievements include advancing the theoretical foundations of generative models and demonstrating their practical utility in understanding real-world human interactions. For students and researchers, Deng’s work offers a compelling vision of how AI can move beyond pattern recognition to achieve deeper, context-aware understanding of human behavior.

Research Focus

Key Achievements

1
H-Index
1
Papers
19
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
Generative Modeling of Human Behavior and Social Interactions Using Abductive Analysis
19 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Virginia Tech

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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