Xiaowei Dong
Papers
2
Total Citations
3
H-Index
1
About
Xiaowei Dong’s research bridges artificial intelligence and agricultural technology, with a focus on human-AI interaction and deep learning applications. In their landmark 2024 study, “AI Aversion or Appreciation? Meta-Analytic Evidence for a Capability-Personalization Framework,” Dong proposed a novel framework to reconcile conflicting findings on whether people prefer AI or human agents. This work, already garnering 2 citations, offers a nuanced understanding of how task capability and personalization shape user attitudes—a critical insight for designing AI systems that gain public trust. Dong also contributes to precision agriculture with their 2025 paper, “A lightweight detection algorithm for cereal weed recognition based on deep learning,” which introduces an efficient, computationally light model for real-time weed identification, holding promise for sustainable farming. Though early in their career, Dong’s dual focus on AI psychology and applied machine learning demonstrates versatility and impact. Their meta-analytic approach and practical algorithm development position them as a rising scholar at the intersection of behavioral science and agricultural AI, with potential to influence both theoretical frameworks and real-world technology deployment.
Research Focus
Key Achievements
Top Papers
- 1
- 2