Papers
3
Total Citations
24
H-Index
3
About
Yanan Lu is a researcher at the intersection of artificial intelligence, robotics, and STEM education, with a focus on data privacy and the pedagogical impact of competitive robotics. Lu’s most cited work, “A federated pedestrian trajectory prediction model with data privacy protection” (2023, 17 citations), addresses a critical challenge in autonomous systems: enabling accurate trajectory prediction for self-driving vehicles and social robots while safeguarding sensitive trajectory data. By proposing a federated learning framework, Lu’s contribution allows models to learn from diverse, scattered data sources without compromising privacy—a key advancement for real-world deployment. Beyond technical AI, Lu investigates the educational dimensions of robotics through studies on the World Robot Olympiad (WRO). In “Impact of participation in the World Robot Olympiad on K-12 robotics education from the coach’s perspective” (2022, 4 citations) and related work (2022, 3 citations), Lu developed and validated instruments to assess how robotics competitions influence participants, students, and coaches. These studies provide empirical evidence for integrating robotics into STEM curricula, highlighting Lu’s dual impact: advancing privacy-preserving AI for autonomous systems and shaping evidence-based practices in K-12 robotics education.
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