Zifan Ye

Beijing Normal University

Papers

1

Total Citations

19

H-Index

1

About

Zifan Ye is a forward-thinking researcher at the intersection of artificial intelligence and education, with a primary focus on developing innovative pedagogical frameworks for AI learning. His most influential work, "Artificial Intelligence Course Design: iSTREAM-based Visual Cognitive Smart Vehicles" (2018, 19 citations), introduces a groundbreaking educational platform that integrates smart vehicles with the iSTREAM (Science, Technology, Robotics, Engineering, Arts, and Mathematics) approach. This paper addresses the urgent need for modern learners to engage with AI through hands-on, visual cognitive systems, transforming how students understand complex AI concepts. Ye’s major contribution lies in bridging theoretical AI education with practical, real-world applications, using smart cars as a tangible medium for teaching machine learning and computer vision. His work has been recognized for its impact on curriculum design, inspiring educators to adopt interactive, project-based learning methods. With growing citation counts reflecting its relevance, Ye’s research continues to shape the next generation of AI practitioners, making him a notable figure in educational technology and AI pedagogy.

Research Focus

Key Achievements

1
H-Index
1
Papers
19
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
Artificial Intelligence Course Design: iSTREAM-based Visual Cognitive Smart Vehicles
19 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Beijing Normal University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago