Kyungtae Han

Toyota Motor Corporation (United States)

Papers

1

Total Citations

6

H-Index

1

About

Dr. Kyungtae Han is a leading researcher at the intersection of vehicular networks, autonomous driving, and artificial intelligence, with a particular focus on optimizing data delivery for next-generation intelligent transportation systems. His key contributions center on solving the critical challenge of managing the massive data volumes generated by Highly-Dynamic (HD) maps—essential for fine-grained environmental awareness, precise localization, and route planning in autonomous vehicles. In his highly cited 2023 work, "DSORL: Data Source Optimization With Reinforcement Learning Scheme for Vehicular Named Data Networks," Dr. Han pioneered a novel reinforcement learning framework that intelligently selects optimal data sources within vehicular Named Data Networks, significantly improving data retrieval efficiency and network reliability. This work, already garnering 6 citations, demonstrates his ability to bridge theoretical AI methods with practical vehicular communication challenges. Dr. Han’s research is pivotal for enabling the real-time, reliable data sharing that future autonomous fleets will require, establishing him as a key innovator in the evolution of smart, connected mobility.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
DSORL: Data Source Optimization With Reinforcement Learning Scheme for Vehicular Named Data Networks
6 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Toyota Motor Corporation (United States)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago