Min Hao
Orcid: 0009-0001-2970-3637Affiliations:
- Singapore University of Technology and Design, Pillar of Information Systems Technology and Design, Tampines, Singapore
- Guangdong University of Technology, School of Automation, Guangzhou, China (PhD 2023)
According to our database1,
Min Hao
authored at least 13 papers
between 2021 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2025
The Butterfly Effect in Vehicular Digital Twin Systems: Complexity and Risk Analysis for Mixed-Traffic Scenarios.
IEEE Trans. Veh. Technol., July, 2025
Constructing the Metaverse With a New Perspective: UAV FoV-Assisted Low-Latency Imaging.
IEEE Wirel. Commun. Lett., January, 2025
Digital-Twin-Assisted Safety Control for Connected Automated Vehicles in Mixed-Autonomy Traffic.
IEEE Internet Things J., 2025
UAV-Assisted Zero Knowledge Model Proof for Generative AI: A Multiagent Deep Reinforcement Learning Approach.
IEEE Internet Things J., 2025
2024
Energy-Efficient Decentralized Federated Learning for UAV Swarm With Spiking Neural Networks and Leader Election Mechanism.
IEEE Wirel. Commun. Lett., October, 2024
Social Attention Network Fused Multipatch Temporal-Variable-Dependency-Based Trajectory Prediction for Internet of Vehicles.
IEEE Internet Things J., October, 2024
Frontiers Comput. Sci., April, 2024
Privacy-preserving Pseudonym Schemes for Personalized 3D Avatars in Mobile Social Metaverses.
CoRR, 2024
Deep Reinforcement Learning for Hybrid Task Scheduling in Collaborative Vehicular Edge Computing.
Proceedings of the 20th International Conference on Mobility, Sensing and Networking, 2024
C-V2X Aided Vehicular Blockchain Sharding Incentive Mechanism in Vehicular Edge Computing.
Proceedings of the 2024 IEEE Global Communications Conference, 2024
2023
Enhancing Digital Twin Model for Connected Vehicles by Powertrain and Longitudinal Dynamics.
Proceedings of the IEEE/CIC International Conference on Communications in China, 2023
2021
URLLC resource slicing and scheduling for trustworthy 6G vehicular services: A federated reinforcement learning approach.
Phys. Commun., 2021
Proceedings of the 93rd IEEE Vehicular Technology Conference, 2021