Ziren Xiao

email: ziren.xiao1(at)gmail

Ziren Xiao receives a Ph.D. degree in Electronic and Electrical Engineering at the University of Liverpool, focusing on artificial intelligence-based multi-agent collaborative path planning. He holds a Master of Science in Computer Science and a Bachelor of Science in Computing and Software Systems from the University of Melbourne. Ziren has various research experience, including work on runtime optimisation of distributed systems using reinforcement learning.

Research Publications

• Citations: 55, h-index: 3
• 1. P Li, Z Xiao, X Wang, M Iqbal, P Casaseca-de-la-Higuera, Multiagent Reinforcement Learning-Based Multimodel Running Latency Optimization in Vehicular Edge Computing Paradigm, IEEE Systems Journal, 2024
• 2. Z Xiao, Artificial Intelligent-Based Multi-Agent Collaborative Path Planning Methods, University of Liverpool, 2024
• 3. Z Xiao, P Li, C Liu, H Gao, X Wang, MACNS: A generic graph neural network integrated deep reinforcement learning based multi-agent collaborative navigation system for dynamic trajectory planning, Information Fusion 105, 102250, 2024
• 4. R Xiao, J Sun, Y Wang, Z Xiao, H Gao, M Iqbal, P Ren, C Luo, X Wang, KAN-PPO: A Fast Convergence and Stable Proximal Policy Optimization Powered by Kolmogorov–Arnold Network, International Conference on Collaborative Computing: Networking …, 2024
• 5. P Li, M Yi, M Iqbal, X Wang, Z Xiao, Graph-based Proximal Policy Optimization Empowered Adaptive Task Scheduling Leveraging Cloud-edge Collaboration for Consumer Electronics, IEEE Transactions on Consumer Electronics, 2024
• 6. Z Xiao, C Leckie, MA Rodriguez, Intelligent Data Source Emission Rate Control for Optimising the Performance of Streaming Applications, 2024 IEEE International Symposium on Cluster, Cloud and Internet Computing …, 2024
• 7. P Li, Z Xiao, X Wang, K Huang, Y Huang, A Tchernykh, Multi-agent Reinforcement Learning Based Collaborative Multi-task Scheduling for Vehicular Edge Computing, International Conference on Collaborative Computing: Networking …, 2023
• 8. P Li, Z Xiao, X Wang, K Huang, Y Huang, H Gao, EPtask: Deep reinforcement learning based energy-efficient and priority-aware task scheduling for dynamic vehicular edge computing, IEEE Transactions on Intelligent Vehicles, 2023
• 9. Z Xiao, C Liu, S Luo, K Huang, H Gao, X Xu, X Wang, A collaborative and dynamic multi-source single-destination navigation algorithm for smart cities, Sustainable Energy Technologies and Assessments 56, 103032, 2023
• 10. Z Xiao, A Harwood, MA Rodriguez, Optimal Rate Control for Latency-constrained High Throughput Big Data Applications, 2022 IEEE International Conference on Big Data (Big Data), 234-241, 2022
• 11. S Duan, T Cai, Z Xiao, J Zhu, X Wang, X Yang, P Song, Deep Learning Assisted Ultra-Accurate Smartphone Testing of Paper-Based ELISA Assays, IEEE International Conference on Nano/Micro Engineered and Molecular Systems …, 2022
• 12. S Duan, T Cai, Z Xiao, X Wang, X Yang, J Zhu, P Song, A Deep Learning Assisted Smartphone Platform for Screening of Alzheimer’s Disease Using a Microfluidic Paper-based Analytical Device, IEEE International Conference on Nano/Micro Engineered and Molecular Systems …, 2022
• 13. Z Xiao, R Xiao, C Liu, H Gao, X Xu, S Luo, X Wang, An Efficient Dynamic Multi-Sources To Single-Destination (DMS-SD) Algorithm In Smart City Navigation Using Adjacent Matrix, IEEE International Conference On Human-Centered Cognitive Systems (HCCS), 2022
• 14. K Ramamohanarao, Z Xiao, PK Katiyar, Algorithms To Reduce Influences of Outliers in XGBoost, Univ. Melbourne, Melbourne, VIC, Australia, Tech. Rep, 2019