Dongyuan Su received his Bachelor's degree in June 2019 from the Special Class of High Performance Computing (SCHPC) of the College of Computer Science and Software Engineering at Shenzhen University. He obtained his Ph.D. in December 2024 from Shenzhen University (supervised by Prof. Laizhong Cui). His research focuses on data transmission, collaborative learning, and collaborative inference mechanisms in vehicular networks.
He has published 6 papers in international journals and conferences such as TSC, ICNP, TMM, TITS, MM, and CN, and has been granted 1 national invention patent. He serves as a reviewer for journals such as TON, TMM, and CN.
Students interested in vehicular networks, federated learning, collaborative learning, collaborative inference, and mobile edge computing are welcome to contact: sudongyuan@sztu.edu.cn
Student Placement: Ruikun Yang (Undergraduate, SZTU 2026) → City University of Hong Kong
教育经历
2019/09 - 2024/12，深圳大学，计算机科学与技术专业，工学博士（硕博连读）
2015/09 - 2019/06，深圳大学，计算机科学与技术专业，工学学士（推免）
Education
2019/09 - 2024/12, Shenzhen University, Ph.D. in Computer Science and Technology
2015/09 - 2019/06, Shenzhen University, Bachelor of Engineering in Computer Science and Technology
工作经历
2026/02 - 至今，深圳技术大学，人工智能学院，助理教授
2025/01 - 2026/01，深圳技术大学，人工智能学院，讲师
Work Experience
2026/02 - Present, Shenzhen Technology University, School of Artificial Intelligence, Assistant Professor
2025/01 - 2026/01, Shenzhen Technology University, School of Artificial Intelligence, Lecturer
主要研究领域
车联网
分布式机器学习
联邦学习
移动边缘计算
Research Areas
Vehicular Networks
Distributed Machine Learning
Federated Learning
Mobile Edge Computing
教学课程
《Python程序设计》
《人工智能数学基础》
Teaching
Python Programming Language
Mathematics for Artificial Intelligence
主要成果
[1] Dongyuan Su, Laizhong Cui. DFL-ALLC: Adaptive Local Learning Control for Decentralized Fedetaed Learning in Heterogeneous Vehicular Networks, IEEE ICASSP, 2026, Accepted. (CCF-B类会议)
[2] Dongyuan Su, Yipeng Zhou, Laizhong Cui, Song Guo. Boosting Dynamic Decentralized Federated Learning by Diversifying Model Sources, IEEE Transactions on Services Computing, 2024, 17(4):1400-1413. DOI: 10.1109/TSC.2024.3377157. (CCF-A类期刊)
[3] Dongyuan Su, Yipeng Zhou, Laizhong Cui, Quan Z. Sheng. Communication Cost-aware Client Selection in Online Federated Learning: A Lyapunov Approach, Computer Networks, 2024, 249:110517. DOI: 10.1016/j.comnet.2024.110517. (CCF-B类期刊)
[4] Dongyuan Su, Yipeng Zhou, Laizhong Cui. Boost Decentralized Federated Learning in Vehicular Networks by Diversifying Data Sources, IEEE ICNP, 2022, 1-11. DOI: 10.1109/ICNP55882.2022.9940426. (CCF-B类会议)
[5] Dongyuan Su, Laizhong Cui, Lei Zhang, Yanyan Suo, Yan Qiu. Rate Adaptation and Block Scheduling for Delay-sensitive Multimedia Applications, ACM MM, 2021, 4828-4832. DOI: 10.1145/3474085.3479224. (CCF-A类会议)
[6] Laizhong Cui, Dongyuan Su, Shu Yang, Zhi Wang, Zhong Ming. TCLiVi: Transmission Control in Live Video Streaming Based on Deep Reinforcement Learning, IEEE Transactions on Multimedia, 2020, 23:651-663. DOI: 10.1109/TMM.2020.2985631. (CCF-A类期刊)
[7] Laizhong Cui, Dongyuan Su, Yipeng Zhou, Lei Zhang, Yulei Wu, Shiping Chen. Edge Learning for Surveillance Video Uploading Sharing in Public Transport Systems, IEEE Transactions on Intelligent Transportation Systems, 2020, 22(4):2274-2285. DOI: 10.1109/TITS.2020.3008420. (CCF-B类期刊)
Publications
[1] Dongyuan Su, Laizhong Cui. DFL-ALLC: Adaptive Local Learning Control for Decentralized Fedetaed Learning in Heterogeneous Vehicular Networks, IEEE ICASSP, 2026, Accepted.
[2] Dongyuan Su, Yipeng Zhou, Laizhong Cui, Song Guo. Boosting Dynamic Decentralized Federated Learning by Diversifying Model Sources, IEEE Transactions on Services Computing, 2024, 17(4):1400-1413. DOI: 10.1109/TSC.2024.3377157.
[3] Dongyuan Su, Yipeng Zhou, Laizhong Cui, Quan Z. Sheng. Communication Cost-aware Client Selection in Online Federated Learning: A Lyapunov Approach, Computer Networks, 2024, 249:110517. DOI: 10.1016/j.comnet.2024.110517.
[4] Dongyuan Su, Yipeng Zhou, Laizhong Cui. Boost Decentralized Federated Learning in Vehicular Networks by Diversifying Data Sources, IEEE ICNP, 2022, 1-11. DOI: 10.1109/ICNP55882.2022.9940426.
[5] Dongyuan Su, Laizhong Cui, Lei Zhang, Yanyan Suo, Yan Qiu. Rate Adaptation and Block Scheduling for Delay-sensitive Multimedia Applications, ACM MM, 2021, 4828-4832. DOI: 10.1145/3474085.3479224.
[6] Laizhong Cui, Dongyuan Su, Shu Yang, Zhi Wang, Zhong Ming. TCLiVi: Transmission Control in Live Video Streaming Based on Deep Reinforcement Learning, IEEE Transactions on Multimedia, 2020, 23:651-663. DOI: 10.1109/TMM.2020.2985631.
[7] Laizhong Cui, Dongyuan Su, Yipeng Zhou, Lei Zhang, Yulei Wu, Shiping Chen. Edge Learning for Surveillance Video Uploading Sharing in Public Transport Systems, IEEE Transactions on Intelligent Transportation Systems, 2020, 22(4):2274-2285. DOI: 10.1109/TITS.2020.3008420.
主要荣誉
学术竞赛
ACM Multimedia Grand Challenge – Meet Deadline Requirements (CCF-A类会议竞赛), 亚军
ACM Multimedia Grand Challenge – Meet Deadline Requirements (CCF-A Conference Competition), Second Place
ACM MM Student Travel Grant
AITrans Competition, Second Prize
Other Awards
Ph.D.: Shenzhen University Outstanding Doctoral Student Selection and Funding Program (Outstanding Doctoral Program), Shenzhen University Doctoral Student Top Innovative Talent Scholarship Special Award, Shenzhen University College of Computer Science and Software Engineering Doctoral Student Top Talent Cultivation Program (Top Talent Program) Grade A, etc.
Master's: National Scholarship, Academic Scholarship Special Award, etc.
Bachelor's: Shenzhen University Outstanding Graduate, Honors Bachelor's Degree, Chen Guoliang Academician Scholarship, Tencent enterprise Scholarship, etc.
National Natural Science Foundation of China, Research on collaborative learning and inference mechanisms for large models in vehicular networks, 2026.1-2028.12. PI
Shenzhen Science and Technology Program, Research on fully decentralized collaborative mechanisms in vehicular networks, 2025.10-2028.10. PI
National Natural Science Foundation of China, Research on the key technologies of scheduling and communication optimization for federated learning, 2024.1-2027.12. Co-I
The Outstanding Young Team of Guangdong Basic and Applied Basic Research Foundation, Research on intelligent transmission mechanism for the new networks, 2024.1-2026.12. Co-I
审稿人
IEEE/ACM Transactions on Networking
IEEE Transactions on Multimedia
Computer Networks
Concurrency and Computation: Practice and Experience
Reviewer
IEEE/ACM Transactions on Networking
IEEE Transactions on Multimedia
Computer Networks
Concurrency and Computation: Practice and Experience