About Me
I am a final-year PhD candidate with Telecommunication Networks (TKN) Group at the School of Electrical Engineering and Computer Science, TU Berlin, working under the supervision of Prof. Dr.-Ing. habil. Falko Dressler. I also hold a position at the School of Computer Science and Technology at Shandong University, where my advisors are Prof. Dongxiao Yu and Prof. Xiuzhen Cheng. I am also very fortunate to closely work with Prof. Di Wang, who directs the PRADA Lab at KAUST.
I obtained my bachelor’s degree (with distinction) in Computer Science from the Taishan (Honors) College at Shandong University in 2021.
Research
My research lies at the intersection of artificial intelligence and information networking, with a primary focus on developing resource-efficient and trustworthy learning algorithms for edge AI. I am particularly interested in decision-making problems (bandit learning and reinforcement learning) and (stochastic) optimization.
At its core, my research addresses the following challenge:
How can we ensure data privacy, fault tolerance, and communication/computation efficiency while maintaining strong learning performance in edge environments where resources are constrained, communication bandwidth is limited, topology is highly dynamic, and adversaries may be present?
My work aims to bridge theory and practice, leveraging theoretical insights to develop innovative, scalable, and impactful real-world solutions.
My research was supported by the inaugural batch of the National Natural Science Foundation of China’s Basic Research Program for Doctoral Students [首批国家自然科学基金博士生项目] and the inaugural batch of the China Association for Science and Technology’s Young Talent Support Program – Doctoral Student Special Plan [首批中国科协青年人才托举工程博士生专项计划].
Opennings: I am always looking for motivated students to collaborate on research projects. If you are interested, please email me with your CV attached. A stipend is available, though it is typically reserved for students with prior collaboration experience.
Publications
(* denotes equal contribution)
Peer-Refereed Conference Papers
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[COCOON]
Robust Matroid Bandit Optimization against Adversarial Contamination
Youming Tao, Xiuzhen Cheng, Falko Dressler, Zhipeng Cai, Dongxiao Yu
The 30th International Computing and Combinatorics Conference (COCOON 2024) -
[ICMC]
Optimizing Task Migration Decisions in Vehicular Edge Computing Environments
Ziqi Zhou, Youming Tao, Agon Memedi, Chunghan Lee, Seyhan Ucar, Onur Altintas, Falko Dressler
he 1st IEEE International Conference on Meta Computing (ICMC 2024) -
[ICNC]
Correlation-Aware and Personalized Privacy-Preserving Data Collection
Dongxiao Yu, Kaiyi Zhang, Youming Tao, Wenlu Xu, Yifei Zou, Xiuzhen Cheng
International Conference on Computing, Networking and Communication (ICNC 2024) - [VLDB]
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[NeurIPS]
On Private and Robust Bandits [arxiv]
Yulian Wu*, Xingyu Zhou*, Youming Tao, Di Wang
The 37th Conference on Neural Information Processing Systems (NeurIPS 2023) -
[IJCAI]
Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited [link]
Youming Tao, Yulian Wu, Xiuzhen Cheng, Di Wang
The 31st International Joint Conference on Artificial Intelligence (IJCAI 2022) -
[AISTATS]
Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits [arxiv] [link]
Youming Tao*, Yulian Wu*, Peng Zhao, Di Wang
The 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022)
Selected as an Oral paper (Acceptance Rate: 44/1685=2.6%).
- Presented at ICML 2022 Workshop on Responsible Decision Making in Dynamic Environments (ICML-RDMDE 2022)
Selected as contributed talk.
- Presented at CCS 2021 Workshop on Privacy Preserving Machine Learning (CCS-PPML 2022)
Peer-Refereed Journal Papers
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[TCS]
Adaptive pruning-based Newton's method for distributed learning [link]
Shuzhen Chen, Yuan Yuan, Youming Tao, Zhipeng Cai, Dongxiao Yu
Theoretical Computer Science (Volume 1026)
A prior version was presented in the 29th International Computing and Combinatorics Conference (COCOON 2023) -
[TMC]
Private Over-the-Air Federated Learning at Band-Limited Edge [link]
Youming Tao, Shuzhen Chen, Congwei Zhang, Di Wang, Dongxiao Yu, Xiuzhen Cheng, Falko Dressler
IEEE Transactions on Mobile Computing (Volume: 23, Issue: 12, December 2024) - [TC]
- [TKDE]
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[TVT]
Decentralized Parallel SGD With Privacy Preservation in Vehicular Networks [link]
Dongxiao Yu, Zongrui Zou, Shuzhen Chen, Youming Tao, Bing Tian, Weifeng Lv, Xiuzhen Cheng
IEEE Transactions on Vehicular Technology (Volume 70, Issue 6, June 2021) -
[JSA]
Distributed Learning Dynamics of Multi-Armed Bandits for Edge Intelligence [link]
Shuzhen Chen, Youming Tao, Dongxiao Yu, FengLi, Bei Gong
Journal of Systems Architecture (Volume 114, March 2021) -
[IOTJ]
Privacy-Preserving Collaborative Learning for Multi-Armed Bandits in IoT [link]
Shuzhen Chen, Youming Tao, Dongxiao Yu, Feng Li, Bei Gong, Xiuzhen Cheng
IEEE Internet of Things Journal (Volume 8, Issue 5, March 2021)
Awards
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National Scholarship of China Nov. 2024
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President's Award, Shandong University Nov. 2023
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National Scholarship of China Oct. 2023
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Outstanding Graduate, Shandong University Jun. 2021
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Dean's Award, Taishan (Honors) College Jun. 2021
Professional Service
- Conference Reviewer/Program Committee Member for NeurIPS 2025 2024, ICML 2025, ICLR 2025, AISTATS 2025 2024, AAAI 2025 2024 2023, ICASSP 2025 2024, ECML-PKDD 2022
- Conference Sub-reviewer for CVPR 2024, NeurIPS 2023, ICML 2023, Euro S&P 2023, ICLR 2023, AISTATS 2023, ESORICS 2022
- Journal Reviewer for Information Processing & Management (IP&M), IEEE/ACM Transactions on Networking (TON), IEEE Transactions on Machine Learning in Communications and Networking (TMLCN), IEEE Transactions on Information Forensics & Security (TIFS), IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE Transactions on Computers (TC), IEEE Transactions on Mobile Computing (TMC), Frontiers of Computer Science (FCS)