Dr. Yijing Lin is a Postdoctoral Researcher at the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), China. She received her Ph.D. degree in Computer Science and Technology from BUPT in 2024 under the supervision of Prof. Zhipeng Gao, and conducted joint research at Nanyang Technological University (Singapore) with Prof. Dusit Niyato and at the Chinese University of Hong Kong (Shenzhen) with Prof. Shuguang Cui. Her research interests include blockchain-enabled trustworthy data governance, federated learning and unlearning, and semantic communication for next-generation intelligent networks. Dr. Lin has published over 20 papers in premier venues such as IEEE TMC, TSC, TDSC, TCOM, TNSE, WWW, IJCAI, and COMST, including two ESI Highly Cited Papers and one ESI Hot Paper. Her research has received IEEE Computer Society Best Paper Award, the IEEE-CCF Service Computing Best Student Paper Award, the KSEM Best Paper Award, the IEEE Trustcom Outstanding Paper Award, he IEEE IWCMC Best Paper Award, and CCF China Blockchain Technology and Applications Summit Forum Best Paper Award. She is also the Principal Investigator of several nationally competitive research grants, including the Postdoctoral Innovation Talent Program funded by the Ministry of Human Resources and Social Security of China, the National Natural Science Foundation of China (NSFC) Youth Program. She is also a Contributor to IEEE standards P3849, P3811, P3231.01, and P3231.02. She received the 2025 Second Prize of the Invention and Innovation Award from the China Invention Association (a national first-class association) and 2024 Second Prizes for Scientific and Technological Progress from the China Urban Rail Transit Association (a national first-class association) and the Beijing Rail Transit Society, respectively.

News

Representative Papers (First author)

For all publications, please refer to my google scholar.

1. Y. Lin, Z. Gao, H. Du, D. Niyato, J. Kang, and X. Liu, “Incentive and dynamic client selection for federated unlearning”, Proceedings of the ACM Web Conference, 2024: 2936-2944. (CCF-A)
2. Y. Lin, Z. Gao, H. Du, D. Niyato, G. Gui, S. Cui, and J. Ren, “Scalable Federated Unlearning via Isolated and Coded Sharding”, IJCAI International Joint Conference on Artificial Intelligence, 2024:4551-4559. (CCF-A)
3. Y. Lin, Z. Gao, H. Du, D. Niyato, J. Kang, Z. Xiong, Z. Zheng, “Blockchain-Based Efficient and Trustworthy AIGC Services in Metaverse,” IEEE Transactions on Services Computing, vol. 17, no. 5, pp. 2067-2079, Sept.-Oct. 2024. (CCF-A)
4. Y. Lin, Z. Gao, H. Du, J. Kang, D. Niyato, Q. Wang, J. Ruan, S. Wan, “DRL-Based Adaptive Sharding for Blockchain-Based Federated Learning,” IEEE Transactions on Communications, vol. 71, no. 10, pp. 5992-6004, Oct. 2023. (CCF-B, Best Paper Award)
5. Y. Lin, J. Ren, J. Wang, N. Ma, Y. Zhang, S. Cui, Efficient and Trusted Federated Unlearning for Semantic Knowledge Base, Science China-Information Sciences (中国科学：信息科学), 2025. (CCF-A)

Representative Projects (PI)

1. PI, Postdoctoral Innovative Talent Support Program, Research on Blockchain-Network Integrated Unlearning Mechanisms for Data Element Circulation, 2024.09-2026.08.
2. PI, National Natural Science Foundation of China, Research on Full-Process Unlearning Methods for Data Element Circulation Governance, 2026.01-2028.12.
3. PI, Beijing Natural Science Foundation, Research on Key Technologies of Industrial Internet of Things Data Sharing for 4ross-domain Trusted Circulation, 2025.07-2028.06.
4. PI, CCF-Huawei Populus euphratica Technology Fund Special Track on Trusted Computing, Post-Hoc Fault-Tolerant Techniques for LLM-Generated Content Based on Machine Unlearning, 2025.02-2026.02.
5. PI, China Postdoctoral Science Foundation, Research on Data Unlearning Staged Closed-Loop Collaborative Mechanism, 2025.07-2026.08.

Service

1. Leading Contributors, IEEE COMSOC Best Readings in Privacy Preservation for Machine Learning in Communications.
2. Youth Editorial Board Members, Blockchain: Research and Applications.
3. Tutorial Organizer, “Trustworthy and Efficient Generative AI and Pretrained LLMs for Next-Generation Communications” at VTC2025-Fall.
4. Track Chair, “Blockchain Enabled Trusted Circulation of Data in IIoT” at CCF Blockchain Summit Forum 2025
5. Moderator, “Intelligent Transportation Systems Career Path to Net Zero” at IEEE Women in Engineering panel 2024.

Teaching

In accordance with university policy, postdoctoral researchers are not permitted to teach courses.

Collaboration

Although I currently do not hold independent supervision quotas as a postdoctoral researcher, I’m open to co-advising students (undergraduate or graduate) in collaboration with faculty members. I welcome collaborative thesis projects, internships, and exploratory research discussions — especially with curious minds who enjoy building, breaking, and improving things. If you’re interested in research topics like federated unlearning, blockchain, trustworthy AI, or data governance, feel free to reach out.

Let’s go! Time to clock out and have some fun!

I believe in reading more, moving more, and seeing more — whether it’s papers, people, mountains, or oceans.