Dingyuan SHI (史鼎元)

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Ph.D candidate
Big Data Analysis Group
School of Computer Science and Enigneering
Beihang University (BUAA)
Google Scholar
GitHub

Short Biography

Dingyuan Shi is currently a Ph.D. candidate in the School of Computer Science and Engineering (SCSE) at Beihang University (BUAA), under the supervision of Prof. Yongxin Tong. He formerly received a B.Eng. degree in computer science and technology from Beihang University in 2020.

Research Interests

Publications

  1. [DASFAA’24] Haolong Yang, Dingyuan Shi, Yuanyuan Zhang, Yi Xu, Ke Xu. "An Efficient Local Differential Privacy Approach for Trajectory Publishing with High Utility". In Proceedings of the 29th International Conference on Database Systems for Advanced Applications, Gifu, Japan, July 02-05, 2024. (CCF-B) [paper]

  2. [ICLR’24] Dingyuan Shi, Yongxin Tong, Zimu Zhou, Ke Xu, Zheng Wang, Jieping Ye. "Graph-Constrained Diffusion for End-to-end Path Planning". In Proceedings of the 12th International Conference on Learning Representations, Vienna, Austria, May 07-11, 2024. [paper][poster][code]

  3. [ICDE’23] Dingyuan Shi, Nan Zhou, Yongxin Tong, Zimu Zhou, Yi Xu, Ke Xu. "Collision-Aware Route Planning in Warehouses Made Efficient: A Strip-based Framework". In Proceedings of the 39th International Conference on Data Engineering, Pages 869-881, Anaheim, CA, USA, April 03-07, 2023. (CCF-A) [paper][slides]

  4. [ICDE’22] Dingyuan Shi, Yongxin Tong, Zimu Zhou, Ke Xu, Wenzhe Tan, Hongbo Li. "Adaptive Task Planning for Large-Scale Robotized Warehouses". In Proceedings of the 38th International Conference on Data Engineering, Pages 3327-3339, Kuala Lumpur, Malaysia, May 09-12, 2022. (CCF-A) [paper][slides][news]

  5. [TKDE’23] Yongxin Tong, Dingyuan Shi, Yi Xu, Weifeng Lv, Zhiwei (Tony) Qin, Xiaocheng Tang. "Combinatorial Optimization Meets Reinforcement Learning: Effective Taxi Order Dispatching at Large-Scale". IEEE Transactions on Knowledge and Data Engineering. 2023,35(10):9812-9823. (CCF-A) [paper][code]

  6. [KDD’21] Dingyuan Shi, Yongxin Tong, Zimu Zhou, Bingchen Song, Weifeng Lv, Qiang Yang. "Learning to Assign: Towards Fair Task Assignment in Large-Scale Ride Hailing". In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Singapore, Singapore, August 14-18, 2021, 3549-3557. (CCF-A) [paper][slides][code]

  7. [JOS’21] Dingyuan Shi, Yansheng Wang, Pengfei Zheng, Yonxin Tong, "Cross-silo Federated Learning-to-Rank". Journal of Software, 2021,32(3):669-688 (in Chinese with English abstract). (CCF-A) [paper (CN)][slides (CN)]

  8. [JOS’22] Shuyuan Li, Yudian Ji, Dingyuan Shi, Wangdong Liao, Lipeng Zhang, Yongxin Tong, Ke Xu. "Data Federation System for Multi-party Security". Journal of Software. 2022,33(3):1111-1127 (in both Chinese and English). (CCF-A) [paper (CN)][paper (EN)]

  9. [ICDE’21] Yansheng Wang, Yongxin Tong, Dingyuan Shi, Ke Xu. "An Efficient Approach for Cross-Silo Federated Learning to Rank". In Proceedings of the 37th International Conference on Data Engineering, Pages 648-659, Chania, Crete, Greece, April 19-22, 2021. (CCF-A) [paper]

  10. [KDD’21] Xiaocheng Tang, Fan Zhang, Zhiwei Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye. "Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms". In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Singapore, Singapore, August 14-18, 2021, 3605-3615. (CCF-A) [paper]

  11. [DEB’20] Yongxin Tong, Yansheng Wang, Dingyuan Shi. "Federated Learning in the Lens of Crowdsourcing". IEEE Data Engineering Bulletin, 43(3): 26-36, 2020. [paper]

  12. [AAAI’20] Yansheng Wang, Yongxin Tong, Dingyuan Shi. "Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework". In Proceedings of the 34th AAAI Conference on Artificial Intelligence, Pages 6283-6290, New York, USA, January 7-12, 2020. (CCF-A) [paper][poster][code]

Patents

  1. 童咏昕, 史鼎元, 魏淑越, 徐毅, 许可. 一种高效的物流机器人集群路径规划方法. 北京市：CN115963838A, 2023-04-14.

  2. 童咏昕, 史鼎元, 宋冰晨, 徐毅, 许可. 一种面向大规模打车平台的任务匹配公平方法. 北京市：CN113240339B, 2022-08-30.

Honors

Intern Experience

  1. AIGC Intern (2024.3-), ByteDance

  2. R&D Intern (2023.9-2024.2), Momenta

  3. Research Intern (2022.12-2023.9), Alibaba DAMO Academy

  4. Algorithm Intern (2021.7-2022.9), Geekplus Technology

Academic Services

Miscellaneous