Single pass Poisson disk sampling via circle packing
Jun Cui, Zeyu Li, Yuxiao Li, Ziheng Guo, Ziming Dai, and Jiawan Zhang. "Single pass Poisson disk sampling via circle packing." Computers & Graphics 135 (2026): 104548.
CV
Education
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
- M.S. in Jekyll, GitHub University, 2014
- B.S. in GitHub, GitHub University, 2012
Work experience
- Spring 2024: Academic Pages Collaborator
- GitHub University
- Duties includes: Updates and improvements to template
- Supervisor: The Users
- Fall 2015: Research Assistant
- GitHub University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
- Summer 2015: Research Assistant
- GitHub University
- Duties included: Tagging issues
- Supervisor: Professor Git
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
Stratos: An End-to-End Distillation Pipeline for Customized LLMs under Distributed Cloud Environments
Ziming Dai, Tuo Zhang, Fei Gao, Xingyi Cai, Xiaofei Wang, Cheng Zhang, Wenyu Wang, and Chengjie Zang. "Stratos: An End-to-End Distillation Pipeline for Customized LLMs Under Distributed Cloud Environments." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 40, no. 47, pp. 40506-40512. 2026.
NSR-Boost: A Neuro-Symbolic Residual Boosting Framework for Industrial Legacy Models
Ziming Dai, Dabiao Ma, Jinle Tong, Mengyuan Han, Jian Yang, Hongtao Liu, Haojun Fei, and Qing Yang. "NSR-Boost: A Neuro-Symbolic Residual Boosting Framework for Industrial Legacy Models." Accepted by the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2026).
TS-PEFT: Unveiling Token-Level Redundancy in Parameter-Efficient Fine-Tuning
Dabiao Ma, Ziming Dai, Zhimin Xin, Shu Wang, Jian Yang, and Haojun Fei. "TS-PEFT: Unveiling Token-Level Redundancy in Parameter-Efficient Fine-Tuning." In the 35th International Joint Conference on Artificial Intelligence. 2026.
ACME: Adaptive Customization of Large Models via Distributed Systems
Ziming Dai, Chao Qiu, Fei Gao, Yunfeng Zhao, Xiaofei Wang. "ACME: Adaptive Customization of Large Models via Distributed Systems." In 2025 IEEE 45th International Conference on Distributed Computing Systems (ICDCS), pp. 45-55. IEEE, 2025.
Multi-Granularity Federated Learning by Graph-Partitioning
Ziming Dai, Yunfeng Zhao, Chao Qiu, Xiaofei Wang, Haipeng Yao, and Dusit Niyato. "Multi-Granularity Federated Learning by Graph-Partitioning." IEEE Transactions on Cloud Computing 13, no. 1 (2024): 18-33.
MG²FL: Multi-Granularity Grouping-Based Federated Learning in Green Edge Computing Systems
Ziming Dai, Yunfeng Zhao, Chao Qiu, Xiaofei Wang, and F. Richard Yu. "MG²FL: Multi-Granularity Grouping-Based Federated Learning in Green Edge Computing Systems." In GLOBECOM 2023-2023 IEEE Global Communications Conference, pp. 152-157. IEEE, 2023.
AImers-6G: AI-Driven Region-Temporal Resource Provisioning for 6G Immersive Services
Qiu Chao, Zheyuan Chen, Xiaoxu Ren, Ziming Dai, Cheng Zhang, and Xiaofei Wang. "AImers-6G: AI-driven region-temporal resource provisioning for 6G immersive services." IEEE Wireless Communications 30, no. 3 (2023): 196-203.
Talks
Conference Proceeding talk 3 on Relevant Topic in Your Field
Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA, USA
Talk 2 on Relevant Topic in Your Field
Talk at London School of Testing, London, UK
Tutorial 1 on Relevant Topic in Your Field
Tutorial at UC-Berkeley Institute for Testing Science, Berkeley, CA, USA
Talk 1 on Relevant Topic in Your Field
Talk at UC San Francisco, Department of Testing, San Francisco, CA, USA
Teaching
Service and leadership
- Currently signed in to 43 different slack teams