个人简介：
陈建国，软件工程学院副教授，博士生导师，逸仙学者，高性能计算课题组负责人。入选国家级青年人才，广东省重大人才工程、全球Top-2%科学家榜单。湖南大学计算机科学与技术博士，美国伊利诺伊大学联合培养博士，曾任加拿大多伦多大学博士后，新加坡A*STAR科技研究局研究科学家。承担国家自然科学基金面上项目、青年项目、博士后国际交流计划派出项目、广西省重点研发计划、广东省自然科学基金、湖南省自然科学基金、CCF 华为胡杨林基金、CCF 百川大模型基金及华为、腾讯、电信、电力等项目，作为骨干参与863计划、973计划等国家级重大项目，累计到账经费700余万元。研究聚焦显存极致优化、异构内存系统、细粒度通算融合算子、分布式推理加速等关键技术，成果已在国家超算长沙中心、国家超算广州中心、中国移动等国产异构算力平台落地应用，具备成熟的系统设计、算法实现与工程落地能力。目前在IEEE-TII、IEEE-TITS、IEEE-TPDS、IEEE-TKDE、EuroSys、ATC、ASPLOS、WWW等国际著名期刊和会议上发表学术论文80余篇，授权发明专利18项。担任国际学术期刊《Neurocomputing 》副编辑、《International Journal of Embedded Systems》副编辑、《Journal of Current Scientific Research》副编辑、《Information Sciences》客座编辑、《Neural Computing and Applications》客座编辑，以及多个国际学术会议的大会主席。
研究领域：高性能计算，大模型系统，异构计算架构，存算协同。
研究与招生：招收博士后、博士、硕士研究生与本科实习生。
欢迎有意报考的同学通过电子邮件与我取得联系。
电子邮件：
chenjg33 at mail.sysu.edu.cn
学术期刊征稿：
Mathematics征稿（中科院SCI 3区），并行与分布式计算理论与应用专刊，欢迎投稿!
Special Issue "Parallel and Distributed Computing: Theory and Applications"
https://www.mdpi.com/journal/mathematics/special_issues/3GA6ZFCFD4
科研项目
1. 2026-2027华东院校企合作项目
2. 2026-2027电信校企合作项目
3. 2026-2027腾讯校企合作项目
4. 2026-2028 深圳市重点研发项目
5. 2025-2026华为校企合作项目
6. 2025-2026 CCF-华为胡杨林基金系统软件专项
7. 2024-2027, 国家自然科学基金面上项目
8. 2024-2026, 广西省重点研发计划项目子课题
9. 2023-2024 CCF-百川-英博大模型基金专项
10. 2023-2025, 广东省自然科学基金面上项目
11. 2021-2023, 国家自然科学基金青年项目
12. 2020-2021, 湖南省自然科学基金青年项目
13. 2018-2020, 博士后国际交流计划派出项目
学术论文
[1] Y. Jiang, et al. Crimson: Collaborative Parameter Updates for Efficient Pipeline Training of Large Language Models. EuroSys 2026.
[2] Z. Hong, et al. Efficient Multi-modal Serving via Module Multiplexing. EuroSys 2026.
[3] Z. Fang, et al. Fate: Fast Edge Inference of Mixture-of-Experts Models via Cross-Layer Gate. WWW 2026.
[4] J. Chen, et al. A Federated Adaptive Large Language Model Fine-Tuning Framework for Software Development. IEEE Transactions on Services Computing, 2025
[5] J. Chen, et al. A Privacy-Preserving Edge Inference Framework for Low-Altitude UAV Swarm Intelligence. 21st IFIP International Conference, NPC 2025
[6] Z. Cai, et al. Blockchain-Empowered Federated Learning: Benefits, Challenges, and Solutions. IEEE Transactions on Big Data. 2025
[7] Y. Huang, et al. Obscura: Concealing Recomputation Overhead in Training of Large Language Models with Bubble-filling Pipeline Transformation. ATC 2025.
[8] X. Hua, et al. SmartAFL: Enhancing Asynchronous Federated Learning with Staleness-Aware Aggregation and Smart Contracts, SCECS 2025
[9] Z. Fang, et al. Klotski: Efficient Mixture-of-Expert Inference via Expert-Aware Multi-Batch Pipeline. ASPLOS 2025.
[10] J. Zhang, et al. Efficient Execution of Arbitrarily Complex Cross-shard Contracts for Blockchain Sharding. IEEE Transactions on Computers. 2025
[11] Z. Cai, et al. F-CODELLM: A federated learning framework for adapting large language models to practical software development. IEEE/ACM ICSE 2024
[12] Z. Hong, et al. Optimus: Warming Serverless ML Inference via Inter-Function Model Transformation. EuroSys 2024.
[13] T. Cai, et al. SmartChain: A Dynamic and Self-Adaptive Sharding Framework for IoT Blockchain. IEEE Transactions on Services Computing, 2024.
[14] J. Chen, et al. Non-cooperative game algorithms for computation offloading in mobile edge computing environments. Journal of Parallel and Distributed Computing, 2023
[15] J. Chen, et al. Synchronous Medical Image Augmentation Framework for Deep Learning-based Image Segmentation. Computerized Medical Imaging and Graphics. 2023
[16] J. Chen, et al. Privacy-Preserving Deep Learning Model for Decentralized VANETs Using Fully Homomorphic Encryption and Blockchain. IEEE Transactions on Intelligent Transportation Systems, 2022
[17] J. Peng, et al. HEA-PAS: A Hybrid Energy Allocation Strategy for Parallel Applications Scheduling on Heterogeneous Computing Systems. Journal of Systems Architecture, 2022
[18] J. Peng, et al. Reliability/Performance-aware Scheduling for Parallel Applications with Energy Constraints on Heterogeneous Computing Systems. IEEE Transactions on Sustainable Computing, 2022
[19] B. Pu, et al. MVSTT: A Multi-View Spatial-Temporal Transformer Network for Traffic Forecasting, IEEE Transactions on Cybernetics, 2022
[20] Y. Kang, et al. A deep graph network with multiple similarity for user clustering in human–computer interaction. ACM Transactions on Multimedia Computing, Communications and Applications, 2022
[21] J. Chen, et al. A Domain Adaptive Density Clustering Algorithm for Data with Varying Density Distribution. IEEE Transactions on Knowledge and Data Engineering. 2021
[22] J. Chen, et al. Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System using Gated Graph Neural Network. ACM Transactions on Intelligent Systems and Technology. 2021
[23] J. Chen, et al. Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems using Multi-objective Reinforcement Learning. ACM Transactions on Cyber-Physical Systems, 2021
[24] J. Hu, et al. Coalition formation for deadline-constrained resource procurement in cloud computing. Journal of Parallel and Distributed Computing, 2021
[25] H. Wang, et al. A Spatiotemporal Graph Neural Network for session-based recommendation. Expert Systems with Applications, 2021
[26] J. Chen, et al. Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing, IEEE Transactions on Industrial Informatics, 2019
[27] J. Chen, et al. Yu. A Bi-layered Parallel Training Architecture for Large-scale Convolutional Neural Networks. IEEE Transactions on Parallel and Distributed Systems. 2019
[28] J. Chen, et al. A Periodicity-based Parallel Time Series Prediction Algorithm in Cloud Computing Environments. Information Sciences, 2019
授权专利
[1] 个性化联邦边缘学习方法、装置、存储介质及计算机设备. ZL2025102434840, 发明专利, 2025
[2] 一种基于区块链和深度学习的去中心化分布式VANET系统. ZL202010262063X, 发明专利, 2021
[3] 医学图像中病症组织定位方法、装置与设备. 2019105604119, 发明专利, 2021
[4] 计算任务卸载系统与方法. ZL2019105948003, 发明专利, 2019
[5] Coflow协同作业流调度感知的数据流划分方法与装置. ZL2019105948003, 发明专利, 2021
[6] 半精度压缩感知采样方法. ZL201910417842X. 发明专利, 2021
[7] 设备体检报告生成方法、装置、计算机设备和存储介质. ZL201910597798, 发明专利, 2020
[8] 一种基于社区检索的影响力社区搜索方法和系统. ZL2019104215734, 发明专利, 2020
[9] Spark Streaming中间数据分区方法、装置、计算机设备和存储介质. ZL2019104380360, 发明专利, 2021
[10] 一种基于向量化的日志模板提取方法和系统. ZL2019104317884, 发明专利, 2020
[11] 数据点组查询方法、装置、计算机设备和存储介质. ZL2019104605580, 发明专利, 2021
著作/教材
1. 陈建国 编著. 《PHP程序设计案例教程》. 机械工业出版社. 2012
2. 陈建国 编著. 《C#项目开发经典案例教程》. 浙江大学出版社. 2014
3. 陈建国 编著. 《PHP程序设计案例教程》(第二版). 机械工业出版社. 2020
4. 陈建国 等编著. 《C#.NET项目开发案例教程》. 清华大学出版社. 2022
5. 陈浩, 陈建国等著. 学术专著《开放协同的科技大数据汇聚融合与演化分析》. 科学出版社. 2022
学术服务
1. 《Neurocomputing 》副编辑
2. 《International Journal of Embedded Systems》副编辑
3. 《Journal of Current Scientific Research》副编辑
4. 《Information Sciences》客座编辑
5. 《Neural Computing and Applications》客座编辑
6. International Conference on Intelligence (ICI 2026). Program Chair
7. International Conference on Blockchain, Artificial Intelligence, and Trustworthy Systems (BlockSys 2025), Program Committee Chair
8. International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2024). General Chair
