柴云鹏
柴云鹏，中国人民大学信息学院院长、党委副书记、教授、博士生导师、中国人民大学“吴玉章”特聘教授。主要研究方向为智能计算系统、数据库系统、存储系统、云计算。担任中国计算机学会教育工委委员，VLDB Sponsor Chair，SIGKDD、WWW、Middleware、DASFAA 等国际会议程序委员会委员。先后主持和参与多项国家重点研发计划、国家自然科学基金联合基金等项目，担任openGauss开源社区CloudNative SIG三个Maintainer之一。在SIGMOD、VLDB、WWW、ASPLOS、ATC、TOS、TKDE等国际顶级会议和期刊上发表几十篇论文。获得深圳市科技进步一等奖、北京市教学成果一等奖、中国产学研创新与促进奖产学研合作创新成果奖一等奖、中国计算机学会科技进步二等奖等奖励。
科研项目：
[1] 国家重点研发计划项目课题，分布式知识图谱数据管理关键技术与系统，负责人。
[2] 国家重点研发计划项目子课题，阿里云流数据大规模在线分析示范应用，负责人。
[3] 面向多元异构存储架构的分布式键值存储系统关键技术研究，负责人。
[4] 基于访问特征分析的流媒体存储系统节能方法研究，负责人。
[5] 中国人民大学-中移信息联合实验室项目：OLAP数据库一体机新型存储系统研发项目，负责人。
[6] 面向新型数据库的特征量化分析及benchmark构建技术合作项目，负责人。
[7] 面向OS领域的多智能体协作技术研究项目，负责人。
[8] OpenPangu在数据智能领域的推理能力测评与优化，负责人。
[9]基于应用画像的Kubernetes多维资源智能调度方法，负责人。
[10] 预测技术在弹性伸缩场景的应用，负责人。
[11] 面向大数据多存储引擎统一数据访问系统开发项目，负责人。
科研成果：
[1] Luo, Y., Xie, M., Tong, Y., Jiang, S., & Chai, Y. (2025). Understanding Robustness Issues of Updatable Learned Indexes:[Experiments & Analysis]. Proceedings of the ACM on Management of Data, 3(4), 1-25.
[2] Bian, H., Geng, D., Li, H., Chai, Y., & Ailamaki, A. (2025, May). PixelsDB: Serverless and NL-Aided Data Analytics with Flexible Service Levels and Prices. In 2025 IEEE 41st International Conference on Data Engineering (ICDE) (pp. 4612-4615). IEEE.
[3] Ma, T., He, D., Ming, Z., Xu, J., Cui, L., & Chai, Y. (2025, June). Utilizing Contrastive Learning for Locating Network Anomalies in Real-time Conferencing Applications. In 2025 IEEE International Conference on Multimedia and Expo (ICME) (pp. 1-6). IEEE.
[4] Xu, D., Zhang, D., Li, T., Chai, Y., Sun, Z., Li, W., ... & Du, X. (2025, May). GeoLM: Performance-oriented Leader Management for Geo-Distributed Consensus Protocol. In IEEE INFOCOM 2025-IEEE Conference on Computer Communications (pp. 1-10). IEEE.
[5] Wu, P., Xie, M., Zhao, E., Zhang, D., Wang, J., Liang, X., ... & Chai, Y. (2025). Turbocharge {ANNS} on Real {Processing-in-Memory} by Enabling {Fine-Grained}{Per-PIM-Core} Scheduling. In 2025 USENIX Annual Technical Conference (USENIX ATC 25) (pp. 1223-1241).
[6] Guo, Y., Ge, J., Guo, P., Chai, Y., Li, T., Shi, M., ... & Ouyang, J. (2024, May). Pass: Predictive auto-scaling system for large-scale enterprise web applications. In Proceedings of the ACM Web Conference 2024 (pp. 2747-2758).
[7] Chen, Y., Tang, T., Xiang, E., Li, L., Zhao, W. X., Wang, J., Chai, Y. & Wen, J. R. (2025, August). Towards coarse-to-fine evaluation of inference efficiency for large language models. In China National Conference on Chinese Computational Linguistics (pp. 244-264). Singapore: Springer Nature Singapore.
[8] Ge, J., Zhang, H., Shi, B., Luo, Y., Guo, Y., Chai, Y., ... & Pan, A. (2023). SALI: A scalable adaptive learned index framework based on probability models. Proceedings of the ACM on Management of Data, 1(4), 1-25.
[9] Wang, Y., Wang, Z., Chai, Y., & Wang, X. (2023). Rethink the linearizability constraints of Raft for distributed systems. IEEE Transactions on Knowledge and Data Engineering, 35(11), 11815-11829.
[10] Sun, D., Tan, R., & Chai, Y. (2023). A universal SMR-aware cache framework with deep optimization for DM-SMR and HM-SMR disks. ACM Transactions on Storage, 19(3), 1-35.
[11] Ge, J., Shi, B., Chai, Y., Luo, Y., Guo, Y., He, Y., & Chai, Y. (2023, April). Cutting learned index into pieces: An in-depth inquiry into updatable learned indexes. In 2023 IEEE 39th International Conference on Data Engineering (ICDE) (pp. 315-327). IEEE.
[12] Ge, J., Zhang, H., Shi, B., Luo, Y., Guo, Y., Chai, Y., ... & Pan, A. (2023). SALI: A scalable adaptive learned index framework based on probability models. Proceedings of the ACM on Management of Data, 1(4), 1-25.
[13] Chai, Y., Ge, J., Zhang, Q., Chai, Y., Wang, X., & Zhang, Q. (2022). Correlation Expert Tuning System for Performance Acceleration. Big Data Research, 30, 100345.
[14] Bao, N., Chai, Y. P., Qin, X., & Wang, C. W. (2022). MacroTrend: A Write-Efficient Cache Algorithm for NVM-Based Read Cache. Journal of Computer Science and Technology, 37(1), 207-230.
[15] Chai, Y., Chai, Y., Wang, X., Wei, H., & Wang, Y. (2020). Adaptive lower-level driven compaction to optimize LSM-tree key-value stores. IEEE Transactions on Knowledge and Data Engineering, 34(6), 2595-2609.
[16] Sun, D., Chai, Y., Liu, C., Sun, W., & Zhang, Q. (2022, July). R2b: high-efficiency and fair i/o scheduling for multi-tenant with differentiated demands. In Proceedings of the 59th ACM/IEEE design automation conference (pp. 883-888).
[17] Sun, D., Song, Y., Chai, Y., Peng, B., Lu, F., & Deng, X. (2022, November). Light-GC: a lightweight and efficient garbage collection scheme for embedded file systems. In Proceedings of the 23rd ACM/IFIP International Middleware Conference (pp. 216-227).
[18] Wang, Y., Chai, Y., & Zhang, Q. (2022, September). WALOR: Workload-Driven Adaptive Layout Optimization of Raft Groups for Heterogeneous Distributed Key-Value Stores. In IFIP International Conference on Network and Parallel Computing (pp. 290-301). Cham: Springer Nature Switzerland.
[19] Ge, J. K., Chai, Y. F., & Chai, Y. P. (2021). Watuning: a workload-aware tuning system with attention-based deep reinforcement learning. Journal of Computer Science and Technology, 36(4), 741-761.
[20] Wang, Y., & Chai, Y. (2021, April). vRaft: accelerating the distributed consensus under virtualized environments. In International Conference on Database Systems for Advanced Applications (pp. 53-70). Cham: Springer International Publishing.
[21] Liang, J., & Chai, Y. (2021, April). CruiseDB: An LSM-tree key-value store with both better tail throughput and tail latency. In 2021 IEEE 37th International Conference on Data Engineering (ICDE) (pp. 1032-1043). IEEE.
[22] Wang, Y., Wang, Z., Chai, Y., & Wang, X. (2021, April). Rethink the linearizability constraints of raft for distributed key-value stores. In 2021 IEEE 37th International Conference on Data Engineering (ICDE) (pp. 1877-1882). IEEE.
[23] Ji, Y., Chai, Y., Zhou, X., Ren, L., & Qin, Y. (2020). Smart intra-query fault tolerance for massive parallel processing databases. Data Science and Engineering, 5(1), 65-79.
[24] Sun, D., & Chai, Y. (2020, March). SAC: A co-design cache algorithm for emerging SMR-based high-density disks. In Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems (pp. 1047-1061).
[25] Bao, N., Chai, Y., Zhang, Y., Wang, C., & Zhang, D. (2020, October). More space may be cheaper: multi-dimensional resource allocation for NVM-based cloud cache. In 2020 IEEE 38th International Conference on Computer Design (ICCD) (pp. 565-572). IEEE.
[26] Bao, N., Chai, Y., & Qin, X. (2019, March). A write-efficient cache algorithm based on macroscopic trend for NVM-based read cache. In 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE) (pp. 1245-1248). IEEE.
[27] Bao, N., Chai, Y., & Qin, X. (2019, March). A write-efficient cache algorithm based on macroscopic trend for NVM-based read cache. In 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE) (pp. 1245-1248). IEEE.
[28] Chai, Y., Chai, Y., Wang, X., Wei, H., Bao, N., & Liang, Y. (2019, April). LDC: a lower-level driven compaction method to optimize SSD-oriented key-value stores. In 2019 IEEE 35th International Conference on Data Engineering (ICDE) (pp. 722-733). IEEE.
[29] Liu, J., Chai, Y. P., Qin, X., & Liu, Y. H. (2018). Endurable SSD-based read cache for improving the performance of selective restore from deduplication systems. Journal of computer science and technology, 33(1), 58-78.
[30] Wang, C., Sun, D., Chai, Y., & Zhou, F. (2018, October). Enabling Accurate Performance Isolation on Hybrid Storage Devices in Cloud Environment. In 2018 IEEE 36th International Conference on Computer Design (ICCD) (pp. 565-568). IEEE.
[31] Wang, Y., Chai, Y., & Wang, X. (2018, November). ALOR: adaptive layout optimization of raft groups for heterogeneous distributed key-Value stores. In IFIP International Conference on Network and Parallel Computing (pp. 13-26). Cham: Springer International Publishing.
[32] Liu, J., Chai, Y., Yan, C., & Wang, X. (2015). A delayed container organization approach to improve restore speed for deduplication systems. IEEE transactions on parallel and distributed systems, 27(9), 2477-2491.
[33] Liang, Y., Chai, Y., Bao, N., Chen, H., & Liu, Y. (2016, June). Elastic queue: A universal SSD lifetime extension plug-in for cache replacement algorithms. In Proceedings of the 9th ACM International on Systems and Storage Conference (pp. 1-11).
[34] Dai, N., Chai, Y., Liang, Y., & Wang, C. (2015, May). ETD-cache: An expiration-time driven cache scheme to make SSD-based read cache endurable and cost-efficient. In Proceedings of the 12th ACM International Conference on Computing Frontiers (pp. 1-8).
[35] Chai, Y., Du, Z., Qin, X., & Bader, D. A. (2015). WEC: Improving durability of SSD cache drives by caching write-efficient data. IEEE Transactions on computers, 64(11), 3304-3316.