Rong Gu(顾荣)
Short Biography
Knowing yourself is the beginning of all wisdom. –Aristotle
I am currently a distinguished researcher in the School of Computer Science at Nanjing University. My research interests include Cloud and Big Data computing systems, Distributed AI Training and Inference System, Intelligent Data Management System, etc. I have published over 70 papers in EuroSys, USENIX ATC, SIGMOD, VLDB, ICDE, KDD, WWW, INFOCOM, VLDBJ, IEEE TPDS, TKDE, TON, and published three monographs. I received the DAMO Academy Young Fellow Award, IEEE TCSC Award for Excellence in Scalable Computing (Early Career), IEEE HPCC 2022 Best Paper Award, the first prize of Jiangsu Science and Technology Prize in 2018, Outstanding Alibaba Innovative Research Program Award in 2023, Tecent Cloud Valuable Professional (TVP) Award in 2021, the first place of the 30th SortBenchmark Competition CloudSort Track (Record Holder). My research results have been adopted by a number of well-known open source software such as Apache Spark, Alluxio, and leading IT/domain companies, including Alibaba, Baidu, Tencent, ByteDance, Huatai Securities, Intel, Sinopec, Weibo and so on. I am the community chair of the Fluid open source project (CNCF Sandbox project), a founding PMC member & maintainer of Alluxio (formly Tachyon) open source project. I am also the co-program chair of IEEE iThings’22,IEEE SocialCom’23, the co-chair of 23rd ChinaSys, vice program chair of ICA3PP’25.
Bio in Chinese(中文简介):
顾荣,南京大学特聘研究员,博士生导师,教育部青年长江学者,达摩院青橙奖获奖者(2023),担任Fluid开源社区主席(Linux基金会旗下CNCF官方项目)、ACM ChinaSys执行委员、中国计算机学会(CCF)分布式计算与系统专委常务委员/大数据专家委员会执行委员/系统软件专委执行委员/数据库专委执行委员(优秀执委)/开源发展委员会执行委员(优秀执委)/南京秘书长。
研究领域:主要领域为云计算与大数据系统、智能计算系统,目前关注大模型推理与训练系统、云原生计算系统、智能数据管理等方向,在相关研究领域共发表录用论文70余篇,包括一流国际学术期刊和会议EuroSys, USENIX ATC, SIGMOD, VLDB, ICDE, KDD, WWW, INFOCOM, VLDBJ, IEEE TPDS, TON, TKDE等,出版学术专著3部,授权发明专利20项。
奖项荣誉:获得江苏省科学技术一等奖、阿里巴巴达摩院青橙奖(2023)、IEEE TCSC Early Career Award(2022, 年度全球5人)、CCF分布式计算与系统专委会青年创新先锋(年度全国2人)、IEEE HPCC会议最佳论文奖、CCF大数据学术会议最佳应用论文奖、阿里巴巴优秀学术合作项目奖、华为公司“难题揭榜”火花奖、腾讯云最具价值专家奖、中兴通讯产学研优秀合作项目奖、中国开源创新大赛一等奖、南京大学青年五四奖章、金陵青年学者、国际计算机排序基准评估比赛CloudSort赛道第1名、ACM南京分会学术新星奖、江苏省计算机学会青年科技奖/优秀科技工作者、CCF数据库专委会优秀执行委员、CCF开源发展委员会优秀执行委员、中国信通院OSCAR尖峰开源人物。
I am recruiting PhD, Master and Undergraduate students. If interested, please feel free to drop me an email.
本人招收研究生(博士生和硕士生)、本科实习生、博士后以及科研助理(长期开放),对大模型推理与训练系统、云原生计算系统、智能数据管理方向感兴趣的同学,欢迎与我联系(gurong[at]casinolhj.com)。本团队科研经费稳定(服务器集群/GPU设备齐全、科研劳务补助充裕、提供校外住宿补贴、大厂实习机会丰富),科研氛围轻松,欢迎联系加入!要求入组同学为人正直,沟通坦诚,并对本团队研究方向感兴趣、踏实勤奋、有一定自驱力和较好抗压能力。
Research
My research interests include
LLM Inference and Training System
Cloud Native Computing System
Intelligent Data Management
News
06/2025 Congratulations on the graduation of all my 2022-year Master students Han Li, Xiaozheng Zhang, Qiming Chen, Wenjie Bao, Ruizhang Yang, Wenxiao Wang, and Linyi Song! (祝贺指导和联合指导的所有2022级硕士研究生(7位)均按时顺利毕业!)
06/2023 Congratulations on the graduation of all my 2020-year Master students Zhong Weichang, Chen Guowang, Chen Yi, and Chen Yuquan! (祝贺指导的所有2020级硕士研究生钟伟畅、陈国旺、陈义、陈雨铨均按时顺利毕业!)
Selected Recent Publications
[SIGMOD'26]HotPrefix: Hotness-Aware KV Cache Scheduling for Efficient Prefix Sharing in LLM Inference Systems. (SIGMOD, CCF-A), 2026.
[SIGMOD'26]Hourglass: An Adaptive Range Filter with Lightweight Hybrid Encoding. (SIGMOD, CCF-A), 2026.
[VLDB'23]ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation. (VLDB, CCF-A), 2023.
[ATC'23]Adaptive Online Cache Capacity Optimization via Lightweight Working Set Size Estimation at Scale. (USENIX ATC, CCF-A), 2023.
[EuroSys'24]Wormhole Filters: Caching Your Hash on Persistent Memory. (EuroSys, CCF-A), 2024.
[SIGMOD'26]Gem: Scalable Monotonic Graph Processing Beyond Billion-Scale on a Single Machine. (SIGMOD, CCF-A), 2026.
[SIGMOD'25]VEGA: An Active-tuning Learned Index with Group-Wise Learning Granularity. (SIGMOD, CCF-A), 2025.
[ICDE'25]Local-to-cloud Database Synchronization via Fine-grained Hybrid Compression. (ICDE, CCF-A), 2025.
[KDD'24]ACER: Accelerating Complex Event Recognition via Two-Phase Filtering under Range Bitmap-Based Indexes. (KDD, CCF-A), 2024.
[TPDS'23]High-level Data Abstraction and Elastic Data Caching for Data-intensive AI Applications on Cloud-native Platforms. (IEEE TPDS, CCF-A), 2023.
[TPDS'26]Parallel Wormhole Filters: High-Performance Approximate Membership Query Data Structures for Persistent Memory. (IEEE TPDS, CCF-A), 2026.
[TKDE'23]Seesaw Counting Filter: A Dynamic Filtering Framework for Vulnerable Negative Keys. (IEEE TKDE, CCF-A), 2023.
[ToN'24]Fluid-Shuttle: Efficient Cloud Data Transmission based on Serverless Computing Compression. (ACM/IEEE ToN, CCF-A), 2024.
[INFOCOM'24]The Reinforcement Cuckoo Filter. (IEEE INFOCOM, CCF-A), to appear, 2024.
[INFOCOM'23]Time and Cost-Efficient Cloud Data Transmission based on Serverless Computing Compression. (IEEE INFOCOM, CCF-A), 2023.
[ATC'22]Meces: Latency-efficient Rescaling via Prioritized State Migration for Stateful Distributed Stream Processing Systems. (USENIX ATC, CCF-A), 2022.
[ICDE'22]Fluid: Dataset Abstraction and Elastic Acceleration for Cloud-native Deep Learning Training Jobs. (IEEE ICDE, CCF-A), 2022.
[TPDS'22]Liquid: Intelligent Resource Estimation and Network-Efficient Scheduling for Deep Learning Jobs on Distributed GPU Clusters. (IEEE TPDS, CCF-A), 2022.
[ICDE'22]Bamboo Filters: Make Resizing Smooth. (IEEE ICDE, CCF-A), pp. 979-991, 2022.
[HPCC'22, Best Paper Award]Efficient, Scalable and Robust Data Shuffle Service for Distributed MapReduce Computing on Cloud. (IEEE HPCC, CCF-C), 2022.
[VLDBJ'22]A Pareto Optimal Bloom Filter Family with Hash Adaptivity (VLDB Journal, CCF-A), 2022.
[WWW'22]Seesaw Counting Filter: An Efficient Guardian for Vulnerable Negative Keys During Dynamic Filtering (WWW, CCF-A), 2022.
[TPDS'18]Penguin: Efficient Query-based Framework for Replaying Large Scale Historical Data. (IEEE TPDS, CCF-A), 2018.
[TPDS'17]Improving Execution Concurrency of Large-Scale Matrix Multiplication on Distributed Data-Parallel Platforms. (IEEE TPDS, CCF-A), 2017.
[ToN'23]SAFE: Service Availability via Failure Elimination Through VNF Scaling. (ACM/IEEE ToN, CCF-A), 2023.
[ToN'24]A Generic Framework for Finding Special Quadratic Elements in Data Streams. (ACM/IEEE ToN, CCF-A), 2024.
[ToN'24]Bamboo Filters: Make Resizing Smooth (Journal Version). (ACM/IEEE ToN, CCF-A), 2024.
[TKDE'24]A Survey of Multi-dimensional Indexes: Past and Future Trends. (IEEE TKDE, CCF-A), 2024.
[ICDE'21]Hash Adaptive Bloom Filter. (IEEE ICDE, CCF-A), 2021.
[ICDE'19]BENU: Distributed Subgraph Enumeration With Backtracking-based Framework. (IEEE ICDE, CCF-A), 2019.
[TPDS'21]Towards Efficient Large-scale Interprocedural Program Static Analysis on Distributed Data-Parallel Computation. (IEEE TPDS, CCF-A), 2021.
[TPDS'21]Towards Efficient Distributed SubgraphEnumeration via Backtracking-based Framework. (IEEE TPDS, CCF-A), 2021.
[TPDS'19]Efficient and Scalable Functional Dependency Discovery on Distributed Data-Parallel Platforms. (IEEE TPDS, CCF-A), 2019.
[TMC'25]A Privacy-Preserving Auction for Task Offloading and Resource Allocation in UAV-Assisted MEC. (IEEE TMC, CCF-A), 2025.
[TMC'24]Joint Deployment of Truck-drone Systems for Camera-based Object Monitoring. (IEEE TMC, CCF-A), 2024.
[TMC'23]Placing Wireless Chargers with Multiple Antenna. (IEEE TMC, CCF-A), 2023.
[TMC'22]Placing Wireless Chargers with Limited Mobility. (IEEE TMC, CCF-A), 2022.
See more info of my publications
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