2025

• [arXiv 2025]  [LLM Framework]   Yiran Guo, Lijie Xu*, Jie Liu*, Dan Ye, Shuang Qiu. Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language Models. arXiv 2025 [Paper][Code]
• [ACM TACO 2025]  [BigData+Memory]   Yicheng Wang, Lijie Xu*, Tian Guo, Wensheng Dou, Hongbin Zeng, Wei Wang, Jun Wei, Tao Huang. BridgeGC: An Efficient Cross-Level Garbage Collector for Big Data Frameworks. ACM Transactions on Architecture and Code Optimization (2025) [Paper][Code]
• [ICDE 2025]]  [BigData+AI]   Zheng Qin, Zheheng Liang*, Lijie Xu*, Wentao Wu, Mingchao Wu, Wuqiang Shen, Wei Wang. FreewayML: An Adaptive and Stable Streaming Learning Framework for Dynamic Data Stream. ICDE 2025 [Paper][Code]
• [ICDE 2025]  [Database]   Lei Tang, Wensheng Dou, Yingying Zheng, Lijie Xu, Wei Wang, Jun Wei, Tao Huang. Proving Cypher Query Equivalence. ICDE 2025 [Paper][Code]

2024

• [arXiv 2024]  [Database+AI]   Lijie Xu, Chulin Xie, Yiran Guo, Gustavo Alonso, Bo Li, Guoliang Li, Wei Wang, Wentao Wu, Ce Zhang. TablePuppet: A Generic Framework for Relational Federated Learning. arXiv 2024 [Paper][Code]
• [VLDB Journal 2024]  [Database+AI]   Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang. Stochastic Gradient Descent without Full Data Shuffle: with Applications to In-Database Machine Learning and Deep Learning Systems. The VLDB Journal (2024) [Paper][Code for PyTorch] [Code for PostgreSQL]
• [ICDE 2024]  [Database+AI]   Guoliang Li, Ji Sun, Lijie Xu, Shifu Li, Jiang Wang, Wen Nie. GaussML: An End-to-End In-Database Machine Learning System. ICDE 2024 (industrial track) [Paper][Code]
• [Journal of Software 2024]  [BigData]   Zheng Qin, Lijie Xu*, Wei Chen, Yi Wang, Mingchao Wu, Hongbin Zeng, Wei Wang. High Throughput Optimization Technique for Apache Flink. Journal of Software (in Chinese) [Paper]

2022

• [SIGMOD 2022]  [Database+AI]   Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang. In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. SIGMOD Conference 2022: 1286-1300. [Paper][Code]
• [ICSE SEIP 2022]  [BigData]   Feng Zhu, Lijie Xu*, Gang Ma, Shuping Ji, Jie Wang, Gang Wang, Hongyi Zhang, Kun Wan, Mingming Wang, Xingchao Zhang, Yuming Wang, Jingpin Li. An Empirical Study on Quality Issues of eBay's Big Data SQL Analytics Platform. ICSE (SEIP) 2022: 33-42 [Paper]
• [Science China Journal 2022]  [BigData]   Hui Li, Shuping Ji, Hua Zhong, Wei Wang, Lijie Xu, Zhen Tang, Jun Wei, Tao Huang. LPW: An Efficient Data-Aware Cache Replacement Strategy for Apache Spark. SCIENCE CHINA Information Sciences, (2022) [Paper]

2021

• [ICDCS 2021]  [AI+System]   Shijian Li, Oren Mangoubi, Lijie Xu, and Tian Guo. Sync-switch: Hybrid parameter synchronization for distributed deep learning. ICDCS 2021: 528-538 [Paper][Code]
• [Journal of Software 2021]  [BigData+Memory]   Yicheng Wang, Hongbin Zeng, Lijie Xu*, Wei Wang, Jun Wei, Tao Huang. A Survey on JVM Optimization for Big Data Processing Frameworks. Journal of Software (in Chinese) [Paper]

2020

• [ICDCS 2020]  [BigData+AI]   Lijie Xu, Xingtong Ye, Kai Kang, Tian Guo, Wensheng Dou, Wei Wang, and Jun Wei. DistStream: An Order-Aware Distributed Framework for Online-Offline Stream Clustering Algorithms. ICDCS 2020: 842-852 [Paper]
• [ISSTA 2020]  [BigData+Memory]   Hui Li, Dong Wang, Tianze Huang, Yu Gao, Wensheng Dou, Lijie Xu, Wei Wang, Jun Wei, Hua Zhong. Detecting Cache-Related Bugs in Spark Application. ISSTA 2020: 363-375 [Paper]

2019

• [VLDB 2019]  [BigData+Memory]   Lijie Xu, Tian Guo, Wensheng Dou, Wei Wang, and Jun Wei. An Experimental Evaluation of Garbage Collectors on Big Data Applications. Proc. VLDB Endow. 12(5): 570-583 (2019) [Paper]
• [ICAC 2019]  [AI+System]   Shijian Li, Robert J. Walls, Lijie Xu, and Tian Guo. Speeding up Deep Learning with Transient Servers. ICAC 2019: 125-135 [Paper]

2018 or earlier

• Teaching Assistant — ETH Zürich, Data Modeling and Databases, Spring 2022

• SIGMOD 2022 — June, 2022 — In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. [Video]

• Program Committee Member, ICDCS 2021
• Reviewer of ACM Transactions on Computer Systems (TOCS)
• Reviewer of IEEE Transactions on Reliability
• Reviewer of Journal of Parallel and Distributed Computing (JPDC) - Elsevier

• Lijie Xu, Yafen Fang, The design principles and implementation of Apache Spark (大数据处理框架Apache Spark设计与实现), Publishing House of Electronics Industry, July 2020
• Cover:
• Preface: https://github.com/JerryLead/ApacheSparkBook/blob/master/Preface.pdf or here.
• Purchase link: https://item.jd.com/12924768.html

• Lijie Xu, Spark Internals (about the design and implementation of Apache Spark, 5K+ Stars and 1.8K+ Forks in github)