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研究方向

本人的研究方向位于数据系统与 AI 的交叉领域，主要关注如何构建高效、可扩展且具备良好可用性的智能系统，致力于研究 AI 工作负载在数据与系统基础设施上的运行特性，并通过系统与数据层面的优化方法，提升模型计算效率、数据利用效率以及系统性能，为复杂数据驱动型应用提供可靠支撑。

在研究方法上，本人强调以数据为中心、以系统为支撑的 AI 研究视角。不同于单纯从模型或算法层面进行优化，本人更关注数据组织方式、访问机制以及系统执行策略对 AI 效率与稳定性的影响。通过分析数据与计算在系统中的协同关系，本人希望探索能够在保持模型能力的同时，有效降低系统开销、提升运行效率的通用方法。

在较早阶段的研究中，本人主要围绕数据分析系统中的效率与完整性问题开展工作，积累了扎实的系统研究基础。此后，本人有较长一段时间深入参与创业，直接面对真实系统的设计、实现与演进。这段经历更加全面地打磨了本人对系统在工程环境中的性能、可靠性与可维护性等方面的认识，也进一步塑造了对“可落地系统研究”的理解。期间，本人曾指导并协作过多位系统与数据工程师，相关经验持续影响着目前的研究方向与问题选择。

代表论文

标识：AI 系统与基础设施数据系统与分析智慧医疗/垂域AI应用企业合作

会议

C29J Yuan, et al.. Query as Anchor: Scenario-Adaptive User Representation via Large Language Model. KDD 2026 产学合作

C28C He, et al.. FOUNDv2: Learning Unified User Quantized Tokenizers for User Representation. KDD 2026 Oral 产学合作

C27C Liu, et al.. DIYHealth Suite: Dataset, Model, and Benchmark for Health Management at Home. ICML 2026

C26S Xiao, J Fu, Z Xie*, L Shou. TokenTiming: A Dynamic Alignment Method for Universal Speculative Decoding Model Pairs. ACL 2026 Main Oral & Awards Nomination

C25F Lin, C You, Z Xie, Z Luo, M Zhang. SaCal: An Efficient Saliency-Guided Causal Framework for Interpretable Healthcare Analytics. ICDE 2026 (To Appear)

C24J Song, Y Liu, G Hu, Z Xie, M Yang, BC Ooi, K Zhou. FAVOR: Efficient Filter-Agnostic Vector ANNS Based on Selectivity-Aware Exclusion Distances. SIGMOD 2026

C23T Lin, et al.. OmniCT: Towards a Unified Slice-Volume LVLM for Comprehensive CT Analysis. ICLR 2026

C22C Lv, H Li, D Yang, Z Xie, L Chen, CS Jensen. DeXOR: Enabling xor in Decimal Space for Streaming Lossless Compression of Floating-point Data. VLDB 2026

C21Y Peng, D Yang, Z Xie, J Sun, L Shou, K Chen, G Chen. SVFusion: A CPU-GPU Co-Processing Architecture for Large-Scale Real-Time Vector Search. VLDB 2026 产学合作

C20Y Wu, et al.. SafeLoad: Efficient Admission Control Framework for Identifying Memory-Overloading Queries in Cloud Data Warehouses. VLDB 2026 产学合作

C19S Wu, et al.. MorphingDB: A Task-Centric AI-Native DBMS for Model Management and Inference. SIGMOD 2026

期刊

J5G Chen, et al.. Generative AI for Healthcare: Fundamentals, Challenges, and Perspectives. SCIENCE CHINA Information Sciences

J4X Chen, Z Xie*, H Li, K Chen, L Shou, D Jiang, G Chen. PIMSHARE: Scheduling for Multi-DNN Inference on Processing-in-memory Accelerated Edge Server. IEEE TCAD 2026

会议

C18H Lin, S Wan, Z Xie*, K Chen*, M Zhang, L Shou, G Chen. A Comprehensive Study of Shapley Value in Data Analytics. VLDB 2025

C17G Hu, S Cai, TTA Dinh, Z Xie*, C Yue, G Chen, BC Ooi. HAKES: Scalable Vector Database for Embedding Search Service. VLDB 2025

C16Z Ji, X Wang, Z Luo, Z Xie, M Zhang. Optimized Batch Prompting for Cost-effective LLMs. VLDB 2025

C15Y Zhou, Z Li, J Zhang, J Wang, Y Wang, Z Xie*, K Chen, L Shou*. FloE: On-the-Fly MoE Inference on Memory-constrained GPU. ICML 2025

C14Y Peng, Z Xie*, K Chen*, G Chen, L Shou. Towards Automatic and Efficient Prediction Query Processing in Analytical Database. ICDE 2025

期刊

J3P Lu, Z Xie*, D Jiang, K Chen, L Shou. Cohort query processing without misleading aging effects. VLDB Journal

J2J Zhang, J Wang, H Li, Z Xie, K Chen, L Shou. CHASe: Client Heterogeneity-Aware Data Selection for Effective Federated Active Learning. TKDE 2025

会议

C13Z Ji, Z Xie, Y Wu, M Zhang. LBSC: A Cost-Aware Caching Framework for Cloud Databases. ICDE 2024 Best Runner-Up Paper

会议

C12C Yue, TTA Dinh, Z Xie, M Zhang, G Chen, BC Ooi, X Xiao. GlassDB: An efficient verifiable ledger database system through transparency. VLDB 2023

C11Y Ma, Z Xie, J Wang, K Chen, L Shou. Continual Federated Learning Based on Knowledge Distillation. IJCAI 2022

C10J Zhang, S Wu, J Zhao, Z Xie, F Li, Y Gao, G Chen. A sampling-based learning framework for big databases. WWW 2022 产学合作

C9M Zhang, Z Xie, C Yue, Z Zhong. Spitz: A verifiable database system. VLDB 2020

C8C Yue, Z Xie, M Zhang, G Chen, BC Ooi, S Wang, X Xiao. Analysis of indexing structures for immutable data. ACM SIGMOD 2020

C7Z Xie, H Ying, C Yue, M Zhang, G Chen, BC Ooi. Cool, a COhort OnLine analytical processing system. ICDE 2020

C6Z Xie, Q Cai, F He, GY Ooi, W Huang, BC Ooi. Cohort analysis with ease. ACM SIGMOD 2018 Demo.

C5Z Xie, Q Cai, G Chen, R Mao, M Zhang. A comprehensive performance evaluation of modern in-memory indices. ICDE 2018

C4Q Cai, Z Xie, M Zhang, G Chen, HV Jagadish, BC Ooi. Effective temporal dependence discovery in time series data. VLDB 2018

C3S Wang, TTA Dinh, Q Lin, Z Xie, M Zhang, Q Cai, G Chen, W Fu, BC Ooi, P Ruan. Forkbase: An efficient storage engine for blockchain and forkable applications. VLDB 2018

C2Z Xie, Q Cai, HV Jagadish, BC Ooi, WF Wong. Parallelizing skip lists for in-memory multi-core database systems. ICDE 2017

C1BC Ooi, et al.. SINGA: A distributed deep learning platform. ACM MM 2015

期刊

J1Q Cai, C Cui, Y Xiong, W Wang, Z Xie, M Zhang. A survey on deep reinforcement learning for data processing and analytics. TKDE 2022

荣誉奖项

• 2026 年 4 月 ACL Awards Nomination
• 2025 年 9 月 CCF 科学技术奖自然科学奖二等奖
• 2024 年 6 月 SIGMOD Systems Award
• 2024 年 4 月 ICDE Best Runner-Up Paper
• 2024 年 8 月 VLDB Distinguished Reviewer

教育经历

谨以此表达对恩师 Ooi Beng Chin 教授的深切怀念与敬意。他是一位杰出的学者、数据系统领域的重要引领者，也是值得敬重的导师与朋友。他的学术精神、治学态度与为人风范，将始终激励我们前行。

• 2014.08 - 2020.01，National University of Singapore，博士，导师为 Beng Chin OOI 教授。
• 2010.09 - 2014.06，上海交通大学，学士，导师为 姚斌 教授。

学术活动

• VLDB Review Board/PC Member: 2022、2023、2024、2026
• ICDE PC Member: 2023、2027
• EDBT PC Member: 2026
• CIKM PC Member: 2025、2026

学生清单

我正在招收具有较强自驱力的博士生、硕士生以及本科科研实习生。如有兴趣，欢迎通过邮件发送你的简历与我联系。