A predictive dynamic load balancing algorithm with service differentiation. - Jiawei Jiang 001; Haojiang Deng; Xue Liu (ICCT, 2013)

TeslaML: Steering Machine Learning Automatically in Tencent. - Jiawei Jiang 001; Ming Huang; Jie Jiang 015; Bin Cui 001 (APWeb/WAIM (2), 2017)

StroMAX: Partitioning-Based Scheduler for Real-Time Stream Processing System. - Jiawei Jiang 001; Zhipeng Zhang; Bin Cui 001; Yunhai Tong; Ning Xu (DASFAA (2), 2017)

TencentBoost: A Gradient Boosting Tree System with Parameter Server. - Jie Jiang 015; Jiawei Jiang 001; Bin Cui 001; Ce Zhang 001 (ICDE, 2017)

Heterogeneity-aware Distributed Parameter Servers. - Jiawei Jiang 001; Bin Cui 001; Ce Zhang 001; Lele Yu (SIGMOD Conference, 2017)

GVoS: A General System for Near-Duplicate Video-Related Applications on Storm. - Jiawei Jiang 001; Yunhai Tong; Hua Lu 001; Bin Cui 001; Kai Lei; Lele Yu (ACM Trans. Inf. Syst., 2017)

DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions. - Jiawei Jiang 001; Bin Cui 001; Ce Zhang 001; Fangcheng Fu (SIGMOD Conference, 2018)

SketchML: Accelerating Distributed Machine Learning with Data Sketches. - Jiawei Jiang 001; Fangcheng Fu; Tong Yang 003; Bin Cui 001 (SIGMOD Conference, 2018)

FeatureBand: A Feature Selection Method by Combining Early Stopping and Genetic Local Search. - Huanran Xue; Jiawei Jiang 001; Yingxia Shao; Bin Cui 001 (APWeb/WAIM (2), 2019)

Sparse Gradient Compression for Distributed SGD. - Haobo Sun; Yingxia Shao; Jiawei Jiang 001; Bin Cui 001; Kai Lei; Yu Xu; Jiang Wang (DASFAA (2), 2019)

MLlib*: Fast Training of GLMs Using Spark MLlib. - Zhipeng Zhang; Jiawei Jiang 001; Wentao Wu 001; Ce Zhang 001; Lele Yu; Bin Cui 001 (ICDE, 2019)

PS2: Parameter Server on Spark. - Zhipeng Zhang; Bin Cui 001; Yingxia Shao; Lele Yu; Jiawei Jiang 001; Xupeng Miao (SIGMOD Conference, 2019)

An Experimental Evaluation of Large Scale GBDT Systems. - Fangcheng Fu; Jiawei Jiang 001; Yingxia Shao; Bin Cui 001 (Proc. VLDB Endow., 2019)

Efficient Automatic CASH via Rising Bandits. - Yang Li 106; Jiawei Jiang 001; Jinyang Gao; Yingxia Shao; Ce Zhang 001; Bin Cui 001 (AAAI, 2020)

PSGraph: How Tencent trains extremely large-scale graphs with Spark? - Jiawei Jiang 001; Pin Xiao; Lele Yu; Xiaosen Li; Jiefeng Cheng; Xupeng Miao; Zhipeng Zhang; Bin Cui 001 (ICDE, 2020)

C olumnSGD: A Column-oriented Framework for Distributed Stochastic Gradient Descent. - Zhipeng Zhang; Wentao Wu 001; Jiawei Jiang 001; Lele Yu; Bin Cui 001; Ce Zhang 001 (ICDE, 2020)

Efficient Diversity-Driven Ensemble for Deep Neural Networks. - Wentao Zhang 001; Jiawei Jiang 001; Yingxia Shao; Bin Cui 001 (ICDE, 2020)

Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript. - Fangcheng Fu; Yuzheng Hu; Yihan He; Jiawei Jiang 001; Yingxia Shao; Ce Zhang 001; Bin Cui 001 (ICML, 2020)

Reliable Data Distillation on Graph Convolutional Network. - Wentao Zhang 001; Xupeng Miao; Yingxia Shao; Jiawei Jiang 001; Lei Chen 002; Olivier Ruas; Bin Cui 001 (SIGMOD Conference, 2020)

Snapshot boosting: a fast ensemble framework for deep neural networks. - Wentao Zhang 001; Jiawei Jiang 001; Yingxia Shao; Bin Cui 001 (Sci. China Inf. Sci., 2020)

SKCompress: compressing sparse and nonuniform gradient in distributed machine learning. - Jiawei Jiang 001; Fangcheng Fu; Tong Yang 003; Yingxia Shao; Bin Cui 001 (VLDB J., 2020)

MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements. - Yang Li 106; Yu Shen 003; Jiawei Jiang 001; Jinyang Gao; Ce Zhang 001; Bin Cui 001 (AAAI, 2021)

Ease.ML: A Lifecycle Management System for Machine Learning. - Leonel Aguilar Melgar; David Dao; Shaoduo Gan; Nezihe Merve Gürel; Nora Hollenstein; Jiawei Jiang 001; Bojan Karlas; Thomas Lemmin; Tian Li 005; Yang Li 106; Susie Xi Rao; Johannes Rausch; et al. (CIDR, 2021)

CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract). - Xupeng Miao; Lingxiao Ma; Zhi Yang 001; Yingxia Shao; Bin Cui 001; Lele Yu; Jiawei Jiang 001 (ICDE, 2021)

OpenBox: A Generalized Black-box Optimization Service. - Yang Li 106; Yu Shen 003; Wentao Zhang 001; Yuanwei Chen; Huaijun Jiang; Mingchao Liu; Jiawei Jiang 001; Jinyang Gao; Wentao Wu 001; Zhi Yang 001; Ce Zhang 001; Bin Cui 001 (KDD, 2021)

VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning. - Fangcheng Fu; Yingxia Shao; Lele Yu; Jiawei Jiang 001; Huanran Xue; Yangyu Tao; Bin Cui 001 (SIGMOD Conference, 2021)

Towards Demystifying Serverless Machine Learning Training. - Jiawei Jiang 001; Shaoduo Gan; Yue Liu; Fanlin Wang; Gustavo Alonso; Ana Klimovic; Ankit Singla; Wentao Wu 001; Ce Zhang 001 (SIGMOD Conference, 2021)

Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce. - Xupeng Miao; Xiaonan Nie; Yingxia Shao; Zhi Yang 001; Jiawei Jiang 001; Lingxiao Ma; Bin Cui 001 (SIGMOD Conference, 2021)

BAGUA: Scaling up Distributed Learning with System Relaxations. - Shaoduo Gan; Xiangru Lian; Rui Wang; Jianbin Chang; Chengjun Liu; Hongmei Shi; Shengzhuo Zhang; Xianghong Li; Tengxu Sun; Jiawei Jiang 001; Binhang Yuan; Sen Yang 004; et al. (Proc. VLDB Endow., 2021)

VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. - Yang Li 106; Yu Shen 003; Wentao Zhang 001; Jiawei Jiang 001; Yaliang Li; Bolin Ding; Jingren Zhou 001; Zhi Yang 001; Wentao Wu 001; Ce Zhang 001; Bin Cui 001 (Proc. VLDB Endow., 2021)

Model averaging in distributed machine learning: a case study with Apache Spark. - Yunyan Guo; Zhipeng Zhang; Jiawei Jiang 001; Wentao Wu 001; Ce Zhang 001; Bin Cui 001; Jianzhong Li (VLDB J., 2021)

Distributed Machine Learning and Gradient Optimization - Jiawei Jiang 001; Bin Cui 001; Ce Zhang 001 (Springer, 2022)

BRIGHT - Graph Neural Networks in Real-time Fraud Detection. - Mingxuan Lu; Zhichao Han 001; Susie Xi Rao; Zitao Zhang; Yang Zhao; Yinan Shan; Ramesh Raghunathan; Ce Zhang 001; Jiawei Jiang 001 (CIKM, 2022)

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract). - Xupeng Miao; Wentao Zhang 001; Yingxia Shao; Bin Cui 001; Lei Chen 002; Ce Zhang 001; Jiawei Jiang 001 (ICDE, 2022)

Analyzing Online Transaction Networks with Network Motifs. - Jiawei Jiang 001; Yusong Hu; Xiaosen Li; Wen Ouyang; Zhitao Wang; Fangcheng Fu; Bin Cui 001 (KDD, 2022)

VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? - Jiawei Jiang 001; Lukas Burkhalter; Fangcheng Fu; Bolin Ding; Bo Du 001; Anwar Hithnawi; Bo Li 026; Ce Zhang 001 (NeurIPS, 2022)

In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. - Lijie Xu; Shuang Qiu; Binhang Yuan; Jiawei Jiang 001; Cédric Renggli; Shaoduo Gan; Kaan Kara; Guoliang Li 001; Ji Liu 002; Wentao Wu 001; Jieping Ye; Ce Zhang 001 (SIGMOD Conference, 2022)

Stochastic Gradient Descent without Full Data Shuffle. - Lijie Xu; Shuang Qiu; Binhang Yuan; Jiawei Jiang 001; Cédric Renggli; Shaoduo Gan; Kaan Kara; Guoliang Li 001; Ji Liu 002; Wentao Wu 001; Jieping Ye; Ce Zhang 001 (CoRR, 2022)

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates. - Fangcheng Fu; Xupeng Miao; Jiawei Jiang 001; Huanran Xue; Bin Cui 001 (CoRR, 2022)

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update. - Fangcheng Fu; Xupeng Miao; Jiawei Jiang 001; Huanran Xue; Bin Cui 001 (Proc. VLDB Endow., 2022)

CuWide: Towards Efficient Flow-Based Training for Sparse Wide Models on GPUs. - Xupeng Miao; Lingxiao Ma; Zhi Yang 001; Yingxia Shao; Bin Cui 001; Lele Yu; Jiawei Jiang 001 (IEEE Trans. Knowl. Data Eng., 2022)

BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks. - Qiang Huang 009; Jiawei Jiang 001; Susie Xi Rao; Ce Zhang 001; Zhichao Han 001; Zitao Zhang; Xin Wang 128; Yongjun He 004; Quanqing Xu; Yang Zhao; Chuang Hu; Shuo Shang; et al. (CoRR, 2023)

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning. - Yuxiang Wang; Xiao Yan 002; Chuang Hu; Fangcheng Fu; Wentao Zhang 001; Hao Wang 013; Shuo Shang; Jiawei Jiang 001 (CoRR, 2023)

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture. - Xupeng Miao; Wentao Zhang 001; Yingxia Shao; Bin Cui 001; Lei Chen 002; Ce Zhang 001; Jiawei Jiang 001 (IEEE Trans. Knowl. Data Eng., 2023)

PIM-Opt: Demystifying Distributed Optimization Algorithms on a Real-World Processing-In-Memory System. - Steve Rhyner; Haocong Luo; Juan Gómez-Luna; Mohammad Sadrosadati; Jiawei Jiang 001; Ataberk Olgun; Harshita Gupta; Ce Zhang 001; Onur Mutlu (PACT, 2024)

Learning Diffusions under Uncertainty. - Hao Huang 001; Qian Yan 001; Keqi Han; Ting Gan; Jiawei Jiang 001; Quanqing Xu; Chuanhui Yang (AAAI, 2024)

TreeCSS: An Efficient Framework for Vertical Federated Learning. - Qinbo Zhang; Xiao Yan 002; Yukai Ding; Quanqing Xu; Chuang Hu; Xiaokai Zhou; Jiawei Jiang 001 (DASFAA (1), 2024)

VFDV-IM: An Efficient and Securely Vertical Federated Data Valuation. - Xiaokai Zhou; Xiao Yan 002; Xinyan Li; Hao Huang 001; Quanqing Xu; Qinbo Zhang; Yen Jerome; Zhaohui Cai; Jiawei Jiang 001 (DASFAA (1), 2024)

Benchtemp: A General Benchmark for Evaluating Temporal Graph Neural Networks. - Qiang Huang 009; Xin Wang 128; Susie Xi Rao; Zhichao Han 001; Zitao Zhang; Yongjun He 004; Quanqing Xu; Yang Zhao; Zhigao Zheng 001; Jiawei Jiang 001 (ICDE, 2024)

HGAMLP: Heterogeneous Graph Attention MLP with De-Redundancy Mechanism. - Yuxuan Liang; Wentao Zhang 001; Zeang Sheng; Ling Yang 006; Jiawei Jiang 001; Yunhai Tong; Bin Cui 001 (ICDE, 2024)

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning. - Yuxiang Wang; Xiao Yan 002; Chuang Hu; Quanqing Xu; Chuanhui Yang; Fangcheng Fu; Wentao Zhang 001; Hao Wang 013; Bo Du 001; Jiawei Jiang 001 (ICDE, 2024)

Self-Supervised Learning for Graph Dataset Condensation. - Yuxiang Wang; Xiao Yan 002; Shiyu Jin; Hao Huang 001; Quanqing Xu; Qingchen Zhang 001; Bo Du 001; Jiawei Jiang 001 (KDD, 2024)

Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters. - Yifei Xia; Fangcheng Fu; Wentao Zhang 001; Jiawei Jiang 001; Bin Cui 001 (NeurIPS, 2024)

Distribution-Aware Data Expansion with Diffusion Models. - Haowei Zhu; Ling Yang 006; Jun-Hai Yong; Hongzhi Yin; Jiawei Jiang 001; Meng Xiao; Wentao Zhang 001; Bin Wang (NeurIPS, 2024)

PICO: Accelerating All k-Core Paradigms on GPU. - Chen Zhao; Ting Yu 004; Zhigao Zheng 001; Song Jin; Jiawei Jiang 001; Bo Du 001; Dacheng Tao (CoRR, 2024)

Analysis of Distributed Optimization Algorithms on a Real Processing-In-Memory System. - Steve Rhyner; Haocong Luo; Juan Gómez-Luna; Mohammad Sadrosadati; Jiawei Jiang 001; Ataberk Olgun; Harshita Gupta; Ce Zhang 001; Onur Mutlu (CoRR, 2024)

Hound: Hunting Supervision Signals for Few and Zero Shot Node Classification on Text-attributed Graph. - Yuxiang Wang; Xiao Yan 002; Shiyu Jin; Quanqing Xu; Chuanhui Yang; Yuanyuan Zhu 001; Chuang Hu; Bo Du 001; Jiawei Jiang 001 (CoRR, 2024)

Retrofitting Temporal Graph Neural Networks with Transformer. - Qiang Huang 009; Xiao Yan 002; Xin Wang 128; Susie Xi Rao; Zhichao Han 001; Fangcheng Fu; Wentao Zhang 001; Jiawei Jiang 001 (CoRR, 2024)

Origin-Destination Demand Prediction: An Urban Radiation and Attraction Perspective. - Xuan Ma; Zepeng Bao; Ming Zhong 002; Yuanyuan Zhu 001; Chenliang Li; Jiawei Jiang 001; Qing Li 001; Tieyun Qian (CoRR, 2024)

A systematic evaluation of machine learning on serverless infrastructure. - Jiawei Jiang 001; Shaoduo Gan; Bo Du 001; Gustavo Alonso; Ana Klimovic; Ankit Singla; Wentao Wu 001; Sheng Wang 007; Ce Zhang 001 (VLDB J., 2024)

How good are machine learning clouds? Benchmarking two snapshots over 5 years. - Jiawei Jiang 001; Yi Wei; Yu Liu 075; Wentao Wu 001; Chuang Hu; Zhigao Zheng 001; Ziyi Zhang; Yingxia Shao; Ce Zhang 001 (VLDB J., 2024)

ProjPert: Projection-Based Perturbation for Label Protection in Split Learning Based Vertical Federated Learning. - Fangcheng Fu; Xuanyu Wang; Jiawei Jiang 001; Huanran Xue; Bin Cui 001 (IEEE Trans. Knowl. Data Eng., 2024)

Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems. - Lijie Xu; Shuang Qiu; Binhang Yuan; Jiawei Jiang 001; Cédric Renggli; Shaoduo Gan; Kaan Kara; Guoliang Li 001; Ji Liu 002; Wentao Wu 001; Jieping Ye; Ce Zhang 001 (VLDB J., 2024)

Tackling Multiplayer Interaction for Federated Generative Adversarial Networks. - Chuang Hu; Tianyu Tu; Yili Gong; Jiawei Jiang 001; Zhigao Zheng 001; Dazhao Cheng (IEEE Trans. Mob. Comput., 2024)

Towards Scalable and Deep Graph Neural Networks via Noise Masking. - Yuxuan Liang; Wentao Zhang 001; Zeang Sheng; Ling Yang 006; Quanqing Xu; Jiawei Jiang 001; Yunhai Tong; Bin Cui 001 (AAAI, 2025)

HaCore: Efficient Coreset Construction with Locality Sensitive Hashing for Vertical Federated Learning. - Qinbo Zhang; Xiao Yan 002; Yukai Ding; Fangcheng Fu; Quanqing Xu; Ziyi Li; Chuang Hu; Jiawei Jiang 001 (AAAI, 2025)

GADACE: Graph Anomaly Detection Combining Attribute Contrast and Structure Reconstruction. - Shihui Wang; Yulan Yang; Zixin Tan; Zhigao Zheng 001; Jiawei Jiang 001; Hao Huang 001; Quanqing Xu; Chuanhui Yang (ICASSP, 2025)

Defending against Attribute Inference Attacks in Post-Training of Recommendation Systems via Unlearning. - Wenhan Wu; Yili Gong; Jiawei Jiang 001; Chuang Hu; Xiaobo Zhou 002; Dazhao Cheng (ICDE, 2025)

Hounding Data Diversity: Towards Participant Selection in Vertical Federated Learning. - Xiaokai Zhou; Xiao Yan 002; Fangcheng Fu; Xinyan Li; Hao Huang 001; Quanqing Xu; Chuanhui Yang; Bo Du 001; Tieyun Qian; Jiawei Jiang 001 (ICDE, 2025)

EDGaE: Efficient Distributed Graph Neural Network Training System at the Edge. - Song Jin; Xiantao Cai; Jiawei Jiang 001 (ICIC (15), 2025)

TESA: A Trajectory and Semantic-aware Dynamic Heterogeneous Graph Neural Network. - Xin Wang 128; Jiawei Jiang 001; Xiao Yan 002; Qiang Huang 009 (WWW, 2025)

Intelligent Welding System for Aluminum Coils by Adaptive Path Planning with Real-world Dataset. - Xiaowei Huang; Huanghuang Liang; Zhili He; Sihan Feng; Jiawei Jiang 001; Kanye Ye Wang; Chuang Hu; Dazhao Cheng (WWW (Companion Volume), 2025)

Aegis: Post-Training Attribute Unlearning in Federated Recommender Systems against Attribute Inference Attacks. - Wenhan Wu; Jiawei Jiang 001; Chuang Hu (WWW, 2025)

Toward Lifelong Unseen Task Processing With a Lightweight Unlabeled Data Schema for AIoT. - Tianyu Tu; Zhili He; Zhigao Zheng 001; Zimu Zheng; Jiawei Jiang 001; Yili Gong; Chuang Hu; Dazhao Cheng (IEEE Internet Things J., 2025)

Data4RACTC. - Xuan Ma; Zepeng Bao; Ming Zhong 002; Yuanyuan Zhu 001; Chenliang Li; Jiawei Jiang 001; Qing Li 001; Tieyun Qian (IEEE DataPort, 2025)

TGraph: A Tensor-centric Graph Processing Framework. - Yongliang Zhang; Yuanyuan Zhu 001; Hao Zhang 098; Congli Gao; Yuyang Wang; Guojing Li; Tianyang Xu; Ming Zhong 002; Jiawei Jiang 001; Tieyun Qian; Chenyi Zhang 002; Jeffrey Xu Yu (Proc. ACM Manag. Data, 2025)

Detecting and Analyzing Motifs in Large-Scale Online Transaction Networks. - Jiawei Jiang 001; Hao Huang 001; Zhigao Zheng 001; Yi Wei; Fangcheng Fu; Xiaosen Li; Bin Cui 001 (IEEE Trans. Knowl. Data Eng., 2025)

Identifying E-Commerce Fraud Through User Behavior Data: Observations and Insights. - Ziyi Zhang; Hang Yin; Susie Xi Rao; Xiao Yan 002; Zhurong Wang; Weiming Liang; Yang Zhao; Yinan Shan; Ruixuan Zhang; Yuhao Lin; Jiawei Jiang 001 (Data Sci. Eng., 2025)

Lock-Free Triangle Counting on GPU. - Zhigao Zheng 001; Guojia Wan; Jiawei Jiang 001; Chuang Hu; Hao Liu; Shahid Mumtaz; Bo Du 001 (IEEE Trans. Computers, 2025)

Exploiting Text Semantics for Few and Zero Shot Node Classification on Text-attributed Graph. - Yuxiang Wang; Xiao Yan 002; Shiyu Jin; Quanqing Xu; Chuang Hu; Yuanyuan Zhu 001; Bo Du 001; Jia Wu; Jiawei Jiang 001 (CoRR, 2025)

MTGRBoost: Boosting Large-scale Generative Recommendation Models in Meituan. - Yuxiang Wang; Xiao Yan 002; Chi Ma; Mincong Huang; Xiaoguang Li; Lei Yu; Chuan Liu; Ruidong Han; He Jiang; Bin Yin; Shangyu Chen; Fei Jiang; et al. (CoRR, 2025)

PriFairFed: A Local Differentially Private Federated Learning Algorithm for Client-Level Fairness. - Chuang Hu; Nanxi Wu; Siping Shi; Xuan Liu; Bing Luo; Kanye Ye Wang; Jiawei Jiang 001; Dazhao Cheng (IEEE Trans. Mob. Comput., 2025)

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG. - Qiming Zeng; Xiao Yan 002; Hao Luo; Yuhao Lin; Yuxiang Wang; Fangcheng Fu; Bo Du 001; Quanqing Xu; Jiawei Jiang 001 (CoRR, 2025)

Acceleration Algorithms in GNNs: A Survey. - Lu Ma; Zeang Sheng; Xunkai Li; Xinyi Gao 001; Zhezheng Hao; Ling Yang 006; Xiaonan Nie; Jiawei Jiang 001; Wentao Zhang 001; Bin Cui 001 (IEEE Trans. Knowl. Data Eng., 2025)

Secure spatial remote sensing image matching. - Yi Wei; Xuan Zhou; Hao Huang 001; Hao Wang 013; Chuang Hu; Jiawei Jiang 001 (GeoInformatica, 2025)

Privacy-protected Retrieval-Augmented Generation for Knowledge Graph Question Answering. - Yunfeng Ning; Mayi Xu; Jintao Wen; Qiankun Pi; Yuanyuan Zhu 001; Ming Zhong 002; Jiawei Jiang 001; Tieyun Qian (CoRR, 2025)