Yu Gu

谷峪

Professor, Ph.D. Supervisor

College of Computer Science and Engineering,

Northeastern University, Shenyang, China

Email: guyu@mail.neu.edu.cn
Office: Room B215-1-2, Information Building, Northeastern University, China
Address: No.195 Chuangxin Road, Hunnan District, Shenyang, China, 110169

RESEARCH INTERESTS

• Big Data Analysis and Distributed Computing
• Graph Data Management and Mining
• Spatial Data Management
• Database System
• Graph Neural Network

TEACHING

• Object-oriented Programming (C++)
• Distributed Systems and Applications
• Big Data Management and Analysis

EDUCATION and EXPERIENCE

• Mar. 2007 - Jan. 2010. Ph.D., College of Information Science and Engineering, Northeastern University, China.
• Sep. 2004 - Mar. 2007. M.S., College of Information Science and Engineering, Northeastern University, China.
• Sep. 2000 - Mar. 2004. B.S., College of Information Science and Engineering, Northeastern University, China.
• Aug. 2008 - Jan. 2009. Research Intern, School of Computing, National University of Singapore.

RESEARCH FUNDINGS

• National Natural Science Foundation of China (NSFC). Distributed Iterative Processing Techniques for Complex Hypergraph Data Analysis. PI. 2019.1-2019.12.
• Liao Ning Revitalization Talents Program. Intelligent Distributed Data Processing Techniques for Big Data Applications. PI. 2019.1-2021.12.
• National Natural Science Foundation of China (NSFC). Key Techniques of Adaptive Data Management over Very Large Dynamic Graphs for High-frequency and Multi-state Iterative Computation. PI. 2015.1-2018.12.
• National Natural Science Foundation of China (NSFC). Research on Data Management Techniques for Location-based Service in IoT space. PI. 2011.1-2013.12.
• Fundamental Research Funds for the Central Universities. Distributed Big Graph Data Management and Computing. PI. 2018.1-2019.12.
• Fundamental Research Funds for the Central Universities. Research on Correlation-sensitive Uncertain Data Management Techniques. PI. 2014.1-2015.12.
• Fundamental Research Funds for the Central Universities. Research on Large-scale Disk-resident Graph Data Processing Techniques on Cloud. PI. 2012.1-2013.12.
• National Key R&D Program of China. Distributed Data Storage and Management for Heterogeneous Architecture. Primary Member. 2018.5-2021.4.
• National Basic Research Program of China (973 Program) . Theory and Key Techniques on Extracting and Integrating Large Scale Multiple Modeling Data from Multi-sources with High Quality. Primary Member. 2012.1-2016.8.
• National Natural Science Foundation of China (NSFC). Distributed Data Processing Techniques for Large-Scale Graph Neural Networks. PI. 2021.1-2024.12.
• National Natural Science Foundation of China (NSFC). Key techniques of the cross-domain and multi-center lake-warehouse architecture. Primary member. 2024.1-2027.12.
• National Key R&D Program of China. Intelligent and Heterogeneous Computation for Hybrid Workloads. Primary member. 2023.12-2026.11.

SELECTED PUBLICATIONS (CCF A/CCF B)

• Pengyi Zhang, Yuchen Yuan, Jie Song, Yu Gu , Qiang Qu, Yongjie Bai: Introducing on-chain graph data to consortium blockchain for commercial transactions. Frontiers of Computer Science (FCS). 18(2): 182608, 2024.
• Hao Yuan, Yajiong Liu, Yanfeng Zhang, Xin Ai, Qiange Wang, Chaoyi Chen, Yu Gu , Ge Yu: Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective. Proceedings of the VLDB Endowment (PVLDB). 17(6): 1241-1254, 2024. (VLDB 2024)
• Xin Ai, Qiange Wang, Chunyu Cao, Yanfeng Zhang, Chaoyi Chen, Hao Yuan, Yu Gu , Ge Yu: NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments. Proceedings of the VLDB Endowment (PVLDB). 17(8): 1995-2008, 2024. (VLDB 2024)
• Zhen Song, Yu Gu* , Qing Sun, Tianyi Li, Yanfeng Zhang, Yushuai Li, Christian S. Jensen, Ge Yu: DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training. Proceedings of the VLDB Endowment (PVLDB). 17(11):3388-3401, 2024. (VLDB 2024)
• Yumeng Song, Yu Gu* , Tianyi Li, Jianzhong Qi, Zhenghao Liu, Christian S. Jensen, Ge Yu: CHGNN: A Semi-Supervised Contrastive Hypergraph Learning Network. IEEE Transactions on Knowledge and Data Engineering (TKDE). 36(9): 4515-4530, 2024.
• Tianshuo Zhou, Sen Mei, Xinze Li, Zhenghao Liu, Chenyan Xiong, Zhiyuan Liu, Yu Gu , Ge Yu: MARVEL: Unlocking the Multi-Modal Capability of Dense Retrieval via Visual Module Plugin. ACL (1) 2024, 14608-14624.
• Qi Dai, Yumeng Song, Yu Gu* , Fangfang Li, Xiaohua Li: Diffusion Model-Enhanced Contrastive Learning for Graph Representation. DASFAA (6) 2024, 332-341.
• Jianpeng Wei, Yu Gu* , Tianyi Li, Jianzhong Qi, Chuanwen Li, Yanfeng Zhang, Christian S. Jensen, Ge Yu: LTPG: Large-Batch Transaction Processing on GPUs with Deterministic Concurrency Control. ICDE 2024, 3865-3877.
• Na Guo, Yaqi Wang, Wenli Sun, Yu Gu* , Jianzhong Qi, Zhenghao Liu, Xiufeng Xia, Ge Yu: Chameleon: Towards Update-Efficient Learned Indexing for Locally Skewed Data. ICDE 2024, 4316-4328.
• Yishu Wang, Jinlong Chu, Ye Yuan, Yu Gu , Hangxu Ji, Hao Zhang: Label Constrained Reachability Queries on Time Dependent Graphs. ICDE 2024, 3244-3256.
• Zhenghao Liu, Zulong Chen, Moufeng Zhang, Shaoyang Duan, Hong Wen, Liangyue Li, Nan Li, Yu Gu , Ge Yu: Modeling User Viewing Flow using Large Language Models for Article Recommendation. WWW 2024, 83-92.
• Zhigang Wang, Ning Wang, Jie Nie, Zhiqiang Wei, Yu Gu , Ge Yu: A lock-free approach to parallelizing personalized PageRank computations on GPU. Frontiers of Computer Science (FCS). 17(1): 171602, 2023.
• Jie Song, Pengyi Zhang, Qiang Qu, Yongjie Bai, Yu Gu , Ge Yu: Why blockchain needs graph: A survey on studies, scenarios, and solutions. Journal of Parallel and Distributed Computing (JPDC). 180: 104730, 2023.
• Zhen Song, Yu Gu* , Tianyi Li, Qing Sun, Yanfeng Zhang, Christian S. Jensen, Ge Yu: ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling. Proceedings of the ACM on Management of Data (SIGMOD). 1(4): 229:1-229:26, 2023. (SIGMOD 2024)
• Chaoyi Chen, Dechao Gao, Yanfeng Zhang, Qiange Wang, Zhenbo Fu, Xuecang Zhang, Junhua Zhu, Yu Gu , Ge Yu: NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams. Proceedings of the VLDB Endowment (PVLDB). 17(3): 455-468, 2023.
• Yuhang Su, Yu Gu* , Zhigang Wang, Ying Zhang, Jianbin Qin, Ge Yu: Efficient Subhypergraph Matching Based on Hyperedge Features. IEEE Transactions on Knowledge and Data Engineering (TKDE). 35(6): 5808-5822, 2023.
• Zhigang Wang, Yilei Tu, Ning Wang, Lixin Gao, Jie Nie, Zhiqiang Wei, Yu Gu , Ge Yu: FSP: Towards Flexible Synchronous Parallel Frameworks for Distributed Machine Learning. IEEE Transactions on Parallel and Distributed Systems (TPDS). 34(2): 687-703, 2023.
• Xinze Li, Zhenghao Liu, Chenyan Xiong, Shi Yu, Yu Gu , Zhiyuan Liu, Ge Yu: Structure-Aware Language Model Pretraining Improves Dense Retrieval on Structured Data. ACL(Findings) 2023, 11560-11574.
• Zhenghao Liu, Sen Mei, Chenyan Xiong, Xiaohua Li, Shi Yu, Zhiyuan Liu, Yu Gu , Ge Yu: Text Matching Improves Sequential Recommendation by Reducing Popularity Biases. CIKM 2023, 1534-1544.
• Jingbo Wang, Yumeng Song, Yu Gu* , Xiaohua Li, Fangfang Li: CLNIE: A Contrastive Learning Based Node Importance Evaluation Method for Knowledge Graphs with Few Labels. DASFAA (2) 2023, 689-705.
• Ning Wang, Yaohua Wang, Zhigang Wang, Jie Nie, Zhiqiang Wei, Peng Tang, Yu Gu , Ge Yu: PrivNUD: Effective Range Query Processing under Local Differential Privacy. ICDE 2023, 2660-2672.
• Yang Song, Yu Gu* , Rui Zhang, Ge Yu: BrePartition: Optimized High-Dimensional kNN Search with Bregman Distances (Extended Abstract). ICDE 2023, 3883-3884.
• Jia Xu, Wanjie Tao, Zulong Chen, Jin Huang, Huihui Liu, Hong Wen, Shenghua Ni, Qun Dai, Yu Gu: PlanRanker: Towards Personalized Ranking of Train Transfer Plans. KDD 2023, 5315-5326.
• Zhen Song, Yu Gu* , Zhigang Wang, Ge Yu: DRPS: efficient disk-resident parameter servers for distributed machine learning. Frontiers of Computer Science (FCS). 16(4): 164321, 2022.
• Ning Wang, Wei Zheng, Zhigang Wang, Zhiqiang Wei, Yu Gu , Peng Tang, Ge Yu: Collecting and analyzing key-value data under shuffled differential privacy. Frontiers of Computer Science (FCS). 17(2): 172606, 2022.
• Yang Song, Yu Gu* , Rui Zhang, Ge Yu: BrePartition: Optimized High-Dimensional kNN Search With Bregman Distances. IEEE Transactions on Knowledge and Data Engineering (TKDE). 34(3): 1053-1065, 2022.
• Yu Gu , Kaiqiang Yu, Zhen Song, Jianzhong Qi, Zhigang Wang, Ge Yu, Rui Zhang: Distributed Hypergraph Processing Using Intersection Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE). 34(7): 3182-3195, 2022.
• Chuanwen Li, Yu Gu , Jianzhong Qi, Ge Yu: Parallel Skyline Processing Using Space Pruning on GPU. CIKM 2022, 1074-1083.
• Yang Wang, Yu Gu , Chuanwen Li: Parallel Pivoted Subgraph Filtering with Partial Coding Trees on GPU. DASFFA (1) 2022, 325-332.
• Yumeng Song, Yu Gu , Xiaohua Li, Chuanwen Li, Ge Yu: CSGNN: Improving Graph Neural Networks with Contrastive Semi-supervised Learning. DASFFA (1) 2022, 731-738.
• Di Wei, Yu Gu , Yumeng Song, Zhen Song, Fangfang Li, Ge Yu: IncreGNN: Incremental Graph Neural Network Learning by Considering Node and Parameter Importance. DASFFA (1) 2022, 739-746.
• Zhenghao Liu, Han Zhang, Chenyan Xiong, Zhiyuan Liu, Yu Gu , Xiaohua Li: Dimension Reduction for Efficient Dense Retrieval via Conditional Autoencoder. EMNLP 2022, 5692-5698.
• Zhen Song, Yu Gu , Jianzhong Qi, Zhigang Wang, Ge Yu: EC-Graph: A Distributed Graph Neural Network System with Error-Compensated Compression. ICDE 2022, 648-660.
• Yu Gu , Kaiqiang Yu, Zhen Song, Jianzhong Qi, Zhigang Wang, Ge Yu, Rui Zhang: Distributed Hypergraph Processing Using Intersection Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE). 34(7): 3182-3195, 2022.
• Yang Song, Yu Gu , Rui Zhang, Ge Yu; BrePartition: Optimized High-Dimensional kNN Search with Bregman Distances. IEEE Transactions on Knowledge and Data Engineering (TKDE). 34(3): 1053-1065, 2022.
• Yang Song, Yu Gu* , Rui Zhang, Ge Yu: ProMIPS: Efficient High-Dimensional c-Approximate Maximum Inner Product Search with a Lightweight Index. ICDE 2021, 1619-1630
• Zhigang Wang, Yu Gu* , Yubin Bao, Ge Yu, Jeffrey Xu Yu, Zhiqiang Wei. HGraph: I/O-efficient Distributed and Iterative Graph Computing by Hybrid Pushing/Pulling. IEEE Transactions on Knowledge and Data Engineering (TKDE). 33(5): 1973-1987, 2021.
• Qian Ma, Wang-Chien Lee, Tao-Yang Fu, Yu Gu , Ge Yu: MIDIA: exploring denoising autoencoders for missing data imputation. Data Min. Knowl. Discov.. 34(6): 1859-1897, 2020.
• Qian Ma, Yu Gu* , Wang-Chien Lee, Ge Yu, Hongbo Liu, Xindong Wu: REMIAN: Real-Time and Error-Tolerant Missing Value Imputation. ACM Trans. Knowl. Discov. Data.(TKDD). 14(6): 77:1-77:38, 2020.
• Zhenzhen Shao, Na Guo, Yu Gu* , Zhigang Wang, Fangfang Li, Ge Yu: Efficient Closeness Centrality Computation for Dynamic Graphs. DASFAA (2) 534-550, 2020.
• Hongfei Xu, Yu Gu* , Yu Sun, Jianzhong Qi, Ge Yu, Rui Zhang: Efficient Processing of Moving Collective Spatial Keyword Queries. VLDB Journal. 29(4): 841-865, 2020.
• Chuanwen Li, Yu Gu , Jianzhong Qi, Rui Zhang, Ge Yu: Moving kNN Query Processing in Metric Space based on Influential Sets. Information Systems. 2019, 83:126-144.
• Hongfei Xu, Yu Gu , Jianzhong Qi, Jiayuan He, Ge Yu: Diversifying Top-k Routes with Spatial Constraints. Journal of Computer Science and Technology. 34(4): 818-838, 2019.
• Qian Ma, Yu Gu , Wang-Chien Lee, Ge Yu: Order-Sensitive Imputation for Clustered Missing Values. ICDE 2019, 2147-2148. (TKDE poster)
• Changfa Wu, Yu Gu* , Ge Yu: DPSCAN: Structural Graph Clustering Based on Density Peaks. DASFAA (2) 2019, 626-641.
• Ying Yang, Yu Gu* , Chuanwen Li, Changyi Wan, Ge Yu: GPU-Accelerated Dynamic Graph Coloring. DASFAA(3) 2019, 296-299.
• Qian Ma, Yu Gu* , Wang-Chien Lee, Ge Yu: Order-Sensitive Imputation for Clustered Missing Values. IEEE Transactions on Knowledge and Data Engineering (TKDE). 31(1):166-180, 2019.
• Yu Gu , Yandan Guo, Yang Song, Xiangmin Zhou, Ge Yu: Approximate Order-Sensitive k-NN Queries over Correlated High-Dimensional Data. IEEE Transactions on Knowledge and Data Engineering (TKDE). 30(11):2037-2050, 2018.
• Zhigang Wang, Lixin Gao, Yu Gu , Yubin Bao, Ge Yu: A Fault-Tolerant Framework for Asynchronous Iterative Computations in Cloud Environments. IEEE Transactions on Parallel and Distributed Systems (TPDS). 29(8):1678-1692, 2018.
• Chuanwen Li, Yu Gu* , Jianzhong Qi, Jiayuan He, Qingxu Deng: A GPU Accelerated Update Efficient Index for kNN Queries in Road Networks. ICDE 2018, 881-892.
• Ning Wang, Xiaokui Xiao, Yin Yang, Zhenjie Zhang, Yu Gu , Ge Yu: PrivSuper: a Superset-First Approach to Frequent Itemset Mining under Differential Privacy. ICDE 2017, 809-820.
• Yu Gu , Guanli Liu, Jianzhong Qi, Hongfei Xu, Ge Yu, Rui Zhang: The Moving k Diversified Nearest Neighbor Query. ICDE 2017, 31-32. (TKDE poster)
• Tianyi Li, Yu Gu*, Xiangmin Zhou, Qian Ma, Ge Yu:  An Effective and Efficient Truth Discovery Framework over Data Streams. EDBT 2017, 180-191.
• Zhigang Wang, Lixin Gao, Yu Gu , Yubin Bao, Ge Yu: FSP: Towards Flexible Synchronous Parallel Framework for Expectation-Maximization based Algorithms on Cloud. ACM SOCC 2017, 1-14.
• Zhigang Wang, Yu Gu , Yubin Bao, Ge Yu, Lixin Gao: An I/O-efficient and adaptive fault-tolerant framework for distributed graph computations. Distributed and Parallel Databases. 35(2): 177-196, 2017.
• Ning Wang, Yu Gu , Jia Xu, Fangfang Li, Ge Yu: Differentially Private Event Histogram Publication on Sequences over Graphs. Journal of computer science and technology. 32(5): 1008-1024, 2017.
• Zhigang Wang, Yu Gu* , Yubin Bao, Ge Yu, Jeffrey Xu Yu: Hybrid Pulling/Pushing for I/O-Efficient Distributed and Iterative Graph Computing. Proceedings of the ACM on Management of Data (SIGMOD). 2016, 479-494.
• Yu Gu , Guanli Liu, Jianzhong Qi, Hongfei Xu, Ge Yu, Rui Zhang: The Moving k Diversified Nearest Neighbor Query. IEEE Transactions on Knowledge and Data Engineering (TKDE). 28(10): 2778-2792, 2016.
• Chuanwen Li, Yu Gu* , Jianzhong Qi, Ge Yu, Rui Zhang, Qingxu Deng: INSQ: An Influential Neighbor Set Based Moving kNN Query Processing System. ICDE 2016, 1338-1341. (demo)
• Jia Xu, Bin Lei, Yu Gu , Marianne Winslett , Ge Yu, Zhenjie Zhang: Efficient Similarity Join Based on Earth Mover’s Distance Using MapReduce. ICDE 2016, 1456-1457. (TKDE poster)
• Miao Li, Lisi Chen, Gao Cong, Yu Gu* , Ge Yu: Efficient processing of location-aware group preference queries. CIKM 2016, 559-568.
• Zhigang Wang, Lixin Gao, Yu Gu , Yubin Bao, Ge Yu: A Fault-Tolerant Framework for Asynchronous Iterative Computations in Cloud Environments. ACM SOCC 2016, 71-83.
• Yu Gu , Chunpeng Gao, Lulu Wang, Ge Yu: Subgraph Similarity Maximal All-Matching over a Large Uncertain Graph. World Wide Web. 19(5):755-782,2016.
• Yu Gu , Hui Zhang, Zhigang Wang, Ge Yu: Efficient Moving k Nearest Neighbor Queries over Line Segment Objects . World Wide Web 19(4):653-677, 2016.
• Jia Xu, Bin Lei, Yu Gu , Marianne Winslett, Ge Yu, Zhenjie Zhang: Efficient Similarity Join Based on Earth Mover’s Distance Using MapReduce . IEEE Transactions on Knowledge and Data Engineering (TKDE). 27(8): 2148-2162, 2015
• Miao Li, Yu Gu , Ge Yu: Effective and Efficient Predictive Density Queries for Indoor Moving Objects. .DASFAA 2015, 244-259.
• Chuanwen Li, Yu Gu* , Jianzhong Qi, Rui Zhang, Ge Yu: A Safe Region based Approach to Moving KNN Queries in Obstructed Space. Knowledge and Information Systems (KAIS). 45(2): 417-451, 2015.
• Chuanwen Li, Yu Gu , Jianzhong Qi, Ge Yu, Rui Zhang, Wang Yi: Processing Moving kNN Queries Using Influential Neighbor Sets. Proceedings of the VLDB Endowment (PVLDB). 8(2): 113-124, 2014.
• Yu Gu , Chunpeng Gao, Gao Cong, Ge Yu: Effective and Efficient Clustering Methods for Correlated Probabilistic Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE). 26(5): 1117-1130, 2014.
• Yanqiu Wang, Rui Zhang, Chuanfei Xu, Jianzhong Qi, Yu Gu , Ge Yu: Continuous visible k nearest neighbor query on moving objects. Information Systems. 44: 1-21,2014.
• Minghan Chen, Yu Gu , Yubin Bao, Ge Yu: Label and Distance-Constraint Reachability Queries in Uncertain Graphs. .DASFAA 2014, Part 1: 188-202.
• Chuanfei Xu, Yu Gu , Lei Chen, Jianzhong Qiao, Ge Yu: Interval Reverse Nearest Neighbor Queries on Uncertain Data with Markov Correlations. ICDE 2013, 170-181.
• Zhigang Wang, Yu Gu, Roger Zimmermann, Ge Yu: Shortest Path Computation over Disk-resident Large Graphs based on Extended Bulk Synchronous Parallel Methods. DASFAA 2013, LNCS 7826, 1-15, 2013.
• Wenan Wang, Yu Gu , Zhigang Wang, Ge Yu. Parallel Triangle Counting over Large Graphs: DASFAA 2013, LNCS 7826, 301-308.
• Jia Xu, Qiushi Bai, Yu Gu , Anthony K.H. Tung, Guoren Wang, Ge Yu, Zhenjie Zhang: EUDEMON: A System for Online Video Frame Copy Detection by Earth Mover's Distance. ICDE 2012, 1233-1236. (demo)
• Chuanwen Li, Yu Gu , Ge Yu, Fangfang Li: wNeighbors: A Method for Finding k Nearest Neighbors in Weighted Regions. DASFAA 2011, LNCS 6588:134-148.
• Mo Chen, Ge Yu, Yu Gu , Zixi Jia, Yanqiu Wang: An Efficient Method for Cleaning Dirty-Events over Uncertain Data in WSNs. Journal of computer science and technology. 26(6): 942-953, 2011.
• Chuanwen Li, Yu Gu , Ge Yu, Bonghee Hong: Aggressive Complex Event Processing with Confidence over Out-of-Order Streams. Journal of computer science and technology. 26(4): 685-696, 2011.
• Yu Gu , Ge Yu, Yueguo Chen, Beng Chin Ooi: Efficient RFID Data Imputation by Analyzing the Correlations of Monitored Objects. DASFAA 2009, LNCS 5463:186-299.(Best Student Paper Award)
• Yu Gu , Ge Yu, Na Guo, Yueguo Chen. Probabilistic Moving Range Query over RFID Data Streams: CIKM 2009, 1413-1416.
• Yueguo Chen, Su Chen, Yu Gu , Mei Hui, Feng Li, Chen Liu, Liangxu Liu, Beng Chin Ooi, Xiaoyan Yang, Dongxiang Zhang, Yuan Zhou: Marcopolo: a community system for sharing and integrating travel information on maps. EDBT 2009, 1148-1151. (demo)
• Tiancheng Zhang, Dejun Yue, Yu Gu , Ge Yu. Boolean Representation Based Data-adaptive Correlation Analysis over Time Series Streams: CIKM 2007, 203-212.

PROFESSIONAL SERVICES

Program Committee Member

• CIKM 2021, APWeb-WAIM 2021
• SIGIR 2020, CIKM 2020, DASFAA 2020, APWeb-WAIM 2020
• DASFAA 2019, Bigcom 2019, NDBC 2019
• CIKM 2018, APWeb-WAIM 2018, NDBC 2018
• CIKM 2017, APWeb-WAIM 2017,ADC 2017, Bigcom 2017,NDBC 2017
• APWeb 2016, WAIM 2016 (demo track), ADC 2016,
• APWeb 2015, ADC 2015

Reviewer for Journal

• ACM Trans. Knowl. Discov. Data
• VLDB Journal
• IEEE Transactions on Data and Knowledge Engineering
• World Wide Web
• Frontier of Computer Science
• Future Generation Computer System

AWARDS and HONORS

• APWeb-WAIM 2020 best paper runner-up award, 2020.
• Youth Talents of Liao Ning Revitalization Talents Program, 2018.
• NDBC 2017 Sashixuan Excellent Student Paper Award (Haixia Wang), 2017.
• NDBC 2015 Sashixuan Excellent Student Paper Award (Honglei Liu), 2015.
• NDBC 2014 Best Paper Award, 2014.
• NDBC 2014 Sashixuan Excellent Student Paper Award (Zhigang Wang), 2014.
• ADC 2012 Best Paper Award, 2012.
• NDBC 2011 Sashixuan Excellent Student Paper Award (Xiaonan Yu), 2011.
• NDBC 2010 Sashixuan Excellent Student Paper Award (Chuanwen Li), 2010.
• DASFAA 2009 Best Student Paper Award, 2009
• APWeb/WAIM 2007 Best Student Paper Runner-up Award, 2007