profile

Yuchen Li

Associate Professor

Lee Kong Chian Fellow

School of Computing and Information System
Singapore Management University

Contact Info:

Email: yuchenli AT smu DOT edu.sg
Address: #4041, 80 Stamford Rd, Singapore 178902
Phone: +(65) 68289614

Short Bio

Yuchen is an Associate Professor at the School of Computing and Information System (SCIS) in the Singapore Management University (SMU). Before joining SMU, he was a research fellow at the National University of Singapore (NUS). He received his Ph.D degree in computer science from NUS in 2017. His major research interests are social analytics and high performance graph mining. Besides, he is also acitvely working on fintech with large language models (LLMs).

HOT We are actively looking for talented and highly motivated Ph.D. students to work on large scale graph learning and fintech with LLMs. If you are interested, please find information about the SCIS PhD Program and send an email to me (full scholarship and monthly stipends available at here).

Recent News

  • NEW Our paper accepted at KDD 2024: "How to Avoid Jumping to Conclusions: Measuring the Robustness of Outstanding Facts in Knowledge Graphs".
  • NEW Our paper accepted at TKDE Journal: "A Survey on Concurrent Processing of Graph Analytical Queries: Systems and Algorithms".
  • NEW Our paper accepted at TKDE Journal: "From A Timeline Contact Graph to Close Contact Tracing and Infection Diffusion Intervention".
  • NEW Two papers accepted at SIGMOD 2024 (Santiago): "gSWORD: GPU-accelerated Sampling for Subgraph Counting" and "uBlade: Efficient Batch Processing for Uncertainty Graph Queries".
  • NEW Two papers accepted at ICDE 2024 (Utrecht): "Discovering Personalized Characteristic Communities in Attributed Graphs" and "Enabling Roll-up and Drill-down Operations in News Exploration with Knowledge Graphs for Due Diligence and Risk Management (Industry)".
  • NEW Our paper accepted at TKDE Journal: "Large-scale Graph Label Propagation on GPUs".
  • NEW Our paper accepted at EDBT 2024 (Paestum): "Balancing Utility and Fairness in Submodular Maximization".
  • NEW Our paper accepted at ICDE 2023 (Anaheim): "Exploiting Reuse for GPU Subgraph Enumeration (Extended Abstract)".
  • NEW Our paper accepted at TKDE Journal: "On the Substructure Countability of Graph Neural Networks".
  • NEW Our paper accepted at ICDM 2022 (Orlando): "Efficient Navigation for Constrained Shortest Path with Adaptive Expansion Control (oral)".
  • NEW I received the Lee Kong Chian Fellowship for research excellece.
  • NEW Our paper accepted at ICDE 2022 (Kuala Lumpur): "Local Clustering over Labeled Graphs: An Index-Free Approach".
  • NEW Our paper accepted at TKDE Journal: "Graph Neural Point Process for Temporal Interaction Prediction".
  • NEW Our paper "From Community Search to Community Understanding: A Multimodal Community Query Engine" received the Best Demo Paper Award (Runner Up) at CIKM 2021 (Queensland).
  • NEW I received the Distinguished Reviewer Award at VLDB 2021 (Copenhagen).
  • NEW Our paper accepted at VLDB 2021 (Copenhagen): "ThunderRW: An In-Memory Graph Random Walk Engine".
  • NEW Two papers accepted at KDD 2021 (Singapore): "Context-aware Outstanding Fact Mining from Knowledge Graphs" and "Forecasting Interaction Order on Temporal Graphs".
  • NEW Our paper accepted at TKDE Journal: "On the Robustness of Diffusion in a Network under Node Attacks".
  • NEW We have four papers accepted at SIGMOD 2021 (Xi'an).
  • NEW Our paper accepted at PODS 2021 (Xi'an): "Minimum Coresets for Maxima Representation of Multidimensional Data".
  • NEW Our paper accepted at DASFAA 2021 (Taipei): "DBL: Efficient Reachability Queries on Dynamic Graphs".
  • NEW Our paper accepted at VLDB 2021 (Copenhagen): "Accelerating Exact Constrained Shortest Paths on GPUs".
  • NEW Our paper accepted at TKDE Journal: "Exploiting Reuse for GPU Subgraph Enumeration".
  • NEW Our paper accepted at WWW Journal: "A Survey of Typical Attributed Graph Queries".
  • NEW We have four papers accepted at ICDE 2021 (Chania).
  • NEW Our paper accepted at WSDM 2021 (Online): "DeepIS: Susceptibility Estimation on Social Networks".
  • Our paper accepted at CIKM 2020 (Online): "Efficient Sampling Algorithms for Approximate Temporal Motif Counting".
  • Our paper was recognized by SIGMOD reproducibility: "GPU-based Graph Traversal on Compressed Graphs".
  • Our paper accepted at SIGIR 2020 (Xi'an): "BiANE: Bipartite Attributed Network Embedding".
  • I was recognized as Outstanding Reviewer for PAKDD 2020.
  • Our paper accepted at SIGMOD 2020 (Portland): "GPU-Accelerated Subgraph Enumeration on Partitioned Graphs".
  • Our paper accepted at WWW 2020 (Taipei): "On the Robustness of Cascade Diffusion under Node Attacks (short)".
  • Our research on Concurrent Graph Processing on GPUs will be supported by MoE funding for three years.
  • Our paper accepted at AAAI 2020 (New York): "Social Influence Does Matter: User Action Prediction for In-Feed Advertising".
  • Our paper "Optimizing Impression Counts for Outdoor Advertising" received the Best Research Paper Award (Runner Up) at KDD 2019 (Alaska).
  • Two papers accepted at KDD 2019 (Alaska): "Optimizing Impression Counts for Outdoor Advertising (oral)" and "Semantic and Influence aware k-Representative Queries over Social Streams (oral)".
  • Two papers accepted at VLDB 2019 (Los Angeles): "SHOAL: Large-scale Hierarchical Taxonomy via Graph-based Query Coalition in E-commerce (demo)" and "ITAA: An Intelligent Trajectory-driven Outdoor Advertising Deployment Assistant (demo)".
  • Our paper accepted at SIGMOD 2019 (Amsterdam): "GPU-based Graph Traversal on Compressed Graphs".
  • Our paper accepted at ICDE 2019 (Macau): "Maximizing Multifaceted Network Influence".
  • Our paper accepted at EDBT 2019 (Lisbon): "Semantic and Influence aware k-Representative Queries over Social Streams".
  • Two papers accepted at ICDM 2018: "Heterogeneous Embedding Propagation for Large-scale E-Commerce User Alignment (short)" and "River: A Real-time Influence Monitoring System on Social Meida Stream (demo)".
  • Our paper accepted at KDD 2018 (London): "Trajectory-driven Influential Billboard Placement (oral)". Check out our teaser video at: http://tiny.cc/29ng4y
  • Our paper accepted at TKDE Journal: "Efficient Representative Subset Selection over Sliding Windows".
  • Our paper accepted at TOIS Journal: "Location-aware Influence Maximization over Dynamic Social Streams".
  • I am chairing the IEEE ICDM 2018 data challenging contest, please click here for more details regarding the competition.
  • Our paper accepted at TKDE Journal: "Influence Maximization on Social Graphs: A Survey".
  • Our paper accepted at VLDB Journal: "Augmented Keyword Search on Spatial Entity Databases".
  • Two papers accepted at ICDE 2018 (Paris): "A Sliding-Window Framework for Representative Subset Selection" (short) and "OCTOPUS: An Online Topic-Aware Influence Analysis System for Social Networks" (demo).
  • I joined SMU as an assistant professor, starting from Jan 2018.
  • Two papers accepted at VLDB 2018: "Accelerating Dynamic Graph Analytics on GPUs" and "Parallel Personalized Pagerank on Dynamic Graphs".


    • LLM-powered Competitve Analysis

    Competitive analysis is a strategic process designed to evaluate competition across various entities, such as companies, workers, and products. Central to this analysis is the identification of "Outstanding Facts" (OFs), which are significant insights highlighting areas where entities distinctly outperform their competitors. Traditionally, the discovery of OFs has relied on predefined data schemas and rule-based methods. However, these approaches are hampered by significant limitations, including (i) a restricted scope of competition that can be identified and (ii) persistent explainability issues regarding why such OFs are relevant to end users. Consequently, extensive human expertise and a costly manual evaluation process are required before OFs can be effectively utilized in downstream analysis. To overcome these challenges, this proposal aims to leverage Large Language Models (LLMs) to develop a next-generation system for the automated discovery and evaluation of OFs. By doing so, we intend to transform competitive analysis through more dynamic, accurate, and comprehensive assessments.

    Grant Information

    Next-Gen Competitive Intelligence: Automated Discovery of Outstanding Facts with Large Language Models. (2025-2027),
    MoE AcRF Tier 1, Role: PI.



    Graph

    Large Scale Graph Processing on GPUs.

    Graphs are powerful structures to represent complex dependencies in the data. Large scale graph processing remains a fundamental challenge, due to its compute-intensive as well as data-intensive nature. There are emerging interests in adopting massively parallel GPUs to speedup graph processing. Nevertheless, existing GPU solutions focus on static, homogeneous graphs and simple graph algorithms, e.g., BFS, shortest path, connected components and etc. In this project, we explore using GPUs for more complex processing tasks (e.g., motif discovery and deep learning on graphs), with emphasis on heterogeneous and dynamic graphs.

    Grant Information

    CONQUEROR: Concurrent graph query processing on CPU-GPU heterogeneous architecture (2020-2023),
    MoE AcRF Tier 2, Role: PI.
    MAGE: A GPU-based Engine in Dynamic Sparse Matrix (2017-2020),
    MoE AcRF Tier 2, Role: Collaborator



    Graph

    Fact Checking on Social Media Streams.

    Massive amount of information has been continuously generated on social media streams. Misinformation posted in social media messages leads to undesirable consequences and can be very difficult to correct since people make casual inferences based on available information about a given event or outcome. A computational fact-checking engine is much needed to identify false statements. Existing approaches either uses knowledge graph to semantically fact-check statements but suffers from performance issue, or completely ignores the semantic meaning and solely focus on viral patterns to determine problematic statements. In this project, we are planning to develop an efficient engine on top of the knowledge graph to fact-check the massive social media streams.

    Grant Information

    PPS: A personalized Platform for Summarizing Social Media Stream (2018-2020),
    MoE AcRF Tier 1, Role: PI.



    Graph

    PhD Students

  • Xiao Hanhua (2021-now)
  • Wang Sha (2021-now)
  • Ye Chang (2020-now)

    Research Staffs

  • Niu Yudong (Research Scientist)

    Past PhD Students

  • Zhang Yipeng (Co-supervise with Prof. Bao Zhifeng at RMIT, 2023, First Placement: CSIRO Data61)
  • Xia Wenwen (CSC-joint PhD, 2023, First Placement: Ant Group)

    Past Research Staffs

  • Yao Siyuan (2021-2023, Next Position: PhD Student at National University of Singapore)
  • Baranadura Dinuka Manohara DE ZOYSA (2022-2023, Next Position: PhD Student at University of Melbourne)

    Past Visiting Students

  • Wenyue Ma (PhD student at Arhus University)
  • Zhu Qiwei (Master student at Zhejiang University)
  • Tang Mengqiu (Master student at Zhejiang University)
  • Li Jianxin (Master student at Zhejiang University)
  • Zhang Jing (Master student at Zhejiang University)
  • Liu Yue (Master student at Zhejiang University)
  • Huang Shixun (PhD student at RMIT)
  • Alvis Logins (PhD student at Arhus University)
  • Huang Wentao (Master student at Renmin University)


    • Conference Publications

    Hanhua Xiao, Yuchen Li, Yanhao Wang, Panagiotis Karras, Kyriakos Mouratidis, Natalia-Rozalia Avlona.
    How to Avoid Jumping to Conclusions: Measuring the Robustness of Outstanding Facts in Knowledge Graphs.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.
    Siyuan Yao, Yuchen Li, Shixuan Sun, Jiaxin Jiang, Bingsheng He.
    uBlade: Efficient Batch Processing for Uncertainty Graph Queries.
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2024.
    Chang Ye, Yuchen Li, Shixuan Sun, Wentian Guo.
    gSWORD: GPU-accelerated Sampling for Subgraph Counting.
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2024.
    Yudong Niu, Yuchen Li, Panagiotis Karras, Yanhao Wang, Zhao Li.
    Discovering Personalized Characteristic Communities in Attributed Graphs.
    IEEE International Conference on Data Engineering (ICDE), 2024.
    Sha Wang, Yuchen Li, Hanhua Xiao, Zhifeng Bao, Lambert Deng, Yanfei Dong.
    Enabling Roll-up and Drill-down Operations in News Exploration with Knowledge Graphs for Due Diligence and Risk Management (Industry).
    IEEE International Conference on Data Engineering (ICDE), 2024.
    Yanhao Wang, Yuchen Li, Francesco Bonchi, Ying Wang.
    Balancing Utility and Fairness in Submodular Maximization.
    International Conference on Extending Database Technology (EDBT), 2024.
    Wentiao Guo, Yuchen Li, Kian-Lee Tan.
    Exploiting Reuse for GPU Subgraph Enumeration (Extended Abstract).
    IEEE International Conference on Data Engineering (ICDE), 2023.
    Wenwen Xia, Yuchen Li, Wentian Guo, Shenghong Li.
    Efficient Navigation for Constrained Shortest Path with Adaptive Expansion Control (Oral).
    IEEE International Conference on Data Mining (ICDM), 2022.
    Yudong Niu, Yuchen Li, Ju Fan, Zhifeng Bao.
    Local Clustering over Labeled Graphs: An Index-Free Approach.
    IEEE International Conference on Data Engineering (ICDE), 2022.
    Shixuan Sun, Yuhang Chen, Shengliang Lu, Bingsheng He, Yuchen Li.
    ThunderRW: An In-Memory Graph Random Walk Engine.
    International Conference on Very Large Data Bases (VLDB), 2021.
    Yueji Yang, Yuchen Li, Panagiotis Karras, Anthony Tung.
    Context-aware Outstanding Fact Mining from Knowledge Graphs.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021.
    Wenwen Xia, Yuchen Li, Jianwei Tian, Shenghong Li.
    Forecasting Interaction Order on Temporal Graphs.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021.
    Chang Ye, Yuchen Li, Bingsheng He, Zhao Li, Jianling Sun.
    GPU-Accelerated Graph Label Propagation for Real-Time Fraud Detection.
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2021.
    Yipeng Zhang, Yuchen Li, Zhifeng Bao, Baihua Zheng, H. V. Jagadish.
    Minimizing the Regret of an Influence Provider.
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2021.
    Shengliang Lu, Shixuan Sun, Johns Paul, Yuchen Li, Bingsheng He.
    Cache-Efficient Fork-Processing Patterns on Large Graphs.
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2021.
    Mo Sha, Yuchen Li, Kian-Lee Tan.
    Self-adaptive Graph Traversal on GPUs.
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2021.
    Yanhao Wang, Michael Mathioudakis, Yuchen Li, Kian-Lee Tan.
    Minimum Coresets for Maxima Representation of Multidimensional Data.
    ACM Symposium on Principles of Database Systems (PODS), 2021.
    Qiuyi Lyu, Yuchen Li, Bingsheng He, Bin Gong.
    DBL: Efficient Reachability Queries on Dynamic Graphs.
    International Conference on Database Systems for Advanced Applications (DASFAA), 2021.
    Wenwen Xia, Yuchen Li, Jun Wu, Shenghong Li.
    DeepIS: Susceptibility Estimation on Social Networks.
    ACM International Conference on Web Search and Data Mining (WSDM), 2021.
    Shixun Huang, Yuchen Li, Zhifeng Bao, Zhao Li.
    Towards Efficient Motif-based Graph Partitioning: An Adaptive Sampling Approach.
    IEEE International Conference on Data Engineering (ICDE), 2021.
    Yuchen Li, Qiwei Zhu, Zheng Lyu, Zhongdong Huang, Jianling Sun.
    DyCuckoo: Dynamic Hash Tables on GPUs.
    IEEE International Conference on Data Engineering (ICDE), 2021.
    Yueji Yang, Yuchen Li, Anthony Tung.
    NewsLink: Empowering Intuitive News Search with Knowledge Graphs.
    IEEE International Conference on Data Engineering (ICDE), 2021.
    Yanhao Wang, Yuchen Li, Raymond Chi-Wing Wong, Kian-Lee Tan.
    A Fully Dynamic Algorithm for k-Regret Minimizing Sets.
    IEEE International Conference on Data Engineering (ICDE), 2021.
    Shengliang Lu, Bingsheng He, Yuchen Li, Hao Fu.
    Accelerating Exact Constrained Shortest Paths on GPUs.
    International Conference on Very Large Data Bases (VLDB), 2020.
    Jingjing Wang, Yanhao Wang, Wenjun Jiang, Yuchen Li, Kian-Lee Tan.
    Efficient Sampling Algorithms for Approximate Temporal Motif Counting.
    ACM International Conference on Information and Knowledge Management (CIKM), 2020.
    Wentao Huang, Yuchen Li, Yuan Fang, Ju Fan, Hongxia Yang.
    BiANE: Bipartite Attributed Network Embedding.
    ACM SIGIR Conference on Information Retrieval (SIGIR), 2020.
    Wentian Guo, Yuchen Li, Mo Sha, Bingsheng He, Xiaokui Xiao, Kian-Lee Tan.
    GPU-Accelerated Subgraph Enumeration on Partitioned Graphs.
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2020.
    Alvis Logins, Yuchen Li, Panagiotis Karras.
    On the Robustness of Cascade Diffusion under Node Attacks (Short).
    The Web Conference (WWW), 2020.
    Hongyang Wang, Qingfei Meng, Ju Fan, Yuchen Li, Laizhong Cui, Xiaoman Zhao, Chong Peng, Gong Chen, Xiaoyong Du.
    Social Influence Does Matter: User Action Prediction for In-Feed Advertising.
    AAAI Conference on Artificial Intelligence (AAAI), 2020.
    Yipeng Zhang, Yuchen Li, Zhifeng Bao, Songsong Mo, Ping Zhang.
    Optimizing Impression Counts for Outdoor Advertising (Oral). Best Research Paper Award (Runner Up)
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019.
    Yanhao Wang, Yuchen Li, Kian-Lee Tan.
    Coresets for Minimum Enclosing Balls over Sliding Windows (Oral).
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019.
    Mo Sha, Yuchen Li, Kian-Lee Tan.
    GPU-based Graph Traversal on Compressed Graphs. SIGMOD reproducibility
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2019.
    Yuchen Li, Ju Fan, George V. Ovchinnikov, Panagiotis Karras.
    Maximizing Multifaceted Network Influence.
    IEEE International Conference on Data Engineering (ICDE), 2019.
    Yanhao Wang, Yuchen Li, Kian-Lee Tan.
    Semantic and Influence-aware K-representative Queries over Social Streams.
    International Conference on Extending Database Technology (EDBT), 2019.
    Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Zhenjie Zhang, Kian-Lee Tan.
    Heterogeneous Embedding Propagation for Large-scale E-Commerce User Alignment (Short).
    IEEE International Conference on Data Mining (ICDM), 2018
    Ping Zhang, Zhifeng Bao, Yuchen Li, Guoliang Li, Yipeng Zhang, Zhiyong Peng.
    Trajectory-driven Influential Billboard Placement (Oral). Best Paper Candidate
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018.
    Yanhao Wang, Yuchen Li, Kian-Lee Tan.
    A Sliding-Window Framework for Representative Subset Selection (short).
    IEEE International Conference on Data Engineering (ICDE), 2018.
    Wentian Guo, Yuchen Li, Mo Sha, Kian-Lee Tan.
    Parallel Personalized PageRank on Dynamic Graphs.
    International Conference on Very Large Data Bases (VLDB), 2017.
    Mo Sha, Yuchen Li, Bingsheng He, Kian-Lee Tan.
    Accelerating Dynamic Graph Analytics on GPUs.
    International Conference on Very Large Data Bases (VLDB), 2017.
    Yuchen Li, Ju Fan, Dongxiang Zhang, Kian-Lee Tan.
    Discovering Your Selling Points: Personalized Social Influential Tags Exploration.
    ACM SIGMOD Conference on Management of Data (SIGMOD), 2017.
    Yanhao Wang, Qi Fan, Yuchen Li, Kian-Lee Tan.
    Real-time Influence Maximization on Dynamic Social Streams.
    International Conference on Very Large Data Bases (VLDB), 2017.
    Yuchen Li, Dongxiang Zhang, Ziquan Lan, Kian-Lee Tan.
    Context-Aware Advertisement Recommendation for High-Speed Social News Feeding.
    IEEE International Conference on Data Engineering (ICDE), 2016.
    Yuchen Li, Dongxiang Zhang, Kian-Lee Tan.
    Real Time Targeted Influence Maximization for Online Advertisements.
    International Conference on Very Large Data Bases (VLDB), 2015
    Yuchen Li, Zhifeng Bao, Guoliang Li, Kian-Lee Tan.
    Real Time Personalized Search on Social Networks.
    IEEE International Conference on Data Engineering (ICDE), 2015.

    Journal Publications

    Yuchen Li, Shixuan Sun, Hanhua Xiao, Chang Ye, Shengliang Lu, Bingsheng He.
    A Survey on Concurrent Processing of Graph Analytical Queries: Systems and Algorithms.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
    Yipeng Zhang, Zhifeng Bao, Yuchen Li, Baihua Zheng, Xiaoli Wang.
    From A Timeline Contact Graph to Close Contact Tracing and Infection Diffusion Intervention.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
    Chang Ye, Yuchen Li, Bingsheng He, Zhao Li, Jianling Sun.
    Large-Scale Graph Label Propagation on GPUs.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.
    Wenwen Xia, Yuchen Li, Shengdong Li.
    On the Substructure Countability of Graph Neural Networks.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
    Wenwen Xia, Yuchen Li, Shengdong Li.
    Graph Neural Point Process for Temporal Interaction Prediction.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
    Alvis Logins, Yuchen Li, Panagiotis Karras.
    On the Robustness of Diffusion in a Network under Node Attacks.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.
    Yanhao Wang, Yuchen Li, Ju Fan, Chang Ye, Mingke Chai.
    A Survey of Typical Attributed Graph Queries.
    World Wide Web (WWW), 2020.
    Wentiao Guo, Yuchen Li, Kian-Lee Tan.
    Exploiting Reuse for GPU Subgraph Enumeration.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.
    Ping Zhang, Zhifeng Bao, Yuchen Li, Guoliang Li, Yipeng Zhang, Zhiyong Peng.
    Towards an Optimal Outdoor Advertising Placement : When a Budget Constraint Meets Moving Trajectories.
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2020.
    Yanhao Wang, Yuchen Li, Kian-Lee Tan.
    Efficient Representative Subset Selection over Sliding Windows.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018.
    Yanhao Wang, Yuchen Li, Ju Fan, Kian-Lee Tan.
    Location-aware Influence Maximization over Dynamic Social Streams.
    ACM Transactions on Information Systems (TOIS), 2018.
    Yuchen Li, Ju Fan, Yanhao Wang, Kian-Lee Tan.
    Influence Maximization on Social Graphs: a Survey.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018.
    Dongxiang Zhang, Yuchen Li, Jie Shao, Hen Tao Shen.
    Augmented Keyword Search on Spatial Entity Databases.
    The International Journal on Very Large Data Bases (VLDBJ), 2018.
    Qi Fan, Yuchen Li, Dongxiang Zhang, Kian-Lee Tan.
    Discovering Newsworthy Themes From Sequenced Data: a Step Towards Computational Journalism.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2017.
    Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen.
    Processing Long Queries Against Short Text: Top-k Advertisement Matching in News Stream Applications.
    ACM Transactions on Information Systems (TOIS), 2017.

    Demos

    Zhao Li, Pengcheng Zou, Xia Chen, Shichang Hu, Peng Zhang, Yumou Zhou, Bingsheng He, Yuchen Li, Xing Tang.
    From Community Search to Community Understanding: A Multimodal Community Query Engine. Best Demo Paper Award (Runner Up)
    ACM International Conference on Information and Knowledge Management (CIKM), 2021.
    Zhao Li, Xia Chen, Xuming Pan, Pengcheng Zou, Yuchen Li, Guoxian Yu.
    SHOAL: Large-scale Hierarchical Taxonomy via Graph-based Query Coalition in E-commerce.
    International Conference on Very Large Data Bases (VLDB), 2019
    Yipeng Zhang, Zhifeng Bao, Songsong Mo, Yuchen Li, Yanghao Zhou.
    ITAA: an Intelligent Trajectory-driven Outdoor Advertising Deployment Assistant.
    International Conference on Very Large Data Bases (VLDB), 2019
    Mo Sha, Yuchen Li, Yanhao Wang, Wentian Guo, Kian-Lee Tan.
    River: a Real-time Influence Monitoring System on Social Media Stream.
    IEEE International Conference on Data Mining (ICDM), 2018
    Ju Fan, Jiarong Qiu, Yuchen Li, Qingfei Meng, Dongxiang Zhang, Guoliang Li, Kian-Lee Tan, Xiaoyong Du.
    OCTOPUS: an Online Topic-Aware Influence Analysis System for Social Networks.
    IEEE International Conference on Data Engineering (ICDE), 2018.

    Teaching

  • CS104 Mathematical Foundations of Computing
  • IS112 Data Management
  • IS480 IS Application Project
  • IS483 IS Project Experience (Application)
  • ACCT652 Data Management

    Selected Awards

  • Outstanding Senior PC Award, CIKM 2024
  • Outstanding Meta-Reviewer Award, ICDE 2024
  • Best Demo Paper Award (Runner Up), CIKM 2021
  • Distinguished Reviewer Award, VLDB 2021
  • Outstanding Reviewer, PAKDD 2020
  • Best Research Paper Award (Runner Up), KDD 2019
  • Lee Kong Chian Fellowship for Research Excellence, SMU 2019-2021, 2022-2024
  • Best Paper Candidate, KDD 2018
  • Audience Appreciation Award Nomination, KDD 2018
  • Research Achivement Award, NUS 2015

    Selected Services

  • Associate Editor of ICDE 2025, 2024
  • Senior PC of CIKM 2024
  • Demo Chair of DASFAA 2025
  • Proceedings Chair of SSDBM 2022
  • Virtual Conference Co-chair of KDD 2021
  • Contest Chair of ICDM 2018
  • PC member of VLDB 2025, 2021, 2020
  • PC member of SIGIR 2024, 2023
  • PC member of SIGMOD 2023
  • PC member of KDD 2023
  • PC member of CIKM 2023, 2021, 2019, 2017
  • PC member of ICDE 2022
  • PC member of IEEE Big Data 2022, 2020, 2019
  • PC member of ASONAM 2020, 2019
  • PC member of ER 2019, 2018
  • PC member of ICDCS 2020
  • PC member of PAKDD 2020
  • Invited Reviewer for the VLDB journal
  • Invited Reviewer for ACM Transactions on Database Systems
  • Invited Reviewer for ACM Transactions on Web
  • Invited Reviewer for ACM Transactions on Data Science
  • Invited Reviewer for ACM Transactions on Information Systems
  • Invited Reviewer for IEEE Transactions on Knowledge and Data Engineering
  • Invited Reviewer for IEEE Transactions on Big Data
  • Invited Reviewer for IEEE Transactions on Network Science and Engineering
  • Guest Editor for IET Smart Cities
  • Veni Grant Reviewer for the Dutch Research Council 2020