yangdingqi

Dingqi YANG

Associate Professor,
Department of Computer and Information Science/State Key Laboratory of Internet of Things for Smart City,
University of Macau, Macau SAR, China
Tel: (00853) 8822 9971
Email: dingqiyang [THAT SYMBOL] um.edu.mo

News

  • 2024.02  One paper on link prediction on noisy knowledge graphs has been accepted by WWW 2024. [PDF] [CODE]
  • 2023.08 One paper on hyper-relational schema modeling has been accepted by ACM MM 2023. [PDF] [CODE]
  • 2023.08 One paper on robust location prediction “Flashback to the Right Moment!” has been accepted by TIST. [PDF] [CODE]
  • 2023.07 One paper on KG instance completion following the “Fast and Slow Thinking” principle has been accepted by TKDE. [PDF] [CODE]
  • 2023.06 One survey on hypergraph representation learning has been accepted by CSUR. [PDF]
  • 2022.12 One paper on embedding based graph analyses has been accepted by TKDE. [PDF] [CODE]
  • 2022.11 One paper on crowd flow prediction for smart campus has been accepted by TPCI [DEMO] [PDF].
  • 2022.02 One paper on streaming graph embeddings has been accepted by TKDE [PDF] [CODE].
  • 2020.11 I moved to the University of Macau as an Associate Professor in Computer Science.

Biography

I’m currently an Associate Professor at the Department of Computer and Information Science with the State Key Laboratory of Internet of Things for Smart City at the University of Macau. Prior to that, I was a senior researcher in the eXascale Infolab at the University of Fribourg, Switzerland from 2015 to 2020. I received my Ph.D. (with highest honors) in Computer Science from Institut Mines-Télécom/Télécom SudParis and Université Pierre et Marie Curie, Paris 6 in Jan. 2015, under the supervision of Prof. Daqing Zhang. In June 2015, My Ph.D. thesis won the CNRS Samovar Doctorate Award (“Prix Doctorant CNRS Samovar/Télécom SudParis”) and Institut Mines-Télécom Press Mention. I’m also a recipient of the “2014 Chinese Government Award for Outstanding Self-financed (non-government sponsored) Students Abroad“.

Research Interests

I’m broadly interested in designing novel data mining and machine learning techniques to efficiently discover knowledge and get insights from Big Data, and also in building practical systems to tackle real-world problems. My research interests lie primarily on Ubiquitous Big Data Analytics, Social Network Analysis, Predictive Modelling, Data Sketching, and Data Privacy.

Selected Recent Publications

  • Weijian Yu, Jie Yang, Dingqi Yang*, Robust Link Prediction over Noisy Hyper-Relational Knowledge Graphs via Active Learning, In Proc. of ACM Web Conference (WWW’24), May. 2024, Singapore. [PDF] [CODE]
  • Yuhuan Lu, Bangchao Deng, Weijian Yu, Dingqi Yang*, HELIOS: Hyper-Relational Schema Modeling from Knowledge Graphs, In Proc. of ACM International Conference on Multimedia (MM’23), Oct. 2023, Ottawa. [PDF] [CODE]
  • Bangchao Deng, Dingqi Yang*, Bingqing Qu, Benjamin Fankhauser, Philippe Cudre-Mauroux, Robust Location Prediction over Sparse Spatiotemporal Trajectory Data: Flashback to the Right Moment ACM Transactions on Intelligent Systems and Technology (TIST), 2023. [PDF] [CODE]
  • Dingqi Yang, Bingqing Qu, Paolo Rosso, and Philippe Cudre-Mauroux, Fast and Slow Thinking: A Two-Step Schema-Aware Approach for Instance Completion in Knowledge Graphs, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. [PDF] [CODE]
  • Alessia Antelmi, Gennaro Cordasco, Mirko Polato, Vittorio Scarano, Carmine Spagnuolo, Dingqi Yang, A Survey on Hypergraph Representation Learning, ACM Computing Surveys (CSUR), 2023. [PDF]
  • Dingqi Yang, Bingqing Qu, Rana Hussein, Paolo Rosso, Philippe Cudre-Mauroux, and Jie Liu, Revisiting Embedding Based Graph Analyses: Hyperparameters Matter! IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. [PDF] [CODE]
  • Dingqi Yang, Bingqing Qu, Jie Yang, Liang Wang, Philippe Cudre-Mauroux, Streaming Graph Embeddings via Incremental Neighborhood Sketching, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022. [PDF] [CODE]
  • Paolo Rosso, Dingqi Yang*, Philippe Cudre-Mauroux, RETA: A Schema-Aware, End-to-End Solution for Instance Completion in Knowledge Graphs, In Proc. of The Web Conference (WWW’21). April 2021, Ljubljana. [PDF] [CODE]
  • Dingqi Yang, Bingqing Qu, Jie Yang, Philippe Cudre-Mauroux, LBSN2Vec++: Heterogeneous Hypergraph Embedding for Location-Based Social Networks, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020. [PDF] [CODE]
  • Dingqi Yang, Benjamin Fankhauser, Paolo Rosso, Philippe Cudre-Mauroux, Location Prediction over Sparse User Mobility Traces using RNNs: Flashback in Hidden States! In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI’20). July 2020, Japan. [PDF] [CODE] [VIDEO]
  • Paolo Rosso, Dingqi Yang*, Philippe Cudre-Mauroux, Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction, In Proc. of The Web Conference (WWW’20). April 2020, Taipei. [PDF] [CODE]
  • Full publication list …

Students

  • Ph.D. students at University of Macau: Bangchao Deng (2024-), Sirui Lai (2023-), Xin Jing (2022-), Yuhuan Lu (2021-)
  • Ph.D. students at University of Fribourg, Switzerland: Paolo Rosso (2017-2021), Rana Hussein (2017-2018)
  • M.S. students at University of Macau: Terence Un Chong In (2023-), Yuxin Yang (2022-), Yanwei Hua (2022-), Hao Yuan (2022-), Weijian Yu (2021-), Chunhua Chen (2021-), Bangchao Deng (2021-2023), Shiyu Zhang (2021-2023), Hang Yin (2021-2023)
  • M.S. students at University of Fribourg, Switzerland: Terence Heaney (Fall 2016)
  • M.S. students at Telecom SudParis, France: Christos Sotiriou (Fall 2013)

Demos

  • NationTelescope: Monitoring and Visualizing Large-Scale Collective Behavior in LBSNs. [Demo] [PDF] [Dataset]

  • CrimeTelescope: Crime Hotspot Prediction based on Urban and Social Media Data Fusion. [Demo] [PDF]

  • CrowdTelescopeWi-Fi-Positioning-Based Multi-Grained Spatiotemporal Crowd Flow Prediction for Smart Campus. [Demo] [PDF]