- 03/2022, 1 paper accepted by ACM SIGMOD 2022, 1 paper by WWW 2022, and 2 papers by EDBT 2022.
- 11/2021, 1 paper accepted by ACM Trans. on Information Systems (ACM TOIS) in 2022.
- 09/2021, 1 paper accepted by IEEE/ACM Trans. on Network (ACM TON) in 2022.
- 01/2022, Prof Xiangrui Wang will visit my research group for one year.
- 08/2021, we have 3 papers accepted by IEEE Trans. on Industrial Informatics (IEEE TII) (IF: 10.2), IEEE Trans. on Intelligent Transportation Systems (IEEE TITS) (IF: 6.5), and ACM Trans. on Sensor Networks.
- 07/2021, Xinxin received a CSC scholarship in 2022. Congrats!
- 07/2021, I have been the Data Science Course Director at CS Warwick.
- 05/2021, Sima has a paper on RoleSim* search accepted by WWW, in collaboration with Hakan's group.
- 04/2021, I joined the PC of VLDB 2022.
- 02/2021, we are guest-editing a special issue on Mathematical Methods and Application in Machine Learning of Mathematics. Please consider submitting your work.
Weiren is an Assistant Professor in the Department of Computer Science at the University of Warwick since 2020. He is the Data Science Course Director and a member of the Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research (SBIDER). He was awarded an Honorary Visiting Fellow by the Department of Computing at Imperial College. Weiren received his Ph.D. degree from the School of Computer Science and Engineering at the University of New South Wales (UNSW, Sydney). During his years at UNSW, he was also a Research Assistant at the Commonwealth Scientific and Industrial Research Organisation (CSIRO), and National ICT Australia (NICTA). After that, he spent two years as a Postdoctoral Researcher at the Adaptive Embedded Systems Engineering (AESE) Laboratory in the Department of Computing, Imperial College. He collaborated with NEC Europe Ltd and the Department of Civil and Environmental Engineering at Imperial, working on an IoT project “Big Data Technologies for Smart Water Systems”.
Weiren is a recipient of seven Best Paper Awards, including one Best Research Paper Award for ECSA 2016, two CiSRA (Canon Information Systems Research Australia) Best Research Paper Awards for ICDE 2014 and VLDB 2013 respectively, one One of the Best Papers of ICDE in 2013, and three Best (Student) Paper Awards for APWEB 2010, WAIM 2010 and WAIM 2011, respectively. He is a member of the IEEE and ACM.
Weiren is interested in developing effective and efficient data analysis techniques for novel data-intensive applications. His current research interests span the area of Big Data analytics, including:
- Large-scale Graph Mining
- Information Retrieval (e.g., web search, hyperlink analysis, recommendation systems, social networks)
- AI, Deep Learning, and Neural Computing in DB
- Spatio-temporal Analytics and Big Data Mining
Weiren has been serving on various editorial boards, and on Programme Committees (e.g., VLDB 2022 PC) and is an active reviewer of many top international journals and conferences.
- IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE)
- IEEE Transactions on Information Forensics and Security (IEEE TIFS)
- IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS)
- ACM Transactions on Information Systems (ACM TOIS)
- ACM Transactions on Knowledge Discovery from Data (ACM TKDD)
- ACM Transactions on Web (ACM TWEB)
- ACM Transactions on Networks (ACM TON)
- The VLDB Journal (VLDB J.)
- World Wide Web Journal (WWW J.)
- Information Systems (IS)
- Data Mining and Knowledge Discovery (DMKD)
- International Journal of Software and Informatics (IJSI)
Conference TPC & Reviewer
- ACM SIGIR International Conference (SIGIR)
- ACM SIGMOD International Conference (SIGMOD)
- International Conference on Very Large Data Base (VLDB)
- International Conference on Data Mining (ICDM)
- Conference on Information and Knowledge Management (CIKM)
- Database Systems for Advanced Applications (DASFAA)
- Australian Database Conference (ADC)
- International Conference on Extending Database Technology (EDBT)
- Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
- Data Warehousing and Knowledge Discovery (DaWak)
- International Conference on Advances in Geographic Information Systems (SIGSPATIAL)
- International Conference on Web-Age Information Management (WAIM)
Some Selected Publications [Full in DBLP]Link opens in a new window
Weiren published more than 60 REF-able papers in prestigious DB and IR-related journals (e.g. VLDB J., ACM TOIS, ACM TON, IEEE TKDE, IEEE TIFS, IEEE TITS, IEEE TII, ACM TWEB) and conferences (e.g. SIGMOD, PVLDB, SIGIR, ICDE, WWW, ICDM, ACL, EDBT, CIKM). Some representative work is as follows:
- X. Ren, L. Shi, W. Yu, S. Yang, C. Zhao, and Z. Xu. LDP-IDS: Local Differential Privacy for Infinite Data Stream. In
Proceedings of the 2022 International Conference on Management of Data (ACM SIGMOD '22), (14 pages) 2022, Accepted to appear. Philadelphia, PA, USA.
- W. Yu, J. Yang, M. Zhang, and D. Wu. CoSimHeat: An Effective Heat Kernel Similarity Measure Based on Billion-Scale Network Topology. The Web Conference (WWW '22). (12 pages) Accepted. 2022.
- W. Yu, J. McCann, C. Zhang, and H. Ferhatosmanoglu. Scaling High-Quality Pairwise Link-Based Similarity Retrieval on Billion-Edge Graphs. ACM Transactions on Information System (ACM TOIS). 40(4): 1-45 (2022)
- D. Wu, H. Xu, Z. Jiang, W. Yu, X. Wei, J. Lu. EdgeLSTM: Towards Deep and Sequential Edge Computing for IoT Applications. IEEE/ACM Transactions on Networking (IEEE/ACM TON). 29(4): 1895-1908 (2021)
- D. Wu, Z. Jiang, X. Xie, X. Wei, W. Yu, R. Li. LSTM Learning With Bayesian and Gaussian Processing for Anomaly Detection in Industrial IoT. IEEE Trans. Ind. Informatics (IEEE. TII) 16(8): 5244-5253 (2020)
- W. Yu, X. Lin, W. Zhang, J. Pei, J. McCann. SimRank*: Effective and scalable pairwise similarity search based on graph topology. The VLDB Journal, 28(3), pp. 401-426, 2019
- W. Yu, J. McCann, C. Zhang. Efficient Pairwise Penetrating-rank Similarity Retrieval. ACM Transactions on Web (ACM TWEB). 13(4): 21:1-21:52 (2019)
- W. Yu, X. Lin, W. Zhang, and J. McCann. Dynamical SimRank Assessment on Time-Varying Networks. The VLDB Journal. 79-104. 2018.
- X. Ren, C. Yu, W. Yu, S. Yang, X. Yang, J. McCann, and P. S. Yu. LoPub: High-Dimensional Crowdsourced Data Publication with Local Differential Privacy. IEEE Transactions on Information Forensics & Security (IEEE TIFS), pp. 2151-2166, 2018.
- W. Yu, and F. Wang. Fast Exact CoSimRank Search on Evolving and Static Graphs. The 27th International World Wide Web Conference (WWW '18). Lyon, France, pp. 599-608, 2018.
- W. Yu, and J. McCann. Random Walk with Restart over Dynamic Graphs. The 15th IEEE International Conference on Data Mining (IEEE ICDM '16). Barcelona, Spain, pp.589-598, 2016.
- W. Yu, and J. McCann. Efficient Partial-Pairs SimRank Search on Large Graphs. The 41st International Conference on Very Large Data Base (VLDB '15). Hawaii, USA, pp. 569-580, 2015.
- W. Yu, and J. McCann. High-Quality Graph-Based Similarity Search. The 38th ACM SIGIR International Conference (ACM SIGIR '15). Santiago, Chile, pp. 83-93, 2015.
- W. Yu, and J. McCann. Co-Simmate: Quick Retrieving All Pairwise Co-Simrank Scores. The 53rd Annual Meeting of the Association for Computational Linguistics. (ACL '15). Beijing, China, pp. 327-334, 2015.
- W. Yu, X. Lin, and W. Zhang. Fast Incremental SimRank on Link-Evolving Graphs. The 30th IEEE International Conference on Data Engineering (IEEE ICDE '14), Chicago, USA, pp. 304-315, 2014.
- W. Yu, and J. McCann. Sig-SR: SimRank Search over Singular Graphs.The 37th ACM SIGIR International Conference (ACM SIGIR '14), Brisbane, Australia, 2014.
- W. Yu, X. Lin, W. Zhang, and J. McCann. Fast All-Pairs SimRank Assessment on Large Graphs and Bipartite Domains. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 27(7): 1810-1823, 2014.
- W. Yu, X. Lin, and W. Zhang. Towards Efficient SimRank Computation on Large Networks. The 29th IEEE International Conference on Data Engineering (IEEE ICDE '13), Brisbane, Australia, pp. 601-612, 2013.
- W. Yu, X. Lin, W. Zhang, L. Chang, and J Pei. More is Simpler: Effectively and Efficiently Assessing Node-Pair Similarities Based on Hyperlinks. The 40th International Conference on Very Large Data Base (VLDB '13), Hangzhou, China, pp. 13-24, 2013.
- W. Yu, and X. Lin. IRWR: Incremental Random Walk with Restart. The 36th ACM SIGIR International Conference (ACM SIGIR '13), Dublin, Ireland, 2013.
- W. Yu, X. Lin, W. Zhang, Y. Zhang, and J. Le. SimFusion+: Extending SimFusion Towards Efficient Estimation on Large and Dynamic Networks. The 35th ACM SIGIR International Conference (ACM SIGIR '12), Portland, USA, pp. 365-374, 2012.
- W. Yu, J. McCann, C. Zhang, and H. Ferhatosmanoglu. Scaling High-Quality Pairwise Link-Based Similarity Retrieval on Billion-Edge Graphs. (A complete version with proofs of all theorems and lemmas, 47 pages). [PDFLink opens in a new window]
- W. Yu, S. Iranmanesh, A. Haldar, M. Zhang, and H. Ferhatosmanoglu. An Axiomatic Role Similarity Measure Based on Graph Topology. [PDF]Link opens in a new window
Room: MSB 5.31
Department of Computer Science
University of Warwick
Tel: +44 (0) 24 761 50759
We have multiple PhD scholarships available for International / EU / Home Students.
I am always looking for self-motivated students who want to pursue a PhD degree in the general area of Big Data Science. Please drop me an email with your CV and academic transcripts (UG/PG).