Associate Professor Sen Wang
Associate Professor

Sen Wang

Email: 
Phone: 
+61 7 336 52907

Background

Dr Sen Wang is an ARC DECRA Senior Research Fellow and Senior Lecturer in computer science and data science at the School of Information Technology and Electrical Engineering at UQ. He is also a CI on several health data analytics research grants. Sen has an interest in ICU data and has clinical collaborations with RBWH and Children’s Hospital. Dr Wang received his PhD degree in 2014 and his research interest includes various topics on Feature Selection, Semi-supervised Learning, Deep Learning, Pattern Recognition, Data Mining, and Health Informatics. Since 2010, Dr Wang has published 80+ academic papers in top conferences and journals. Most were published in internationally renowned journals and conferences in the fields of data science, data mining, and machine learning, such as Algorithmica, TNNLS, TMC, TKDE, TCYB, TMM, WWWJ, Signal Processing, ACM TOMM, ACM MM, IJCAI, AAAI, SDM, CIKM, CVPR, ICCV, ICDM, ISWC, ECML-PKDD, PAKDD, ICONIP, ICPADS, and WISE, all CORE A/A* journals and conferences.

Availability

Associate Professor Sen Wang is:
Available for supervision

Fields of research

Biomedical and Clinical Sciences Information and Computing Sciences Machine learning

Qualifications

  • Doctor of Philosophy, The University of Queensland

Search Professor Sen Wang’s works on UQ eSpace

113 works between 2012 and 2025
All (113) Journal Article (40) Book Chapter (1) Conference Publication (68) Other Outputs (1) Edited Outputs (3)

81 - 100 of 113 works

2017

Journal Article

A multiview learning framework with a linear computational cost

Xue, Xiaowei, Nie, Feiping, Li, Zhihui, Wang, Sen, Li, Xue and Yao, Min (2017). A multiview learning framework with a linear computational cost. IEEE Transactions on Cybernetics, 48 (8), 2416-2425. doi: 10.1109/TCYB.2017.2739423

A multiview learning framework with a linear computational cost

2017

Journal Article

Unsupervised 2D dimensionality reduction with adaptive structure learning

Zhao, Xiaowei, Nie, Feiping, Wang, Sen, Guo, Jun, Xu, Pengfei and Chen, Xiaojiang (2017). Unsupervised 2D dimensionality reduction with adaptive structure learning. Neural Computation, 29 (5), 1352-1374. doi: 10.1162/NECO_a_00950

Unsupervised 2D dimensionality reduction with adaptive structure learning

2017

Journal Article

Collaborative text categorization via exploiting sparse coefficients

Yao, Lina, Sheng, Quan Z., Wang, Xianzhi, Wang, Shengrui, Li, Xue and Wang, Sen (2017). Collaborative text categorization via exploiting sparse coefficients. World Wide Web: internet and web information systems, 21 (2), 1-22. doi: 10.1007/s11280-017-0460-2

Collaborative text categorization via exploiting sparse coefficients

2017

Journal Article

Learning multiple diagnosis codes for ICU patients with local disease correlation mining

Wang, Sen, Li, Xue, Chang, Xiaojun, Yao, Lina, Sheng, Quan Z. and Long, Guodong (2017). Learning multiple diagnosis codes for ICU patients with local disease correlation mining. ACM Transactions on Knowledge Discovery from Data, 11 (3) 31, 1-21. doi: 10.1145/3003729

Learning multiple diagnosis codes for ICU patients with local disease correlation mining

2017

Conference Publication

PDD graph: bridging electronic medical records and biomedical knowledge graphs via entity linking

Wang, Meng, Zhang, Jiaheng, Liu, Jun, Hu, Wei, Wang, Sen, Li, Xue and Liu, Wenqiang (2017). PDD graph: bridging electronic medical records and biomedical knowledge graphs via entity linking. The Semantic Web – ISWC 2017: 16th International Semantic Web Conference Vienna, Austria, October 21–25, 2017 Proceedings, Part II, Vienna, Austria, 21-25 October 2017. Cham, Switzerland: Springer Nature. doi: 10.1007/978-3-319-68204-4_23

PDD graph: bridging electronic medical records and biomedical knowledge graphs via entity linking

2017

Conference Publication

Improving chinese sentiment analysis via segmentation-based representation using parallel CNN

Hao, Yazhou, Zheng, Qinghua, Lan, Yangyang, Li, Yufei, Wang, Meng, Wang, Sen and Li, Chen (2017). Improving chinese sentiment analysis via segmentation-based representation using parallel CNN. 13th International Conference on Advanced Data Mining and Applications ADMA 2017, Singapore, 5–6 November 2017. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-69179-4_47

Improving chinese sentiment analysis via segmentation-based representation using parallel CNN

2017

Conference Publication

Uncovering locally discriminative structure for feature analysis

Wang, Sen, Nie, Feiping, Chang, Xiaojun, Li, Xue, Sheng, Quan Z. and Yao, Lina (2017). Uncovering locally discriminative structure for feature analysis. 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016, Riva del Garda, Italy, 19 - 23 September 2016. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-46128-1_18

Uncovering locally discriminative structure for feature analysis

2017

Conference Publication

Provenance-based rumor detection

Duong, Chi Thang, Nguyen, Quoc Viet Hung, Wang, Sen and Stantic, Bela (2017). Provenance-based rumor detection. 28th Australasian Database Conference, ADC 2017, Brisbane, QLD Australia, 25–28 September 2017. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-68155-9_10

Provenance-based rumor detection

2017

Conference Publication

Multi-view correlated feature learning by uncovering shared component

Xue, Xiaowei, Nie, Feiping, Wang, Sen, Chang, Xiaojun, Stantic, Bela and Yao, Min (2017). Multi-view correlated feature learning by uncovering shared component. 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, CA United States, 4–9 February 2017. Washington, DC United States: AAAI Press. doi: 10.1609/aaai.v31i1.10823

Multi-view correlated feature learning by uncovering shared component

2016

Journal Article

Diagnosis code assignment using sparsity-based disease correlation embedding

Wang, Sen, Chang, Xiaojun, Li, Xue, Long, Guodong, Yao, Lina and Sheng, Quan Z. (2016). Diagnosis code assignment using sparsity-based disease correlation embedding. IEEE Transactions on Knowledge and Data Engineering, 28 (12), 3191-3202. doi: 10.1109/TKDE.2016.2605687

Diagnosis code assignment using sparsity-based disease correlation embedding

2016

Journal Article

Compound rank-k projections for bilinear analysis

Chang, Xiaojun, Nie, Feiping, Wang, Sen, Yang, Yi, Zhou, Xiaofang and Zhang, Chengqi (2016). Compound rank-k projections for bilinear analysis. IEEE Transactions on Neural Networks and Learning Systems, 27 (7) 7161356, 1502-1513. doi: 10.1109/TNNLS.2015.2441735

Compound rank-k projections for bilinear analysis

2016

Journal Article

Multi-task support vector machines for feature selection with shared knowledge discovery

Wang, Sen, Chang, Xiaojun, Li, Xue, Sheng, Quan Z. and Chen, Weitong (2016). Multi-task support vector machines for feature selection with shared knowledge discovery. Signal Processing, 120, 746-753. doi: 10.1016/j.sigpro.2014.12.012

Multi-task support vector machines for feature selection with shared knowledge discovery

2016

Conference Publication

Unobtrusive posture recognition via online learning of multi-dimensional RFID received signal strength

Yao, Lina, Sheng, Quan Z., Ruan, Wenjie, Li, Xue, Wang, Sen and Yang, Zhi (2016). Unobtrusive posture recognition via online learning of multi-dimensional RFID received signal strength. 2015 IEEE 21st International Conference on Parallel and Distributed Systems, ICPADS 2015, Melbourne, Victoria, Australia, 14- 17 December 2015. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPADS.2015.23

Unobtrusive posture recognition via online learning of multi-dimensional RFID received signal strength

2016

Conference Publication

Classification based on compressive multivariate time series

Utomo, Chandra, Li, Xue and Wang, Sen (2016). Classification based on compressive multivariate time series. 27th Australasian Database Conference on Databases Theory and Applications, ADC 2016, Sydney Australia, 28-29 September 2016. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-46922-5_16

Classification based on compressive multivariate time series

2016

Conference Publication

Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing data

Yao, Lina, Sheng, Quan Z., Li, Xue, Wang, Sen, Gu, Tao, Ruan, Wenjie and Zou, Wan (2016). Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing data. 15th IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, United States, 14-17 November 2015. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDM.2015.102

Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing data

2016

Conference Publication

Learning from less for better: semi-supervised activity recognition via shared structure discovery

Yao, Lina, Nie, Feiping, Sheng, Quan Z., Gu, Tao, Li, Xue and Wang, Sen (2016). Learning from less for better: semi-supervised activity recognition via shared structure discovery. 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016, Heidelberg, Germany, 12-16 September 2016. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2971648.2971701

Learning from less for better: semi-supervised activity recognition via shared structure discovery

2016

Conference Publication

Learning graph-based POI embedding for location-based recommendation

Xie, Min, Yin, Hongzhi, Wang, Hao, Xu, Fanjiang, Chen, Weitong and Wang, Sen (2016). Learning graph-based POI embedding for location-based recommendation. 25th ACM International Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, United States, 24 - 28 October 2016. New York, NY, United States: ACM. doi: 10.1145/2983323.2983711

Learning graph-based POI embedding for location-based recommendation

2015

Journal Article

Multi-label classification via learning a unified object-label graph with sparse representation

Yao, Lina, Sheng, Quan Z., Ngu, Anne H.H., Gao, Byron J., Li, Xue and Wang, Sen (2015). Multi-label classification via learning a unified object-label graph with sparse representation. World Wide Web, 19 (6), 1-25. doi: 10.1007/s11280-015-0376-7

Multi-label classification via learning a unified object-label graph with sparse representation

2015

Journal Article

Compact representation for large-scale unconstrained video analysis

Wang, Sen, Pan, Pingbo, Long, Guodong, Chen, Weitong, Li, Xue and Sheng, Quan Z. (2015). Compact representation for large-scale unconstrained video analysis. World Wide Web, 19 (2), 231-246. doi: 10.1007/s11280-015-0354-0

Compact representation for large-scale unconstrained video analysis

2015

Conference Publication

Unsupervised feature analysis with class margin optimization

Wang, Sen, Nie, Feiping, Chang, Xiaojun, Yao, Lina, Li, Xue and Sheng, Quan Z. (2015). Unsupervised feature analysis with class margin optimization. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Porto, Portugal, 7-11 September 2015. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-23528-8_24

Unsupervised feature analysis with class margin optimization

Current funding

  • 2024 - 2029
    ARC Training Centre in Predictive Breeding for Agricultural Futures
    ARC Industrial Transformation Training Centres
    Open grant
  • 2024 - 2027
    Embracing Changes for Responsive Video-sharing Services
    ARC Discovery Projects
    Open grant
  • 2023 - 2026
    Short Sequence Representation Learning with Limited Supervision
    ARC Discovery Projects
    Open grant
  • 2021 - 2026
    ARC Training Centre for Information Resilience
    ARC Industrial Transformation Training Centres
    Open grant

Past funding

  • 2020 - 2024
    Towards Explainable Multi-source Multivariate Time-series Analysis
    ARC Discovery Early Career Researcher Award
    Open grant
  • 2019 - 2022
    Collaborative Lab of Health Informatics with Neusoft
    Neusoft Research of Intelligent Healthcare Technology, Co Ltd
    Open grant

Availability

Associate Professor Sen Wang is:
Available for supervision

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Supervision history

Current supervision

  • Doctor Philosophy

    Short Sequence Representation Learning with Limited Supervision

    Principal Advisor

    Other advisors: Professor Xue Li, Associate Professor Jiajun Liu

  • Doctor Philosophy

    Expanding Data Sets to Allow Improved Critical Care for Children - Outpatient Risk Prediction

    Principal Advisor

    Other advisors: Professor Shazia Sadiq, Associate Professor Adam Irwin

  • Doctor Philosophy

    Information-Preserving Efficient Vision Transformers

    Principal Advisor

    Other advisors: Associate Professor Jiajun Liu

  • Doctor Philosophy

    Towards Explainable Multi-source Multivariate Time-series Analysis

    Principal Advisor

    Other advisors: Associate Professor Jiajun Liu

  • Doctor Philosophy

    Towards Explainable Multi-source Multivariate Time-series Analysis

    Principal Advisor

    Other advisors: Associate Professor Jiajun Liu, Dr Ruihong Qiu

  • Doctor Philosophy

    Understanding Human Intention and Performance

    Associate Advisor

    Other advisors: Dr Xin Yu

  • Doctor Philosophy

    Combating evolving deceptive fake visual information through deepfake detection

    Associate Advisor

    Other advisors: Dr Xin Yu

  • Doctor Philosophy

    Short Sequence Representation Learning with Limited Supervision

    Associate Advisor

    Other advisors: Professor Xue Li

  • Doctor Philosophy

    The prediction, diagnosis, and severity estimation models for plant disease

    Associate Advisor

    Other advisors: Dr Xin Yu

  • Doctor Philosophy

    Towards Efficient Pest Detection in Agriculture

    Associate Advisor

    Other advisors: Dr Xin Yu

  • Doctor Philosophy

    AI-guided prediction of genomic breeding values for yield and vigour in macadamia

    Associate Advisor

    Other advisors: Professor Bruce Topp, Professor Lee Hickey, Dr Eric Dinglasan, Dr Mobashwer Alam

Completed supervision

Enquiries

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