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

118 works between 2012 and 2026
All (118) Journal Article (41) Other Outputs (1) Edited Outputs (3) Conference Publication (72) Book Chapter (1)

81 - 100 of 118 works

2018

Conference Publication

Dynamic Illness Severity Prediction via Multi-task RNNs for Intensive Care Unit

Chen, Weitong, Wang, Sen, Long, Guodong, Yao, Lina, Sheng, Quan Z. and Li, Xue (2018). Dynamic Illness Severity Prediction via Multi-task RNNs for Intensive Care Unit. 18th IEEE International Conference on Data Mining, ICDM 2018, Singapore, 17 - 20 November 2018. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2018.00111

Dynamic Illness Severity Prediction via Multi-task RNNs for Intensive Care Unit

2018

Conference Publication

EEG-based motion intention recognition via multi-task RNNs

Chen, Weitong, Wang, Sen, Zhang, Xiang, Yao, Lina, Yue, Lin, Qian, Buyue and Li, Xue (2018). EEG-based motion intention recognition via multi-task RNNs. 2018 SIAM International Conference on Data Mining, SDM 2018, San Diego, CA, United States, 3-5 May 2018. Society for Industrial and Applied Mathematics Publications. doi: 10.1137/1.9781611975321.32

EEG-based motion intention recognition via multi-task RNNs

2018

Conference Publication

Fuzzy integral optimization with deep Q-network for EEG-based intention recognition

Zhang, Dalin, Yao, Lina, Wang, Sen, Chen, Kaixuan, Yang, Zheng and Benatallah, Boualem (2018). Fuzzy integral optimization with deep Q-network for EEG-based intention recognition. 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, 25–28 May 2023. Weinheim, Germany: Springer. doi: 10.1007/978-3-319-93034-3_13

Fuzzy integral optimization with deep Q-network for EEG-based intention recognition

2017

Journal Article

Answering why-not questions on semantic multimedia queries

Wang, Meng, Chen, Weitong, Wang, Sen, Liu, Jun, Li, Xue and Stantic, Bela (2017). Answering why-not questions on semantic multimedia queries. Multimedia Tools and Applications, 77 (3), 3405-3429. doi: 10.1007/s11042-017-5151-6

Answering why-not questions on semantic multimedia queries

2017

Journal Article

Multi-factors based sentence ordering for cross-document fusion from multimodal content

Yue, Lin, Shi, Zhenkun, Han, Jiayu, Wang, Sen, Chen, Weitong and Zuo, Wanli (2017). Multi-factors based sentence ordering for cross-document fusion from multimodal content. Neurocomputing, 253, 6-14. doi: 10.1016/j.neucom.2016.12.084

Multi-factors based sentence ordering for cross-document fusion from multimodal content

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

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

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

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

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

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

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
  • 2021 - 2026
    ARC Training Centre for Information Resilience
    ARC Industrial Transformation Training Centres
    Open grant

Past funding

  • 2023 - 2026
    Short Sequence Representation Learning with Limited Supervision
    ARC Discovery Projects
    Open grant
  • 2020 - 2025
    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

Completed supervision

Enquiries

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