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Assoc Prof Xiaohui Tao

Assoc Prof Xiaohui Tao
Name Xiaohui Tao
Position Head of School (Mathematics, Physics and Computing)
Section School of Mathematics, Physics and Computing
Office D102
Location Toowoomba Campus
Phone +61 7 4631 1576
Extension 1576
Email
Qualifications PhD QUT
Homepage https://tao-xiaohui.info
The views expressed on staff homepages may not reflect the views of the University.

Dr. Xiaohui Tao is an elected Senior Member of IEEE and ACM, an active researcher in AI, and Associate Professor (Computing) in School of Mathematics, Physics and Computing (SoMPC), University of Southern Queensland (USQ), Australia. His research interests include data analytics, machine learning, knowledge engineering, information retrieval, and health informatics. During his research career, Tao gained a wealth of knowledge and experience in dealing with massive data sets and delivering solutions to complex research problems. He developed many innovative models, methods and systems, such as a multi-disease recommender system, a clinic decision support system for personalised and evidence-based medicine, a heterogeneous information graph model for health risk prediction, an algorithm to detect potential mental issues using sentiment analysis and natural language processing techniques, and an ontology learning and mining model for personalised information gathering, and made contributions to the areas such as Knowledge Engineering, Text Mining and Information Retrieval and Health informatics. The research outcomes have been published on many top-tier journals (e.g., TKDE, IPM, KBS, ESWA, and PRL) and conferences (e.g., IJCAI, ICDE, CIKM, PAKDD and WISE). A/Prof. Tao received ARC DP grant (Ref. DP220101360) in 2022-24, Australian Endeavour Research Fellow in 2015-16, and was awarded with "Research Performance Award" and "Discipline Research Performance Improvement Award" by SoMPC, USQ, "Research Award" by Department of Mathematics and Computing, USQ in 2012 and "Dean's Award for Academic Excellence" by Faculty of Science and Technology at QUT in 2009. A/Prof. Tao has been active in professional services. He has served PC Chair in WI '17, '18, WI-IAT '21 and BESC '18 and '21. He has been an editor or guest editor in many journals including INFFUS and WWWJ, and also been a regular reviewer in many top-ranking journals such as TKDE, TPDS, and KBS. Dr. Tao has also been actively participating in tertiary education ever since 2005 and taught a variety of IT/IS subjects. Currently, he is the lead of the Intelligent Data Engineering and Analytics Group in SoMPC, USQ and is the Principal Supervisor of a number of PhD and Research Master students.


Fields of Research (FoR)

  • Expert Systems ( 080105 )
  • Pattern Recognition and Data Mining ( 080109 )
  • Natural Language Processing ( 080107 )
  • Natural Language Processing ( 460208 )
  • Artificial Intelligence ( 460200 )
  • Data Mining And Knowledge Discovery ( 460502 )
  • Data Management And Data Science ( 460500 )
  • Recommender Systems ( 460510 )
  • Information Retrieval And Web Search ( 460508 )
  • Semi- And Unsupervised Learning ( 461106 )
  • Knowledge Representation And Reasoning ( 460206 )
  • Deep Learning ( 461103 )
  • Context Learning ( 461102 )
  • Machine Learning ( 461100 )
  • Reinforcement Learning ( 461105 )
  • Neural Networks ( 461104 )

Research interests
Natural Language Processing, Knowledge engineering, knowledge management, Data mining, Data Analytics, Information retrieval, Health Informatics

Professional memberships
Elected senior member, Association for Computing Machinery (ACM)
Elected senior member, Institute of Electrical and Electronics Engineers (IEEE)
IEEE Computer Society
IEEE Technical Committee on Intelligent Informatics
Web Intelligence Consortium (WIC)

Industry affiliations
Executive Secretary, Web Intelligence Consortium
Managing Editor, Web Intelligence Journal
Editor-in-Chief, IEEE Intelligent Informatics Bulletin
Editorial Board member, Scalable Information Systems
Editorial Board member, Computers and Education: Arti ficial Intelligence, Elsevier

Currently teaching courses/programs
MSC8001 Research Project I (2017 - present)
MSC8002 Research Project II (2017 - present)
MSC8003 Industry Based Research Practice I (2016 - present)
MSC8004 Industry Based Research Practice II (2016 - present)
CSC8600 Advanced ICT Professional Project (2017 – present)
CSC3600 ICT Professional Project (2013 – present)
CSC1401 Foundation Programming (2011-2017)
CSC1402 Foundation Computing (2011 – 2016)

Teaching experience(Tertiary)
16 Years

Administrative responsibilities
Discipline Team Leader (Computing), 2021-present
Program Director, Master of Data Science (2020-2021)
Program Director, Postgraduate Programs (Master of Science, Master of Computing, Master of Computing Technology), School of Sciences (2016-2019)

Research most recent
1. Xiaohua Wu, Lin Li, and Xiaohui Tao, Towards the Quantitative Interpretability Analysis of Citizens Happiness Prediction. Accepted by the 31st International Joint Conference on Artificial Intelligence (IJCAI-ECAI), July 23-29, 2022, Messe Wien, Vienna, Austria [CORE A*]

2. Ru Wang, Lin Li, Xiaohui Tao, Peipei Wang, and Peiyu Liu. Contrastive and attentive graph learning for multi-view clustering. Information Processing and Management, 2022 (in press). [Q1]

3. Chee Keong Wee, Xujuan Zhou, Raj Gururanjan, Xiaohui Tao, Nathen Wee, and Prabal Barua. Automated Triaging Medical Referral for Otorhinolaryngology using Data Mining and Machine Learning Techniques. IEEE Access, 2022. [DOI: 10.1109/ACCESS.2022.3168980][Q1]

4. Matthew Squires, Xiaohui Tao, Soman Elangovan, Raj Gururajan, Xujuan Zhou, and U Rajendra Acharya. A Novel Genetic Algorithm Based System for the Scheduling of Medical Treatments, Expert Systems With Applications. Expert Systems with Applications, Volume 195, 1 June 2022, 116464. [https://doi.org/10.1016/j.eswa.2021.116464][Q1]

5. Thuan Pham, Xiaohui Tao, Ji Zhang, Jianming Yong, Yuefeng Li, and Haoran Xie. Graph-based Multi-label Disease Prediction Model Learning from Medical Data and Domain Knowledge. Knowledge-Based Systems, Volume 235, 10 January 2022, 107662. [https://doi.org/10.1016/j.knosys.2021.107662][Q1]

6. Xieling Chen, Gary Cheng, Fu Lee Wang, Xiaohui Tao, Haoran Xie and Lingling Xu. Machine and cognitive intelligence for human health: systematic review. Brain Informatics, volume 9, Article number: 5 (2022) [https://doi.org/10.1186/s40708-022-00153-9][Q1]

7. Wang Gao, Lin Li, Xiaohui Tao, Jing Zhou, Jun Tao. Identifying informative tweets during a pandemic via a topic-aware neural language model. World Wide Web, 1–16, 16 Mar 2022. [doi: 10.1007/s11280-022-01034-1][ERA CORE A]

8. Hongzhi Kuai, Xiaohui Tao, and Ning Zhong. Web Intelligence meets Brain Informatics: towards the Future of Artificial Intelligence in the Connected World, World Wide Web, Springer, 2022. [doi: 10.1007/s11280-022-01030-5][ERA CORE A]

9. Ru Wang, Lin Li, Peipei Wang, Xiaohui Tao and Peiyu Liu. Deep boundary-aware clustering by jointly optimizing unsupervised representation learning. Multimedia Tools and Applications, 2022. [https://doi.org/10.1007/s11042-021-11597-2][Q1]

See more on: https://eprints.usq.edu.au/cgi/search/simple?screen=Search&order=&q_merge=ALL&q=xiaohui+tao&_action_search=Search


Research most notable
1. Xiaohui Tao, Yuefeng Li, and Ning Zhong. A Personalized Ontology Model for Web Information Gathering. IEEE Transactions on Knowledge and Data Engineering, Sept 02, 2010. IEEE computer Society Digital Library. IEEE Computer Society, [doi:10.1109/TKDE.2010.145] [Scopus citation: 86, Google Scholar: 168, accessed on 1 May 2022]

2. Xujuan Zhou, Xiaohui Tao, Jianming Yong, and Zhenyu Yang. Sentiment Analysis on Tweets for Social Events. In Proceedings of the 17th IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 557-562, 2013. [Scopus citation: 70, Google Scholar: 130, accessed on 1 May 2022]

3. Huizhi Liang, Yue Xu, Yuefeng Li, Richi Nayak, and Xiaohui Tao. Connecting users and items with weighted tags for personalised item recommendations. In Proceedings of the 21st ACM Conference on Hypertext and Hypermedia (Hypertext 2010), pages 51-60, 2010. [Scopus citation: 69, Google Scholar: 105, accessed on 1 May 2022]

4. Moloud Abdar, Mariam Zomorodi-Moghadam, Xujuan Zhou, Raj Gururajan, Xiaohui Tao, Prabal D Barua and Rashmi Gururajan, A new nested ensemble technique for automated diagnosis of breast cancer, Pattern Recognition Letters, Elsevier, Volume 132, page 123-131, April 2020 [Scopus citation: 56, Google Scholar: 96, accessed on 1 May 2022]

5. Ji Zhang, Raid Luaibi Lafta, Xiaohui Tao, Yan Li, Fulong Chen, Yonglong Luo, and Xiaodong Zhu. Coupling a Fast Fourier Transformation with a Machine Learning Ensemble Model to Support Recommendations for Heart Disease Patients in a Telehealth Environment, In IEEE Access, vol. 5, pp. 10674-10685, (2017). [Scopus citation: 53, Google Scholar: 62, accessed on 1 May 2022]


Publications in ePrints

Squires, Matthew and Tao, XiaohuiORCID: https://orcid.org/0000-0002-0020-077X and Elangovan, Soman and Gururajan, RajORCID: https://orcid.org/0000-0002-5919-0174 and Zhou, Xujuan and Acharya, Udyavara Rajendra (2022) A novel genetic algorithm based system for the scheduling of medical treatments. Expert Systems With Applications, 195:116464. pp. 1-12. ISSN 0957-4174

Shaik, Thanveer ORCID: https://orcid.org/0000-0002-9730-665X and Tao, XiaohuiORCID: https://orcid.org/0000-0002-0020-077X and Li, YanORCID: https://orcid.org/0000-0002-4694-4926 and Dann, ChristopherORCID: https://orcid.org/0000-0001-7477-0305 and McDonald, Jacquie and Redmond, PetreaORCID: https://orcid.org/0000-0001-9674-1206 and Galligan, LindaORCID: https://orcid.org/0000-0001-8156-8690 (2022) A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis. IEEE Access, 10. pp. 56720-56739.

Wee, Chee Keong and Zhou, Xujuan and Gururajan, RajORCID: https://orcid.org/0000-0002-5919-0174 and Tao, XiaohuiORCID: https://orcid.org/0000-0002-0020-077X and Wee, Nathan (2022) Adaptive Fault Resolution for Database Replication Systems. In: 17th International Conference on Advanced Data Mining and Applications (ADMA 2021), 2 Feb - 4 Feb 2022, Sydney, Australia.

Wee, Chee Keong and Zhou, XuJuan and Gururajan, RajORCID: https://orcid.org/0000-0002-5919-0174 and Tao, XiaohuiORCID: https://orcid.org/0000-0002-0020-077X and Chen, Jennifer and Gururajan, Rashmi and Wee, Nathan and Barua, Prabal DattaORCID: https://orcid.org/0000-0001-5117-8333 (2022) Automated Triaging Medical Referral for Otorhinolaryngology Using Data Mining and Machine Learning Techniques. IEEE Access, 10. pp. 44531-44548.

Li, Lin and Zhao, Lingyun and Nai, Peiran and Tao, XiaohuiORCID: https://orcid.org/0000-0002-0020-077X (2022) Charge prediction modeling with interpretation enhancement driven by double-layer criminal system. World Wide Web, 25 (1). pp. 381-400. ISSN 1386-145X

View full listing in ePrints

Research supervisor in the area of:

  • Expert Systems ( 080105 )
  • Pattern Recognition and Data Mining ( 080109 )
  • Natural Language Processing ( 080107 )
  • Natural Language Processing ( 460208 )
  • Artificial Intelligence ( 460200 )
  • Data Mining And Knowledge Discovery ( 460502 )
  • Data Management And Data Science ( 460500 )
  • Recommender Systems ( 460510 )
  • Information Retrieval And Web Search ( 460508 )
  • Semi- And Unsupervised Learning ( 461106 )
  • Knowledge Representation And Reasoning ( 460206 )
  • Deep Learning ( 461103 )
  • Context Learning ( 461102 )
  • Machine Learning ( 461100 )
  • Reinforcement Learning ( 461105 )
  • Neural Networks ( 461104 )


Research topics