Weitong Chen

Dr Weitong Chen

Lecturer

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD - email supervisor to discuss availability.

Dr Tony Weitong Chen is a lecturer at the University of Adelaide (UoA). Before moving to UoA, Tony spent two years at the University of Queensland, serving as Associated Lecturer and Post-Doc Research Fellow. Tony received the PhD degree from the University of Queensland (Australia) in 2020, the Master degree from the University of Queensland, and the Bachelor degree from Griffith University. His current main research interests include Machine Learning and its applications to medical data. He has built strong collaboration links with experts in universities, industry, government and professional bodies. His research has been supported by several internal and external grants.

I am interested in topics in areas including time-series data analysis, semi-supervised learning, natural language processing, and Internet of Things applications.

My current research relates to two specific areas:

  • Mining Imbalanced and Annotation-Missing Health Data, and
  • Enhancing Trustworthy by Generalizing from a Few Examples.

  • Appointments
    Date Position Institution name
    2022 - ongoing Adjunct Research Fellow The university of Queensland
    2022 - ongoing lecturer The University of Adelaide
    2021 - 2022 Associated Lecturer The University of Queensland
    2020 - 2022 Postdoctoral Research Fellow The University of Queensland

  • Language Competencies
    Language Competency
    Chinese (Cantonese) Can read, write, speak, understand spoken and peer review
    Chinese (Mandarin) Can read, write, speak, understand spoken and peer review
    English Can read, write, speak, understand spoken and peer review

  • Education
    Date Institution name Country Title
    2017 - 2020 The University of Queensland Australia PhD
    2011 - 2022 The University of Queensland Australia Master of Computer Science
    2009 - 2022 Griffith University Australia Bachelor of Information System

  • Research Interests
    Information Systems Optimisation

  • Journals
    Year Citation
    2022 Li, B., Huang, Z., Chen, T. W., Dai, T., Zang, Y., Xie, W., . . . Cai, K. (2022). MSN: Mapless Short-Range Navigation Based on Time Critical Deep Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems, 10 pages.
    DOI
    2022 Li, B., Dai, T., Chen, W., Song, X., Zang, Y., Huang, Z., . . . Cai, K. (2022). : A Trusted Parallel Route Planning Model on Dynamic Road Networks. IEEE Transactions on Intelligent Transportation Systems, 1-13.
    DOI
    2022 Liu, A. C., Law, O. M. K., & Law, I. (2022). Healthcare.
    2022 Wang, Y., Chen, W., Pi, D., & Yue, L. (2022). Adaptive Multi-Hop Reading on Memory Neural Network with Selective Coverage Mechanism for Medication Recommendation. ACTA ELECTONICA SINICA, 50(4), 943.
    2021 Wang, Y., Chen, W., Pi, D., & Yue, L. (2021). Adversarially regularized medication recommendation model with multi-hop memory network. Knowledge and Information Systems, 63(1), 125-142.
    DOI WoS7
    2021 Li, B., Liang, R., Zhu, D., Chen, W., & Lin, Q. (2021). Blockchain-based trust management model for location privacy preserving in VANET. IEEE Transactions on Intelligent Transportation Systems, 22(6), 3765-3775.
    DOI Scopus20 WoS22
    2021 Zhang, Y., Li, B., Gao, H., Ji, Y., Yang, H., Wang, M., & Chen, W. (2021). Fine-Grained Evaluation of Knowledge Graph Embedding Model in Knowledge Enhancement Downstream Tasks. Big Data Research, 25, 9 pages.
    DOI WoS2
    2021 Yue, L., Shen, H., Wang, S., Boots, R., Long, G., Chen, W., & Zhao, X. (2021). Exploring BCI control in smart environments: intention recognition via EEG representation enhancement learning. ACM Transactions on Knowledge Discovery from Data (TKDD), 15(5), 1-20.
    DOI WoS7
    2021 Wang, M., Chen, W., Wang, S., Jiang, Y., Yao, L., & Qi, G. (2021). Efficient search over incomplete knowledge graphs in binarized embedding space. Future Generation Computer Systems, 123, 24-34.
    DOI WoS1
    2020 Yue, L., Tian, D., Chen, W., Han, X., & Yin, M. (2020). Deep learning for heterogeneous medical data analysis. World Wide Web, 23(5), 2715-2737.
    DOI WoS21
    2020 Wang, Y., Chen, W., Pi, D., & Boots, R. (2020). Graph augmented triplet architecture for fine-grained patient similarity. World Wide Web, 23(5), 2739-2752.
    DOI WoS2
    2020 Chen, W., Long, G., Yao, L., & Sheng, Q. Z. (2020). AMRNN: attended multi-task recurrent neural networks for dynamic illness severity prediction. World Wide Web, 23(5), 2753-2770.
    DOI WoS13
    2020 Cai, K., Yue, H., Li, B., Chen, W., & Huang, W. (2020). Combining Chrominance Features and Fast ICA for Noncontact Imaging Photoplethysmography. IEEE Access, 8, 50171-50179.
    DOI Scopus5 WoS4
    2020 Zhang, A., Li, B., Wang, W., Wan, S., & Chen, W. (2020). MII: a novel text classification model combining deep active learning with bert. Computers, Materials and Continua, 63(3), 1499-1514.
    DOI
    2019 Yue, L., Chen, W., Li, X., Zuo, W., & Yin, M. (2019). A survey of sentiment analysis in social media. Knowledge and Information Systems, 60(2), 617-663.
    DOI WoS141
    2019 Li, Y., Chen, W., Liu, D., Zhang, Z., Wu, S., & Liu, C. (2019). IFFLC: an integrated framework of feature learning and classification for multiple diagnosis codes assignment. Ieee Access, 7, 36810-36818.
    2019 Ma, J., Wen, J., Zhong, M., Chen, W., & Li, X. (2019). MMM: multi-source multi-net micro-video recommendation with clustered hidden item representation learning. Data Science and Engineering, 4(3), 240-253.
    2018 Utomo, C. P., Li, X., & Chen, W. (2018). Treatment recommendation in critical care: A scalable and interpretable approach in partially observable health states.
    2018 Wang, M., Chen, W., Wang, S., Liu, J., Li, X., & Stantic, B. (2018). Answering why-not questions on semantic multimedia queries. Multimedia Tools and Applications, 77(3), 3405-3429.
    DOI WoS3
    2017 Yang, Y., Xu, Y., Han, J., Wang, E., Chen, W., & Yue, L. (2017). Efficient traffic congestion estimation using multiple spatio-temporal properties. Neurocomputing, 267, 344-353.
    2017 Yue, L., Shi, Z., Han, J., Wang, S., Chen, W., & Zuo, W. (2017). Multi-factors based sentence ordering for cross-document fusion from multimodal content. Neurocomputing, 253, 6-14.
    2017 Zhang, D., Yao, L., Zhang, X., Wang, S., Chen, W., & Boots, R. (2017). EEG-based intention recognition from spatio-temporal representations via cascade and parallel convolutional recurrent neural networks. arXiv preprint arXiv:1708.06578, 1-8.
    2016 Wang, S., Chang, X., Li, X., Sheng, Q. Z., & Chen, W. (2016). Multi-task support vector machines for feature selection with shared knowledge discovery. Signal Processing, 120, 746-753.
    DOI Scopus42 WoS39
    2016 Wang, S., Pan, P., Long, G., Chen, W., Li, X., & Sheng, Q. Z. (2016). Compact representation for large-scale unconstrained video analysis. World Wide Web, 19(2), 231-246.
    DOI Scopus4 WoS2
    2015 Li, X., Zhu, G., Guo, X., & Chen, W. (2015). Spatial and Temporal Word Spectrum of Social Media.

  • Book Chapters
    Year Citation
    2021 Liu, B., Zuccon, G., Hua, W., & Chen, W. (2021). Diagnosis Ranking with Knowledge Graph Convolutional Networks. In Lecture Notes in Computer Science (Vol. 12656 LNCS, pp. 359-374). Springer International Publishing.
    DOI

  • Conference Papers
    Year Citation
    2022 Qiu, Y., Chen, W., Yue, L., Xu, M., & Zhu, B. (2022). STCT: Spatial-Temporal Conv-Transformer Network for Cardiac Arrhythmias Recognition. In B. Li, L. Yue, J. Jiang, W. Chen, X. Li, G. Long, . . . H. Yu (Eds.), ADVANCED DATA MINING AND APPLICATIONS, ADMA 2021, PT I Vol. 13087 (pp. 86-100). ELECTR NETWORK: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI
    2022 Han, K., Chen, W., & Xu, M. (2022). Investigating Active Positive-Unlabeled Learning with Deep Networks. In G. Long, X. Yu, & S. Wang (Eds.), AI 2021: ADVANCES IN ARTIFICIAL INTELLIGENCE Vol. 13151 (pp. 607-618). Univ Technol Sydney, ELECTR NETWORK: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI
    2022 Zhang, C., Zhang, Y., Mao, J., Chen, W., Yue, L., Bai, G., & Xu, M. (2022). Towards Better Generalization for Neural Network-Based SAT Solvers. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 199-210). Springer, Cham.
    2022 Tran, K. P., Chen, W., & Xu, M. (2022). Improving Traffic Load Prediction with Multi-modality: A Case Study of Brisbane. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13151 LNAI (pp. 254-266). Sydney, NSW, Australia: Springer.
    DOI
    2022 Shen, S., Chen, W., & Xu, M. (2022). What Leads to Arrhythmia: Active Causal Representation Learning of ECG Classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13728 LNAI (pp. 501-515). Springer International Publishing.
    DOI
    2021 Su, G., Chen, W., & Xu, M. (2021). Positive-Unlabeled Learning from Imbalanced Data.. In IJCAI (pp. 2995-3001).
    2021 Liu, C., Yang, Y., Yao, Z., Xu, Y., Chen, W., Yue, L., & Wu, H. (2021). Discovering Urban Functions of High-Definition Zoning with Continuous Human Traces. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management (pp. 1048-1057).
    2021 Wang, Y., Chen, W., Pi, D., Yue, L., Xu, M., & Li, X. (2021). Multi-hop Reading on Memory Neural Network with Selective Coverage for Medication Recommendation. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management (pp. 2020-2029).
    2021 Yue, L., Tian, D., Jiang, J., Yao, L., Chen, W., & Zhao, X. (2021). Intention Recognition from Spatio-Temporal Representation of EEG Signals. In M. Qiao, G. Vossen, S. Wang, & L. Li (Eds.), DATABASES THEORY AND APPLICATIONS (ADC 2021) Vol. 12610 (pp. 1-12). Otago Univ, ELECTR NETWORK: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI WoS4
    2021 Wang, Y., Chen, W., Pi, D., Yue, L., Wang, S., & Xu, M. (2021). Self-Supervised Adversarial Distribution Regularization for Medication Recommendation.. In IJCAI (pp. 3134-3140).
    2019 Ma, J., Wen, J., Zhong, M., Liu, L., Li, C., Chen, W., . . . Li, X. (2019). Dbrec: dual-bridging recommendation via discovering latent groups. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM '19) (pp. 1513-1522). New York, NY, USA: Association for Computing Machinery.
    DOI WoS3
    2019 Chen, W., Yue, L., Li, B., Wang, C., & Sheng, Q. Z. (2019). DAMTRNN: a delta attention-based multi-task RNN for intention recognition. In International Conference on Advanced Data Mining and Applications Vol. LNAI 11888 (pp. 373-388). Dalian, China: Springer, Cham.
    DOI WoS8
    2019 Ma, J., Zhong, M., Wen, J., Chen, W., Zhou, X., & Li, X. (2019). RecKGC: Integrating Recommendation with Knowledge Graph Completion. In J. Li, S. Wang, S. Qin, X. Li, & S. Wang (Eds.), International Conference on Advanced Data Mining and Applications Vol. 11888 (pp. 250-265). Switzerland: Springer, Cham.
    DOI WoS1
    2019 Zhang, Z., Chen, W., Liu, C., Kang, Y., Liu, F., Li, Y., & Wei, S. (2019). Robust feature selection based on fuzzy rough sets with representative sample. In J. Li, S. Qin, S. Wang, S. Wang, & X. Li (Eds.), International Conference on Advanced Data Mining and Applications Vol. 11888 (pp. 151-165). Switzerland: Springer, Cham.
    DOI WoS1
    2019 Shi, Z., Chen, W., Liang, S., Zuo, W., Yue, L., & Wang, S. (2019). Deep interpretable mortality model for intensive care unit risk prediction. In J. Li, S. Wang, S. Qin, X. Li, & S. Wang (Eds.), Advanced Data Mining and Applications. ADMA 2019. Vol. 11888 (pp. 617-631). Dalian, China: Springer, Cham.
    DOI WoS3
    2019 Ma, J., Wen, J., Zhong, M., Chen, W., Zhou, X., & Indulska, J. (2019). Multi-source Multi-net Micro-video Recommendation with Hidden Item Category Discovery. In G. Li, J. Yang, J. Gama, J. Natwichai, & Y. Tong (Eds.), DATABASE SYSTEMS FOR ADVANCED APPLICATIONS (DASFAA 2019), PT II Vol. 11447 (pp. 384-400). Chiang Mai, THAILAND: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI WoS4
    2019 Shi, Z., Zuo, W., Chen, W., Yue, L., Hao, Y., & Liang, S. (2019). DMMAM: Deep Multi-source Multi-task Attention Model for Intensive Care Unit Diagnosis. In G. Li, J. Yang, J. Gama, J. Natwichai, & Y. Tong (Eds.), DATABASE SYSTEMS FOR ADVANCED APPLICATIONS (DASFAA 2019), PT II Vol. 11447 (pp. 53-69). Chiang Mai, THAILAND: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI WoS3
    2019 Wang, Y., Chen, W., Li, B., & Boots, R. (2019). Learning Fine-Grained Patient Similarity with Dynamic Bayesian Network Embedded RNNs. In G. Li, J. Yang, J. Gama, J. Natwichai, & Y. Tong (Eds.), DATABASE SYSTEMS FOR ADVANCED APPLICATIONS (DASFAA 2019), PT I Vol. 11446 (pp. 587-603). Chiang Mai, THAILAND: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI WoS3
    2019 Xu, X., Huang, Z., Wu, J., Fu, Y., Luo, N., Chen, W., . . . Yin, M. (2019). Finding the Key Influences on the House Price by Finite Mixture Model Based on the Real Estate Data in Changchun. In G. Li, J. Yang, J. Gama, J. Natwichai, & Y. Tong (Eds.), DATABASE SYSTEMS FOR ADVANCED APPLICATIONS Vol. 11448 (pp. 378-382). Chiang Mai, THAILAND: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI
    2019 Wang, R., Wang, M., Liu, J., Chen, W., Cochez, M., & Decker, S. (2019). Leveraging Knowledge Graph Embeddings for Natural Language Question Answering. In G. Li, J. Yang, J. Gama, J. Natwichai, & Y. Tong (Eds.), DATABASE SYSTEMS FOR ADVANCED APPLICATIONS (DASFAA 2019), PT I Vol. 11446 (pp. 659-675). Chiang Mai, THAILAND: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI WoS11
    2018 Zhang, D., Yao, L., Zhang, X., Wang, S., Chen, W., & Boots, R. (2018). Cascade and Parallel Convolutional Recurrent Neural Networks on EEG-Based Intention Recognition for Brain Computer Interface. In THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE (pp. 1703-1710). New Orleans, LA: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
    WoS56
    2018 Chen, W., Wang, S., Long, G., Yao, L., Sheng, Q. Z., & Li, X. (2018). Dynamic illness severity prediction via multi-task RNNs for Intensive Care Unit. In Proceedings of the IEEE International Conference on Data Mining (ICDM 2018) (pp. 917-922). Piscataway, NJ, USA: IEEE.
    DOI WoS15
    2018 Chen, W., Wang, S., Zhang, X., Yao, L., Yue, L., Qian, B., & Li, X. (2018). EEG-based motion intention recognition via multi-task RNNs. In Proceedings of the 2018 SIAM International Conference on Data Mining (pp. 279-287). Society for Industrial and Applied Mathematics.
    2017 Chen, H., Yin, H., Li, X., Wang, M., Chen, W., & Chen, T. (2017). People opinion topic model: opinion based user clustering in social networks. In Proceedings of the 26th International Conference on World Wide Web Companion (WWW'17) (pp. 1353-1359). Perth, Australia: Association for Computing Machinery.
    DOI WoS12
    2017 Zheng, Y., Wei, B., Liu, J., Wang, M., Chen, W., Wu, B., & Chen, Y. (2017). Quality prediction of newly proposed questions in CQA by leveraging weakly supervised learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10604 LNAI (pp. 655-667). Springer International Publishing.
    DOI Scopus4
    2017 Shi, Z., Zuo, W., Chen, W., Yue, L., Han, J., & Feng, L. (2017). User relation prediction based on matrix factorization and hybrid particle swarm optimization. In Proceedings of the 26th International Conference on World Wide Web Companion (pp. 1335-1341). Perth, Australia: ACM Digital.
    DOI WoS10
    2016 Li, B., Zhang, C., Chen, W., Yang, Y., Feng, S., Zhang, Q., . . . Li, D. (2016). Dynamic reverse furthest neighbor querying algorithm of moving objects. In International Conference on Advanced Data Mining and Applications (pp. 266-279). Springer, Cham.
    2016 Xie, M., Yin, H., Wang, H., Xu, F., Chen, W., & Wang, S. (2016). Learning graph-based poi embedding for location-based recommendation. In Proceedings of the 25th ACM international on conference on information and knowledge management (pp. 15-24).

  • Theses
    Year Citation
    - Chen, W. (n.d.). Deep multi-task learning on time-series medical data.

  • Current Higher Degree by Research Supervision (University of Adelaide)
    Date Role Research Topic Program Degree Type Student Load Student Name
    2023 Co-Supervisor Summarising Articles with Deep Neural Networks Doctor of Philosophy Doctorate Full Time Ms Congbo Ma

  • Other Supervision Activities
    Date Role Research Topic Location Program Supervision Type Student Load Student Name
    2023 - ongoing External Supervisor Domain Adaptation in Causality Views The University of Queensland - Doctorate Full Time Shaofei Shen
    2022 - ongoing Principal Supervisor Deep learning methods for imbalanced medical multivariate time series data University of Queensland Computer Science Doctorate Full Time Yixuan qiu
    2022 - ongoing External Supervisor High-stakes Decision Making with Weakly Supervised Data The University of Queensland Computer Science Doctorate Full Time Yawen Zhao
    2022 - ongoing External Supervisor Distribution-aware Automatic Summary Generalisation from Multi-modal Medical Data The University of Queensland - Doctorate Full Time Hao Gong
    2022 - ongoing Principal Supervisor Fairness-aware Personal Medicine: From Disease Diagnosis to Treatment The University of Qeensland Computer Science Doctorate Full Time Chenhao Zhang
    2022 - ongoing External Supervisor Machine Learning for Cyber Security The University of Queensland Cyber Security Doctorate Full Time Kun Han
  • Position: Lecturer
  • Phone: 83130676
  • Email: weitong.chen@adelaide.edu.au
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor Level Four
  • Room: 4.45
  • Org Unit: Computer Science
Connect With Me
External Profiles