
Dr Weitong Chen
Senior 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 an ARC EC Industry Fellow, a senior lecturer at the University of Adelaide (UoA) and a researcher at the Australian Institute for Machine Learning (AIML), having previously served as an Associate Lecturer and Post-Doc Research Fellow at the University of Queensland. He earned his PhD from the University of Queensland in 2020, after completing both his Master's and Bachelor's degrees at the University of Queensland and at Griffith University respectively. His research primarily focuses on machine learning, with a special interest in its application to medical data. Dr. Chen is known for his extensive collaborative efforts with professionals in academia, industry, government, and professional bodies, and various internal and external grants have supported his research.
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.
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Appointments
Date Position Institution name 2024 - ongoing Senior Lecturer The University of Adelaide 2022 - ongoing Researcher Australian Institute for Machine Learning (AIML) 2022 - 2024 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
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Journals
Year Citation 2025 Zhao, Y., Zhang, M., Zhang, C., Chen, W., Ye, N., & Xu, M. (2025). A boosting framework for positive-unlabeled learning. Statistics and Computing, 35(1), 22 pages.
Scopus12025 Han, K., Koay, A. M. Y., Ko, R. K. L., Chen, W., & Xu, M. (2025). Adapting to the stream: an instance-attention GNN method for irregular multivariate time series data. Frontiers of Computer Science, 19(8), 13 pages.
Scopus12025 Asundi, S. H., Plummer, M. P., Sundararajan, K., O’Callaghan, G., Kar, P., Jukes, A., . . . Webber, T. (2025). Cumulative Radiation Exposure Post Aneurysmal Subarachnoid Haemorrhage. Clinical Neuroradiology, 6 pages.
2025 Sun, Y., Yue, L., Liu, Y., Chen, W., & Sun, Z. (2025). The Application of the SubChain Salp Swarm Algorithm in the Less-Than-Truckload Freight Matching Problem. APPLIED SCIENCES-BASEL, 15(8), 14 pages.
2025 Sun, Y., Yue, L., Jin, H., Chen, W., & Sun, Z. (2025). A Modeling Method for Emergency Rescue Center Siting Based on the Variable Butterfly Optimization Algorithm. Electronics (Switzerland), 14(8), 18 pages.
2025 Wang, X., Figueredo, G., Li, R., Zhang, W. E., Chen, W., & Chen, X. (2025). A survey of deep-learning-based radiology report generation using multimodal inputs. Medical Image Analysis, 103, 26 pages.
2024 Zhang, C., Chen, W., Zhang, W., & Xu, M. (2024). Mitigating the Impact of Inaccurate Feedback in Dynamic Learning-to-Rank: A Study of Overlooked Interesting Items. ACM Transactions on Intelligent Systems and Technology, 16(1), 5-1-5-26.
2024 Duncker, D., & Linz, D. (2024). eCardiology in cardiac electrophysiology. Herzschrittmachertherapie Und Elektrophysiologie, 35(2), 95-96.
Scopus2 Europe PMC22024 Kabiri, S., Tavakkoli, E., Navarro, D. A., Degryse, F., Grimison, C., Higgins, C. P., . . . McLaughlin, M. J. (2024). The complex effect of dissolved organic carbon on desorption of per- and poly-fluoroalkyl substances from soil under alkaline conditions. Environmental Pollution, 356, 124234-1-124234-9.
Scopus6 Europe PMC22024 Hamza, M. A., Evans, J. D., Andersson, G. G., Metha, G. F., & Shearer, C. J. (2024). Ultrathin Ru-CdIn₂S₄ nanosheets for simultaneous photocatalytic green hydrogen production and selective oxidation of furfuryl alcohol to furfural. Chemical Engineering Journal, 493, 152603-1-152603-12.
Scopus152024 Zhuang, H., Zhang, W., Chen, W., Yang, J., & Sheng, Q. Z. (2024). Improving Faithfulness and Factuality with Contrastive Learning in Explainable Recommendation. ACM Transactions on Intelligent Systems and Technology, 16(1), 9-1-9-23.
2024 Xu, Y., Li, T., Yang, Y., Chen, W., & Yue, L. (2024). An adaptive category-aware recommender based on dual knowledge graphs. Information Processing and Management, 61(3), 14 pages.
Scopus102023 Chen, W., Zhang, W. E., & Yue, L. (2023). Death comes but why: A multi-task memory-fused prediction for accurate and explainable illness severity in ICUs. World Wide Web, 26(6), 4025-4045.
Scopus42023 Qiu, Y., Lin, F., Chen, W., & Xu, M. (2023). Pre-training in Medical Data: A Survey. Machine Intelligence Research, 20(2), 147-179.
Scopus17 WoS52023 Li, B., Huang, Z., Chen, T. W., Dai, T., Zang, Y., Xie, W., . . . Cai, K. (2023). MSN: Mapless Short-Range Navigation Based on Time Critical Deep Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems, 24(8), 10 pages.
Scopus14 WoS12022 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, 24(1), 1-13.
Scopus10 WoS22022 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.
Scopus22021 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.
Scopus28 WoS162021 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.
WoS22021 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.
Scopus99 WoS382021 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.
Scopus18 WoS82021 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.
WoS12020 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.
WoS142020 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.
Scopus63 WoS272020 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.
WoS32020 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.
Scopus8 WoS62020 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.
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.
Scopus417 WoS1812019 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 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.
WoS32017 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.
Scopus432017 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.
Scopus22017 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.
Scopus47 WoS422016 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.
Scopus4 WoS22015 Li, X., Zhu, G., Guo, X., & Chen, W. (2015). Spatial and Temporal Word Spectrum of Social Media. -
Books
Year Citation 2022 Chen, W., Yao, L., Taotao, C., Pan, S., & Shen, T. (Eds.) (2022). Advanced Data Mining and Applications
18th International Conference, ADMA 2022, Brisbane, QLD, Australia, November 28-30, 2022, Proceedings, Part II (Vol. 13726 LNAI). Springer International Publishing AG. -
Book Chapters
Year Citation 2023 Yue, L., Zhang, Y., Zhao, X., Zhang, Z., & Chen, W. (2023). Improving Motor Imagery Intention Recognition via Local Relation Networks. In B. Li, L. Yue, C. Tao, X. Han, D. Calvanese, & T. Amagasa (Eds.), Web and Big Data (Vol. 13421 LNCS, pp. 345-356). Switzerland: Springer Nature Switzerland.
DOI Scopus12021 Liu, B., Zuccon, G., Hua, W., & Chen, W. (2021). Diagnosis Ranking with Knowledge Graph Convolutional Networks. In D. Hiemstra, M. -F. Moens, J. Mothe, R. Perego, M. Potthast, & F. Sebastiani (Eds.), Advances in Information Retrieval (Vol. 12656, pp. 359-374). New York, NY, USA: Springer, Cham.
DOI2020 Arrieta, M., Colas, I., Macaulay, M., Waugh, R., & Ramsay, L. (2020). A Modular Tray Growth System for Barley. In Methods in Molecular Biology (Vol. 2061, pp. 367-379). Springer New York.
DOI Scopus4 Europe PMC4 -
Conference Papers
Year Citation 2025 Han, K., Koay, A., Ko, R. K. L., Chen, W., & Xu, M. (2025). Mining Irregular Time Series Data with Noisy Labels: A Risk Estimation Approach. In T. Chen, Y. Cao, Q. V. H. Nguyen, & T. T. Nguyen (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 15449 LNCS (pp. 293-307). AUSTRALIA, Gold Coast: SPRINGER-VERLAG SINGAPORE PTE LTD.
DOI2025 Shakeri, A., Zhang, W. E., Beheshti, A., Chen, W., Yang, J., & Yang, L. (2025). FedDPG: An Adaptive Yet Efficient Prompt-Tuning Approach in Federated Learning Settings. In Lecture Notes in Computer Science (pp. 40-51). Sydney, NSW, Australia: Springer Nature Singapore.
DOI2024 George Dong, C., David Li, Z., Nathan Zheng, L., Chen, W., & Emma Zhang, W. (2024). Boosting Certificate Robustness for Time Series Classification with Efficient Self-Ensemble. In International Conference on Information and Knowledge Management, Proceedings (pp. 477-486). ID, Boise: ASSOC COMPUTING MACHINERY.
DOI2024 Qu, Y., Yang, J., Zhang, W. E., Chen, W., & Yu, H. Q. (2024). Data-Product Catalogues: Envisioning with Knowledge-aware Natural Language Processing. In Proceedings of the IEEE International Conference on Web Services, ICWS Vol. 33 (pp. 45-54). Shenzhen, China: IEEE.
DOI2024 Shakeri, A., Chen, P., Shu, Y., Yang, L., Zhang, W. E., & Chen, W. (2024). Transforming Data Product Generation through Federated Learning: An Exploration of FL Applications in Data Ecosystems. In Proceedings of the IEEE International Conference on Web Services, ICWS Vol. 27 (pp. 84-91). Shenzhen, China: IEEE.
DOI2024 Tan, X., Wang, Z., Wang, M., Shen, D., Chen, W., & Wang, B. (2024). Large Covariance Estimation from Streaming Data with Knowledge-Based Sketch Matrix. In M. Onizuka, J. G. Lee, Y. Tong, C. Xiao, Y. Ishikawa, S. Amer-Yahia, . . . K. Lu (Eds.), DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, DASFAA 2024, PT 5 Vol. 14854 (pp. 493-502). JAPAN, Gifu: SPRINGER-VERLAG SINGAPORE PTE LTD.
DOI2024 Zhuang, H., Zhang, W. E., Xie, L., Chen, W., Yang, J., & Sheng, Q. Z. (2024). Automatic, Meta and Human Evaluation for Multimodal Summarization with Multimodal Output. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024 Vol. 1 (pp. 7761-7783). Online: Association for Computational Linguistics (ACL).
DOI Scopus12024 Zheng, L. N., Li, Z., Dong, C. G., Zhang, W. E., Yue, L., Xu, M., . . . Chen, W. (2024). Irregularity-Informed Time Series Analysis: Adaptive Modelling of Spatial and Temporal Dynamics. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (pp. 3405-3414). Boise ID USA: ACM.
DOI Scopus12024 Zheng, L. N., Dong, C. G., Zhang, W. E., Chen, X., Yue, L., & Chen, W. (2024). Devil in the Tail: A Multi-Modal Framework for Drug-Drug Interaction Prediction in Long Tail Distinction. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (pp. 3395-3404). Boise, Idaho: ACM.
DOI2024 Zhuang, H., Emma Zhang, W., Yang, J., Chen, W., & Sheng, Q. Z. (2024). Not All Negatives are Equally Negative: Soft Contrastive Learning for Unsupervised Sentence Representations. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (pp. 3591-3601). Boise, Idaho: ACM.
DOI2024 Qiu, Y., Chen, W., & Xu, M. (2024). A Progressive Sampling Method for Dual-Node Imbalanced Learning with Restricted Data Access. In G. Chen, L. Khan, X. Gao, M. Qiu, W. Pedrycz, & X. Wu (Eds.), Proceedings of the 23rd IEEE International Conference on Data Mining (ICDM 2023) (pp. 508-517). Shanghai, China: IEEE.
DOI Scopus12024 Dong, C. G., Zheng, L. N., Chen, W., Zhang, W. E., & Yue, L. (2024). SWAP: Exploiting Second-Ranked Logits for Adversarial Attacks on Time Series. In Proceedings of the IEEE International Conference on Knowledge Graph (ICKG 2023) (pp. 117-125). Online: IEEE.
DOI Scopus62023 Shen, S., Zhang, M., Chen, W., Bialkowski, A., & Xu, M. (2023). Words Can Be Confusing: Stereotype Bias Removal in Text Classification at the Word Level. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13938 LNCS (pp. 99-111). Online: Springer Nature Switzerland.
DOI2023 Guo, L., Zhang, W. E., Chen, W., Yang, N., Nguyen, Q., & Vo, T. D. (2023). Oyster Mushroom Growth Stage Identification: An Exploration of Computer Vision Technologies. In Proceedings of the 36th Australasian Joint Conference on Artificial Intelligence Vol. 14471 (pp. 67-78). Brisbane, QLD: Springer Nature Singapore.
DOI2023 Wen, Z., Zhang, W. E., Guo, L., & Chen, W. (2023). Demo Abstract: Navigating Indoors: A Cost-effective Drone-based Solution. In SenSys 2023 - Proceedings of the 21st ACM Conference on Embedded Networked Sensors Systems (pp. 496-497). TURKEY, Bahcesehir Univ, Istanbul: ASSOC COMPUTING MACHINERY.
DOI2023 Shen, S., Xu, M., Yue, L., Boots, R., & Chen, W. (2023). Death Comes But Why: An Interpretable Illness Severity Predictions in ICU. In B. Li, L. Yue, C. Tao, X. Han, D. Calvanese, & T. Amagasa (Eds.), Proceedings International Joint Conference APWeb-WAIM 2022 Vol. 13421 LNCS (pp. 60-75). Nanjing, China: Springer Nature Switzerland.
DOI Scopus42022 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). Online: Springer International Publishing.
DOI Scopus12022 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 Vol. 13281 LNAI (pp. 199-210). Online: Springer, Cham.
DOI Scopus22022 Qiu, Y., Chen, W., Yue, L., Xu, M., & Zhu, B. (2022). STCT: Spatial-Temporal Conv-Transformer Network for Cardiac Arrhythmias Recognition. In International Conference on Advanced Data Mining and Applications Vol. 13087 LNAI (pp. 86-100). Online: Springer, Cham.
DOI Scopus8 WoS12022 Han, K., Chen, W., & Xu, M. (2022). Investigating Active Positive-Unlabeled Learning with Deep Networks. In Australasian Joint Conference on Artificial Intelligence Vol. 13151 (pp. 607-618). Online: Springer, Cham.
DOI WoS12022 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). Online: Springer.
DOI Scopus12021 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). Virtual, Online: International Joint Conferences on Artificial Intelligen.
DOI Scopus332021 Su, G., Chen, W., & Xu, M. (2021). Positive-Unlabeled Learning from Imbalanced Data.. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (pp. 2995-3001). Montreal Canada: International Joint Conferences on Artificial Intelligence. 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). Virtual, Online: Association for Computing Machinery.
DOI Scopus42021 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). Virtual, Online: Association for Computing Machinery.
DOI Scopus11 WoS22021 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 LNCS (pp. 1-12). Switzerland AG: Springer, Cham.
DOI Scopus8 WoS42019 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 WoS72019 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 Scopus8 WoS92019 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 WoS22019 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 WoS12019 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 Scopus7 WoS42019 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 Database Systems for Advanced Applications Vol. 11447 (pp. 384-400). Handle, Switzerland: Springer, Cham.
DOI WoS52019 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 Database Systems for Advanced Applications (DASFAA) Vol. 11447 (pp. 53-69). Handel, Switzerland: Springer, Cham.
DOI Scopus6 WoS52019 Wang, Y., Chen, W., Li, B., & Boots, R. (2019). Learning fine-grained patient similarity with dynamic bayesian network embedded RNNs. In Database Systems for Advanced Applications Vol. 11446 (pp. 587-603). Handel, Switzerland: Springer, Cham.
DOI WoS32019 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 International Conference on Database Systems for Advanced Applications Vol. 11448 (pp. 378-382). Chiang Mai, THAILAND: Springer, Cham.
DOI WoS22019 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. Vol. 11446 (pp. 659-675). New York, NY, USA: Springer, Cham.
DOI WoS152018 Zhang, D., Yao, L., Zhang, X., Wang, S., Chen, W., Boots, R., & Benatallah, B. (2018). Cascade and parallel convolutional recurrent neural networks on EEG-based intention recognition for brain computer interface. In Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence Vol. 32 (pp. 1703-1710). Palo Alto, California, USA: AAAI Press.
DOI WoS812018 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 WoS222018 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 SIAM International Conference on Data Mining Sdm 2018 (pp. 279-287). Society for Industrial and Applied Mathematics.
DOI Scopus832017 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 WoS152017 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 Advanced Data Mining and Applications 13th International Conference, ADMA 2017, Proceedings Vol. 10604 LNAI (pp. 655-667). Switzerland: Springer, Cham.
DOI Scopus42017 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 Scopus11 WoS102016 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). -
Conference Items
Year Citation 2018 Utomo, C. P., Li, X., & Chen, W. (2018). Treatment recommendation in critical care: A scalable and interpretable approach in partially observable health states. Poster session presented at the meeting of Proceedings of the International Conference on Information Systems - Bridging the Internet of People, Data, and Things, ICIS 2018. Illinois, USA: Association for Information Systems. -
Theses
Year Citation - Chen, W. (n.d.). Deep multi-task learning on time-series medical data. -
Preprint
Year Citation 2023 Dong, C. G., Zheng, L. N., Chen, W., Zhang, W. E., & Yue, L. (2023). SWAP: Exploiting Second-Ranked Logits for Adversarial Attacks on Time
Series.2023 Cooper, L., Xu, H., Polmear, J., Szeto, C., Pang, E. S., Gupta, M., . . . Good-Jacobson, K. (2023). Type I interferon dynamics determines memory B cell epigenetic identity in chronic viral infection.
DOI2022 Currenti, J., Qiao, L., Pai, R., Gupta, S., Khyriem, C., Wise, K., . . . Sharma, A. (2022). STOmics-GenX: CRISPR based approach to improve cell identity specific gene detection from spatially resolved transcriptomics.
DOI2022 Gruber, E., So, J., Lewis, A., Franich, R., Cole, R., Martelotto, L., . . . Kats, L. (2022). Inhibition of mutant IDH1 promotes cycling of acute myeloid leukemia stem cells.
DOI
Grants and Funding ($1,466,333.00)
- 2025 Global Partnership Engagement Fund 2025 - 2025 Education Knowledge Graph Construction, Embedding, and Application (UoA & TJU)
- ARC IE - ARC ECR Industry Fellowship 2024 - 2026 Future of Work: Achieving Efficiency and Productivity through Optimisation (ARC & SA PAthology)
- ARC LP - Principal Investigator 2024 - 2026 Advanced Data Analytics for Cost-effective Mushroom Cultivation (ARC & CLEVER MUSHROOMS PTY LTD; PIXELFORCE SYSTEMS PTY LTD; HOKKEN CO., LTD)
- ARC DP - Principal Investigator 2024 - 2026 Institutional Grants System icon Towards knowledge discovery from imperfect and evolving data (ARC)
- Research Small Equipment Support Scheme 2024 2024 -2024 Automated 3D Scaner for High-Resolution Mushroom Growth Monitoring and Data Collection
- UoA Sustainability FAME Strategy Grant 2023 - Investigator 2023 - Sustainable Warriors or Marketing Mirage? (UoA)
- UoA CMS Research Grants 2023 - 2023 (UoA)
- ANA Partnership Fund- Principal Investigator 2023 - 2023 AID-MI: Artificial Intelligence Based Diagnosis Using Multimodal Information For Cardiopulmonary Disease (UoA & UoN)
- UoA START-UP GRANT - Principal Investigator 2022 - 2024
- UQ AI-ECR Research Fund - Principal Investigator 2022 - 2022 Towards Positive Emotion: Artificial Intelligence-Based Expression Rephrasing (UQ)
- UQ Cyber Security Seed Fund - Principal Investigator 2022 - 2022 Collaborated Learning with Medical Data Making High-Stake Decision Without Information Leakage (UQ & RBWH)
- UQ AI Initiative - Investigator 2021 - 2022 AI Monitored ICU Illness Severity Prediction (UQ & RBWH)
- ITEE Research Support Fund - Principal Investigator 2021 - 2021 Multi-Task Memory-Fused RNNs for Explainable Illness Severity Prediction (UQ)
Awards & Achievements
- 2024 Best Student Paper Award, The Australasian Database Conference, Australia
- 2024 Emerging Researcher, The 20th International Conference on Advanced Data Mining and Applications, Australia
- 2024 Best Student Paper Runner-up Award, The 20th International Conference on Advanced Data Mining and Applications, Australia
- 2024 20th Anniversary Service Award, The 20th International Conference on Advanced Data Mining and Applications, Australia
- 2023 Early Career Research Excellence Award, The University of Adelaide, Australia
- 2023 Outstanding Service Award, The 36th Australasian Joint Conference on Artificial Intelligence, Australia
- 2022 Best Student Paper Award, APWEB-WAIM 2022, China
- 2022 Best Poster Award, The 34th Australasian Joint Conference on Artificial Intelligence, Australia
- 2021 Best Presentation Award, 17th International Conference on Advanced Data Mining and Applications, Australia
- 2021 Best Paper - Highly Commended Award, Australasian Computer Science Week Multiconference, New Zealand
- 2019 Best Student Paper Award, 15th International Conference on Advanced Data Mining and Applications, China
- 2018 Student Travel Grant, International Conference on Data Mining 2018 Singapore
- 2016 Outstanding Service Award, 12th International Conference on Advanced Data Mining and Applications, Australia
- 2014 Premier‘s Awards for Open Data, Australia
- 2014 1st Place, Microsoft Startup Q Award for Open Data, Australia
To be considered for a recommendation letter from me for graduate school applications, you must satisfy at least two of the following criteria:
- Achieved a grade exceeding 90% in my class.
- Completed your MSc project under my supervision with a High Distinction (HD) grade.
- Represented the University of Adelaide (UoA) in the world final of the ACM programming contest.
- Demonstrated strong preparation for graduate studies, such as contributing to a publication in a reputable conference or journal.
Please note:
- Writing a recommendation letter is a time-intensive process, so I ask that your request be made with due courtesy. Requests lacking politeness will not be acknowledged.
- Given the limited number of letters I can write annually, I may have to decline many requests. This decision is not personal. If I agree to consider your request, expect a 30-minute interview where I will assess your computer science knowledge through technical questions.
- I will only write recommendation letters for up to five graduate schools per student.
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2025 Co-Supervisor Exploring scientific literature for anomalous adsorption phenomena using natural language processing Master of Philosophy Master Full Time Mr Fengxu Yang 2025 Principal Supervisor Advanced Adaptive Learning Frameworks for Scalable and Efficient Continual Learning in Machine Learning Applications Doctor of Philosophy Doctorate Full Time Mr Zechao Sun 2025 Co-Supervisor Learning from imperfect and evolving data Master of Philosophy Master Full Time Mr Chang Dong 2024 Principal Supervisor Cutting-Edge Artificial Intelligence in Smart and Digital Agriculture Doctor of Philosophy Doctorate Full Time Ms Lipin Guo 2024 Co-Supervisor Large Language Models for Adaptive Microservice Composition and Orchestration Master of Philosophy Master Full Time Mr Jeffrey Chan 2024 Principal Supervisor Artificial intelligence-based diagnosis using multimodal information Doctor of Philosophy Doctorate Full Time Mr Liangwei Zheng 2024 Principal Supervisor Exploring Explainable AI in Pathological Diagnostics and Healthcare Doctor of Philosophy Doctorate Full Time Mr Wenhao Liang 2023 Principal Supervisor An efficient and robust deep learning framework for multi-scale feature fusion object detection Doctor of Philosophy Doctorate Full Time Mr Yibo Sun 2023 Co-Supervisor Can Active Learning and Federated Learning Help Sensitive Information Protection Master of Philosophy Master Full Time Mr Lishan Yang -
Past Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2023 - 2024 Co-Supervisor Deep Learning Based Multi-document Summarization 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 -
Mentoring
Date Topic Location Name 2025 - 2025 Guardians of the InfoSphere: A Multi-Modal Approach to Disinformation Detection in Large Language Models University of Maryland Jason Pittman
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