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 an ARC EC Industry Fellow, a 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 applications in medical data. Dr. Chen is known for his extensive collaborative efforts with professionals in academia, industry, government, and professional bodies, and his research has been supported by various 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	Researcher	Australian Institute for Machine Learning (AIML)
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

Journals

Year	Citation
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. DOI
2023	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. DOI Scopus1
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	Qiu, Y., Lin, F., Chen, W., & Xu, M. (2023). Pre-training in Medical Data: A Survey. Machine Intelligence Research, 20(2), 147-179. DOI Scopus7 WoS5
2023	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), 8628-8637. DOI Scopus2 WoS1
2023	Li, B., Dai, T., Chen, W., Song, X., Zang, Y., Huang, Z., . . . Cai, K. (2023). T-PORP: A Trusted Parallel Route Planning Model on Dynamic Road Networks. IEEE Transactions on Intelligent Transportation Systems, 24(1), 1238-1250. DOI Scopus3 WoS2
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 WoS16
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	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 Scopus71 WoS38
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 WoS8
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	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 WoS14
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 WoS27
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 WoS3
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 Scopus8 WoS6
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 WoS181
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. DOI
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 Scopus46 WoS42
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.
-	Zhuang, H., Zhang, W., Chen, W., Yang, J., & Sheng, Q. Z. (n.d.). Improving Faithfulness and Factuality with Contrastive Learning in Explainable Recommendation. ACM Transactions on Intelligent Systems and Technology. DOI

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
2024	Guo, L., Zhang, W. E., Chen, W., Yang, N., Nguyen, Q., & Vo, T. D. (2024). Oyster Mushroom Growth Stage Identification: An Exploration of Computer Vision Technologies. In T. Liu, L. Yue, G. Webb, & D. Wang (Eds.), Lecture Notes in Computer Science (Vol. 14471 LNAI, pp. 67-78). SPRINGER-VERLAG SINGAPORE PTE LTD. DOI
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
2021	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. DOI

Conference Papers

Year	Citation
2024	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 - IEEE International Conference on Data Mining, ICDM (pp. 508-517). PEOPLES R CHINA, Shanghai: IEEE COMPUTER SOC. DOI
2024	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 - IEEE International Conference on Knowledge Graph, ICKG 2023 (pp. 117-125). Online: IEEE. DOI
2023	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). ACM. DOI
2023	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. DOI
2023	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 Scopus1
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). Online: Springer International Publishing. 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). Online: Springer, Cham. DOI
2022	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 (pp. 86-100). Online: Springer, Cham. DOI WoS1
2022	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 WoS1
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). Online: Springer. DOI
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).
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, CIKM 2021 (pp. 1048-1057). Univ Queensland, ELECTR NETWORK: ASSOC COMPUTING MACHINERY. DOI
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, CIKM 2021 (pp. 2020-2029). Univ Queensland, ELECTR NETWORK: ASSOC COMPUTING MACHINERY. DOI WoS2
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). Switzerland AG: Springer, Cham. DOI WoS4
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 WoS7
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 WoS9
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 WoS2
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 WoS4
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 Database Systems for Advanced Applications Vol. 11447 (pp. 384-400). Handle, Switzerland: Springer, Cham. DOI WoS5
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 Database Systems for Advanced Applications (DASFAA) Vol. 11447 (pp. 53-69). Handel, Switzerland: Springer, Cham. DOI WoS5
2019	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 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 International Conference on Database Systems for Advanced Applications Vol. 11448 (pp. 378-382). Chiang Mai, THAILAND: Springer, Cham. DOI WoS2
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. Vol. 11446 (pp. 659-675). New York, NY, USA: Springer, Cham. DOI WoS15
2018	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 WoS81
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 WoS22
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 WoS15
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 Advanced Data Mining and Applications 13th International Conference, ADMA 2017, Proceedings Vol. 10604 LNAI (pp. 655-667). Switzerland: Springer, Cham. 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).

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.

Grants and Funding ($1,441,333.00)

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)
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

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.

Current Higher Degree by Research Supervision (University of Adelaide)

Date	Role	Research Topic	Program	Degree Type	Student Load	Student Name
2024	Co-Supervisor	Large Language Models for Adaptive Microservice Composition and Orchestration	Master of Philosophy	Master	Full Time	Mr Jeffrey Chan
2024	Principal Supervisor	Cutting-Edge Artificial Intelligence in Smart and Digital Agriculture	Doctor of Philosophy	Doctorate	Full Time	Ms Lipin Guo
2024	Principal Supervisor	Artificial intelligence-based diagnosis using multimodal information	Doctor of Philosophy	Doctorate	Full Time	Mr Liangwei Zheng
2023	Co-Supervisor	Leveraging Knowledge-aware Methodologies for Multi-document Summarization	Doctor of Philosophy	Doctorate	Full Time	Miss Yutong Qu
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	Learning from imperfect and evolving data	Doctor of Philosophy	Doctorate	Full Time	Mr Chang Dong
2023	Co-Supervisor	Federated learning for data product generation	Doctor of Philosophy	Doctorate	Full Time	Mr Ali Shakeri
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