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.
- 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
My 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.
Career
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 |
Research Interests
Publications
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 Article has an altmetric score of 2 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 Article has an altmetric score of 3 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 Article has an altmetric score of 12 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 Applications18th 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
Grants and Funding ($1,441,333.00)
- ARC IE - ARC ECR Industry Fellowship2024 - 2026Future of Work: Achieving Efficiency and Productivity through Optimisation (ARC & SA PAthology)
- ARC LP - Principal Investigator2024 - 2026Advanced Data Analytics for Cost-effective Mushroom Cultivation (ARC & CLEVER MUSHROOMS PTY LTD; PIXELFORCE SYSTEMS PTY LTD; HOKKEN CO., LTD)
- ARC DP - Principal Investigator 2024 - 2026Institutional 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 Grants2023 - 2023 (UoA)
- ANA Partnership Fund- Principal Investigator2023 - 2023AID-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 - 2022Towards Positive Emotion: Artificial Intelligence-Based Expression Rephrasing (UQ)
- UQ Cyber Security Seed Fund - Principal Investigator 2022 - 2022Collaborated Learning with Medical Data Making High-Stake Decision Without Information Leakage (UQ & RBWH)
- UQ AI Initiative - Investigator 2021 - 2022AI 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
- 2023Early 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
- 2021Best 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
- 2018Student 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
Teaching
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.
Supervision
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 |
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 |
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 |
Discover more from DT Lab
Subscribe to get the latest posts to your email.