Assoc. Prof. Kewen Liao

Note that CS/IT is conference rigorously peer-reviewed and ranked discipline with 7% A*, 16% A, and 36% B venues (see CORE/ERA conference ranking). Journals were used to be ranked by CORE/ERA journal ranking (discontinued from 2022) with the latest update in 2020. Scopus ranks the journals by CiteScore/SJR/SNIP. In the following, selections of my top-10 publications are highlighted with their venue rankings at the time of publication. By convention, the indications of 'equal contribution', 'alphabetical order', 'corresponding author' etc. denoted in the paper were agreed between the authors to justify their equal or important contributions to the research work besides authorship ordering.

Top 10 Refereed Conference Papers

1. Townim Faisal Chowdhury, Kewen Liao, Minh Hieu Phan, Minh-Son To, Yutong Xie, Kevin Hung, David Ross, Anton van den Hengel, Johan W. Verjans, Zhibin Liao. CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation. To appear at the 41st IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR 2024), Seattle WA, USA, June 17-21, 2024. [CORE A*, CiteScore/SJR/SNIP-Median top 1%, 2nd author]
2. Longkun Guo^, Chaoqi Jia^, Kewen Liao^, Zhigang Lu^, and Minghui Xue^. Efficient Constrained k-Center Clustering with Background Knowledge. To appear at the 38th AAAI Conference on Artificial Intelligence (AAAI 2024), Vancouver, Canada, February 20-27, 2024. [CORE A*, ^: alphabetical co-1st author with equal contribution]
3. Lu Chen, Chengfei Liu, Rui Zhou, Kewen Liao, Jiajie Xu, and Jianxin Li. Densest Multipartite Subgraph Search in Heterogeneous Information Networks. To appear at the 50th International Conference on Very Large Databases (VLDB 2024), Guangzhou, China, August 25-29, 2024. [CORE A*]
4. Songjie Xie, Youlong Wu^, Kewen Liao^, Lu Chen, Chengfei Liu, Haifeng Shen, MingJian Tang, and Lu Sun. Fed-SC: One-Shot Federated Subspace Clustering over High-Dimensional Data. The 39th IEEE International Conference on Data Engineering (ICDE 2023), Anaheim, California, USA, April 3-7, 2023. [CORE A*, ^: co-corresponding author]
5. Hao Li, Jie Shao, Kewen Liao, and Mingjian Tang. Do Simpler Statistical Methods Perform Better in Multivariate Long Sequence Time-Series Forecasting? The 31st ACM International Conference on Information & Knowledge Management (CIKM 2022), Atlanta, Georgia, USA, October 17-21, 2022. [CORE A]
6. Haifeng Shen, Kewen Liao, Zhibin Liao, Job Doornberg, Maoying Qiao, Anton van den Hengel, Johan W. Verjans, Human-AI Interactive and Continuous Sensemaking: A Case Study of Image Classification using Scribble Attention Maps. ACM conference on Computer-Human Interaction (CHI 2021), Extended Abstracts, May 8-13, 2021, Yokohama, Japan. [CORE A*, 2nd author]
7. Lu Chen, Chengfei Liu, Kewen Liao, Jianxin Li, Rui Zhou. Contextual Community Search over Large Social Networks. The 35th IEEE International Conference on Data Engineering (ICDE 2019), Macau, China, 8-11 April 2019. [CORE A*]
8. Longkun Guo, Yunyun Deng^, Kewen Liao^, Qiang He, Timos Sellis and Zheshan Hu. A Fast Algorithm for Optimally Finding Partially Disjoint Shortest Paths. The 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), Stockholm, Sweden, July 13-19, 2018. [CORE A*, ^: co-2nd author with equal contribution]
9. Kewen Liao, Alistair Moffat, Matthias Petri and Anthony Wirth. A Cost Model for Long-Term Compressed Data Retention. The 10th ACM International Conference on Web Search and Data Mining (WSDM 2017), Cambridge UK, February 6-10, 2017. [CORE A*, 1st author]
10. Kewen Liao, Matthias Petri, Alistair Moffat and Anthony Wirth. Effective Construction of Relative Lempel-Ziv Dictionaries. The 25th World Wide Web Conference (WWW 2016), Montreal, Canada, April 11 - 15, 2016. [CORE A*, 1st author]

Top 10 Refereed Journal Articles

1. Federico Montori^, Kewen Liao^, Matteo De Giosa, Prem Prakash Jayaraman, Luciano Bononi, Timos Sellis, and Dimitrios Georgakopoulos. A Metadata-Assisted Cascading Ensemble Classification Framework for Automatic Annotation of Open IoT Data. IEEE Internet of Things Journal, Volume: 10, Issue: 15, 2023. [CiteScore/SJR/SNIP-Median top 3%, ^: co-1st author with equal contribution]
2. Aylwin Sim, Ryan Timmins, Josh Ruddym, Haifeng Shen, Kewen Liao, Nirav Maniar, Jack Hickey, Morgan Williams, and David Opar. Hamstring strain injury risk factors in Australian Football change over the course of the season. Medicine & Science in Sports & Exercise, 156(2):297-306, 2023. [CiteScore/SJR/SNIP-Median top 3%]
3. Chaoqi Jia, Longkun Guo^, Kewen Liao^, and Zhigang Lu^, Efficient algorithm for the k-means problem with must-link and cannot-link constraints. Tsinghua Science and Technology, Volume: 28, Issue: 6, 2023. [CiteScore/SJR/SNIP-Median top 7%, ^: alphabetical co-senior author]
4. Longkun Guo^, Kewen Liao^, Di Xiao^, and Pei Yao^. Submodular Maximization over Data Streams with Differential Privacy Noise. Theoretical Computer Science, Vol 886: 113625, 2023. [CORE A, top-3 journal in computing theory by h5-index, ^: alphabetical co-1st author with equal contribution]
5. Zhibin Liao^, Kewen Liao^, Haifeng Shen, Marouska F. van Boxel, Jasper Prijs, Ruurd L. Jaarsma, Job Doornberg, Anton van den Hengel, and Johan W. Verjans. CNN Attention Guidance for Improved Orthopedics Radiographic Fracture Classification. IEEE Journal of Biomedical and Health Informatics, Volume: 26 Issue: 7, pp 3139 - 3150, 2022. [CORE A*, CiteScore/SJR/SNIP-Median top 6%, ^: co-1st author with equal contribution]
6. Abdur Rahim Mohammad Forkan, Yong-Bin Kang, Prem Prakash Jayaraman, Kewen Liao, Rohit Kaul, Graham Morgan, Rajiv Ranjan, and Samir Sinha. CorrDetector: A Framework for Structural Corrosion Detection from Drone Images using Ensemble Deep Learning. Expert Systems with Applications, Volume 193: 116461 (2022). [CORE B, CiteScore/SJR/SNIP-Median top 4%]
7. Theodor Wyeld, Peerumporn Jiranantanagorn, Haifeng Shen, Kewen Liao, Tomasz Bednarz, Understanding the Effects of Real-time Sentiment Analysis and Morale Visualisation in Backchannel Systems. International Journal of Human-Computer Studies, Volume 145, January 2021, 102524. [CORE A, CiteScore/SJR/SNIP-Median top 5%]
8. Oshini Goonetilleke, Danai Koutra, Kewen Liao, and Timos Sellis. On Effective and Efficient Graph Edge Labeling. Distributed and Parallel Databases, Vol 37, No 1, pp 5-38, 2019. [ERA A]
9. Kewen Liao, Hong Shen and Longkun Guo. Improved approximation algorithms for constrained fault-tolerant resource allocation. Theoretical Computer Science, Vol 590, pp 118-128, 2015. [ERA A, 1st author]
10. Kewen Liao and Hong Shen. LP-Based Approximation Algorithms for Reliable Resource Allocation. The (Oxford) Computer Journal, Vol 57, No 1, pp 154-164, 2014. [ERA A*, 1st author]

Patent and book chapter

Research Interest and Topics

A/Prof Liao's research interest broadly includes theory (algorithm/model effectiveness, efficiency, and complexity bounds) and applications (human-centred models, systems, services, and tools) of Algorithms, Data Science, AI and Machine Learning. He is currently working on the following fundamental and interesting research topics such as approximation and learning-based algorithms for NP-hard combinatorial optimisation problems, constrained clustering and coverage optimisation, graph mining and community search, time series classification and forecasting, IoT sensor data classification and anomaly detection, explainable and multi-modal computer vision, human-in-the-loop deep learning for image recognition, text compression, classification, topic modelling, and sentiment analysis, and privacy-preserved federated learning. A/Prof Liao is actively seeking interested and high-calibrate PhD or MPhil students to join HilstLab. Full stipend scholarships and tuition waivers are available through ACU Higher Degree Research Hub. 

Clustering and coverage optimisation:

• Constrained k-center and k-means clustering
• Facility location and k-median clustering
• Offline and online target/disk/sensor coverage 
• Streaming submodular maximisation 

Graph optimisation:

• Social network community search 
• Densest subgraph mining 
• Constrained disjoint shortest paths search
• Learning-based graph combinatorial optimization

Time series and spatial-temporal streams analytics:

• Deep learning for time series forecasting 
• Deep multimodal sensor datastream classification 
• Machine learning for time series anomaly detection
• Machine learning for IoT sensor datastream classification and annotation 

Computer vision:

• Interpretable multimodal deep computer vision 
• Multimodal human activity recognition
• Weakly supervised semantic segmentation 
• Deep learning for image-based anomaly detection

NLP and text analytics:

• Sentiment and behaviour analysis and classification 
• Short and long text clustering and topic modelling

Cybersecurity:

• Blockchain-enabled secure data sharing 
• Privacy-preserved federated learning

Human-centred models, systems, services, and tools:

• Human-in-the-loop deep learning models
• Trusted IoT sensor marketplace systems
• Similarity search of context-aware web services
• Manual and generative data annotation and labelling tools

Besides, Dr Liao's research has been proudly supported by:

Selected Professional Services

Member, Association for Computing Machinery (ACM)

Member, Institute of Electrical and Electronics Engineers (IEEE)