Dr Sen Wang is an ARC DECRA Senior Research Fellow and Senior Lecturer in computer science and data science at the School of Information Technology and Electrical Engineering at UQ. He is also a CI on several health data analytics research grants. Sen has an interest in ICU data and has clinical collaborations with RBWH and Children’s Hospital. Dr Wang received his PhD degree in 2014 and his research interest includes various topics on Feature Selection, Semi-supervised Learning, Deep Learning, Pattern Recognition, Data Mining, and Health Informatics. Since 2010, Dr Wang has published 80+ academic papers in top conferences and journals. Most were published in internationally renowned journals and conferences in the fields of data science, data mining, and machine learning, such as Algorithmica, TNNLS, TMC, TKDE, TCYB, TMM, WWWJ, Signal Processing, ACM TOMM, ACM MM, IJCAI, AAAI, SDM, CIKM, CVPR, ICCV, ICDM, ISWC, ECML-PKDD, PAKDD, ICONIP, ICPADS, and WISE, all CORE A/A* journals and conferences.
Journal Article: A multi-level neural network for implicit causality detection in web texts
Liang, Shining, Zuo, Wanli, Shi, Zhenkun, Wang, Sen, Wang, Junhu and Zuo, Xianglin (2022). A multi-level neural network for implicit causality detection in web texts. Neurocomputing, 481, 121-132. doi: 10.1016/j.neucom.2022.01.076
Journal Article: Information resilience: the nexus of responsible and agile approaches to information use
Sadiq, Shazia, Aryani, Amir, Demartini, Gianluca, Hua, Wen, Indulska, Marta, Burton-Jones, Andrew, Khosravi, Hassan, Benavides-Prado, Diana, Sellis, Timos, Someh, Ida, Vaithianathan, Rhema, Wang, Sen and Zhou, Xiaofang (2022). Information resilience: the nexus of responsible and agile approaches to information use. The VLDB Journal. doi: 10.1007/s00778-021-00720-2
Book Chapter: InDISP: An Interpretable Model for Dynamic Illness Severity Prediction
Ma, Xinyu, Wang, Meng, Liu, Xing, Yang, Yifan, Zheng, Yefeng and Wang, Sen (2022). InDISP: An Interpretable Model for Dynamic Illness Severity Prediction. Database Systems for Advanced Applications. (pp. 631-638) Cham: Springer International Publishing. doi: 10.1007/978-3-031-00126-0_46
ARC Training Centre for Information Resilience
(2021–2026) ARC Industrial Transformation Training Centres
Towards Explainable Multi-source Multivariate Time-series Analysis
(2020–2022) ARC Discovery Early Career Researcher Award
Collaborative Lab of Health Informatics with Neusoft
(2019–2022) Neusoft Research ot Intelligent Healthcare Technology, Co Ltd
Towards Explainable Multi-source Multivariate Time-series Analysis
Doctor Philosophy
Towards Explainable Multi-source Multivariate Time-series Analysis
Doctor Philosophy
Towards Explainable Multi-source Multivariate Time-series Analysis
Doctor Philosophy
InDISP: An Interpretable Model for Dynamic Illness Severity Prediction
Ma, Xinyu, Wang, Meng, Liu, Xing, Yang, Yifan, Zheng, Yefeng and Wang, Sen (2022). InDISP: An Interpretable Model for Dynamic Illness Severity Prediction. Database Systems for Advanced Applications. (pp. 631-638) Cham: Springer International Publishing. doi: 10.1007/978-3-031-00126-0_46
A multi-level neural network for implicit causality detection in web texts
Liang, Shining, Zuo, Wanli, Shi, Zhenkun, Wang, Sen, Wang, Junhu and Zuo, Xianglin (2022). A multi-level neural network for implicit causality detection in web texts. Neurocomputing, 481, 121-132. doi: 10.1016/j.neucom.2022.01.076
Information resilience: the nexus of responsible and agile approaches to information use
Sadiq, Shazia, Aryani, Amir, Demartini, Gianluca, Hua, Wen, Indulska, Marta, Burton-Jones, Andrew, Khosravi, Hassan, Benavides-Prado, Diana, Sellis, Timos, Someh, Ida, Vaithianathan, Rhema, Wang, Sen and Zhou, Xiaofang (2022). Information resilience: the nexus of responsible and agile approaches to information use. The VLDB Journal. doi: 10.1007/s00778-021-00720-2
Deep dynamic imputation of clinical time series for mortality prediction
Shi, Zhenkun, Wang, Sen, Yue, Lin, Pang, Lixin, Zuo, Xianglin, Zuo, Wanli and Li, Xue (2021). Deep dynamic imputation of clinical time series for mortality prediction. Information Sciences, 579, 607-622. doi: 10.1016/j.ins.2021.08.016
Scalable estimator for multi-task gaussian graphical models based in an IoT network
Wang, Beilun, Zhang, Jiaqi, Zhang, Yan, Wang, Meng and Wang, Sen (2021). Scalable estimator for multi-task gaussian graphical models based in an IoT network. ACM Transactions on Sensor Networks, 17 (3) 3432312. doi: 10.1145/3432312
Hu, Mingwei, Tan, Qiyang, Knibbe, Ruth, Wang, Sen, Li, Xue, Wu, Tianqi, Jarin, Sams and Zhang, Ming-Xing (2021). Prediction of mechanical properties of wrought aluminium alloys using feature engineering assisted machine learning approach. Metallurgical and Materials Transactions A: Physical Metallurgy and Materials Science, 52 (7), 2873-2884. doi: 10.1007/s11661-021-06279-5
Explaining similarity for SPARQL queries
Wang, Meng, Chen, Kefei, Xiao, Gang, Zhang, Xinyue, Chen, Hongxu and Wang, Sen (2021). Explaining similarity for SPARQL queries. World Wide Web, 24 (5), 1813-1835. doi: 10.1007/s11280-021-00886-3
Yue, Lin, Shen, Hao, Wang, Sen, Boots, Robert, Long, Guodong, Chen, Weitong and Zhao, Xiaowei (2021). Exploring BCI control in smart environments: intention recognition via EEG representation enhancement learning. ACM Transactions on Knowledge Discovery from Data, 15 (5) 3450449, 1-20. doi: 10.1145/3450449
Editorial for application-driven knowledge acquisition
Li, Xue, Wang, Sen and Li, Bohan (2020). Editorial for application-driven knowledge acquisition. World Wide Web, 23 (5), 2649-2651. doi: 10.1007/s11280-020-00827-6
Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition
Zhang, Dalin, Yao, Lina, Chen, Kaixuan, Wang, Sen, Chang, Xiaojun and Liu, Yunhao (2020). Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition. IEEE Transactions on Cybernetics, 50 (7) 8698218, 3033-3044. doi: 10.1109/TCYB.2019.2905157
A Graph-Based Hierarchical Attention Model for Movement Intention Detection from EEG Signals
Zhang, Dalin, Yao, Lina, Chen, Kaixuan, Wang, Sen, Haghighi, Pari Delir and Sullivan, Caley (2019). A Graph-Based Hierarchical Attention Model for Movement Intention Detection from EEG Signals. IEEE Transactions On Neural Systems and Rehabilitation Engineering, 27 (11) 8847648, 2247-2253. doi: 10.1109/TNSRE.2019.2943362
Compressive representation for device-free activity recognition with passive RFID signal strength
Yao, Lina, Sheng, Quan Z., Li, Xue, Gu, Tao, Tan, Mingkui, Wang, Xianzhi, Wang, Sen and Ruan, Wenjie (2018). Compressive representation for device-free activity recognition with passive RFID signal strength. IEEE Transactions On Mobile Computing, 17 (2) 7938705, 293-306. doi: 10.1109/TMC.2017.2706282
Answering why-not questions on semantic multimedia queries
Wang, Meng, Chen, Weitong, Wang, Sen, Liu, Jun, Li, Xue and Stantic, Bela (2017). Answering why-not questions on semantic multimedia queries. Multimedia Tools and Applications, 77 (3), 3405-3429. doi: 10.1007/s11042-017-5151-6
A multiview learning framework with a linear computational cost
Xue, Xiaowei, Nie, Feiping, Li, Zhihui, Wang, Sen, Li, Xue and Yao, Min (2017). A multiview learning framework with a linear computational cost. IEEE Transactions on Cybernetics, 48 (8), 2416-2425. doi: 10.1109/TCYB.2017.2739423
Collaborative text categorization via exploiting sparse coefficients
Yao, Lina, Sheng, Quan Z., Wang, Xianzhi, Wang, Shengrui, Li, Xue and Wang, Sen (2017). Collaborative text categorization via exploiting sparse coefficients. World Wide Web: internet and web information systems, 21 (2), 1-22. doi: 10.1007/s11280-017-0460-2
Learning multiple diagnosis codes for ICU patients with local disease correlation mining
Wang, Sen, Li, Xue, Chang, Xiaojun, Yao, Lina, Sheng, Quan Z. and Long, Guodong (2017). Learning multiple diagnosis codes for ICU patients with local disease correlation mining. ACM Transactions on Knowledge Discovery from Data, 11 (3) 31, 1-21. doi: 10.1145/3003729
Diagnosis code assignment using sparsity-based disease correlation embedding
Wang, Sen, Chang, Xiaojun, Li, Xue, Long, Guodong, Yao, Lina and Sheng, Quan Z. (2016). Diagnosis code assignment using sparsity-based disease correlation embedding. IEEE Transactions on Knowledge and Data Engineering, 28 (12), 3191-3202. doi: 10.1109/TKDE.2016.2605687
Compound rank-k projections for bilinear analysis
Chang, Xiaojun, Nie, Feiping, Wang, Sen, Yang, Yi, Zhou, Xiaofang and Zhang, Chengqi (2016). Compound rank-k projections for bilinear analysis. IEEE Transactions on Neural Networks and Learning Systems, 27 (7) 7161356, 1502-1513. doi: 10.1109/TNNLS.2015.2441735
Multi-task support vector machines for feature selection with shared knowledge discovery
Wang, Sen, Chang, Xiaojun, Li, Xue, Sheng, Quan Z. and Chen, Weitong (2016). Multi-task support vector machines for feature selection with shared knowledge discovery. Signal Processing, 120, 746-753. doi: 10.1016/j.sigpro.2014.12.012
Multi-label classification via learning a unified object-label graph with sparse representation
Yao, Lina, Sheng, Quan Z., Ngu, Anne H.H., Gao, Byron J., Li, Xue and Wang, Sen (2015). Multi-label classification via learning a unified object-label graph with sparse representation. World Wide Web, 19 (6), 1-25. doi: 10.1007/s11280-015-0376-7
Compact representation for large-scale unconstrained video analysis
Wang, Sen, Pan, Pingbo, Long, Guodong, Chen, Weitong, Li, Xue and Sheng, Quan Z. (2015). Compact representation for large-scale unconstrained video analysis. World Wide Web, 19 (2), 231-246. doi: 10.1007/s11280-015-0354-0
Graph-based clustering and ranking for diversified image search
Yan, Yan, Liu, Gaowen, Wang, Sen, Zhang, Jian and Zheng, Kai (2014). Graph-based clustering and ranking for diversified image search. Multimedia Systems, 23 (1), 41-52. doi: 10.1007/s00530-014-0419-4
Structured streaming skeleton: a new feature for online human gesture recognition
Zhao, Xin, Li, Xue, Pang, Chaoyi, Sheng, Quan Z., Wang, Sen and Ye, Mao (2014). Structured streaming skeleton: a new feature for online human gesture recognition. ACM Transactions on Multimedia Computing, Communications and Applications, 11 (Supp. 1s) 22, 22:1-22:18. doi: 10.1145/2648583
Semi-supervised multiple feature analysis for action recognition
Wang, Sen, Ma, Zhigang, Yang, Yi, Li, Xue, Pang, Chaoyi and Hauptmann, Alexander G. (2014). Semi-supervised multiple feature analysis for action recognition. IEEE Transactions on Multimedia, 16 (2) 6675840, 289-298. doi: 10.1109/TMM.2013.2293060
Human action recognition based on semi-supervised discriminant analysis with global constraint
Zhao, Xin, Li, Xue, Pang, Chaoyi and Wang, Sen (2013). Human action recognition based on semi-supervised discriminant analysis with global constraint. Neurocomputing, 105, 45-50. doi: 10.1016/j.neucom.2012.04.038
Computing Unrestricted Synopses Under Maximum Error Bound
Pang, Chaoyi, Zhang, Qing, Zhou, Xiaofang, Hansen, David, Wang, Sen and Maeder, Anthony (2013). Computing Unrestricted Synopses Under Maximum Error Bound. Algorithmica, 65 (1), 1-42. doi: 10.1007/s00453-011-9571-9
CausalRec: causal inference for visual debiasing in visually-aware recommendation
Qiu, Ruihong, Wang, Sen, Chen, Zhi, Yin, Hongzhi and Huang, Zi (2021). CausalRec: causal inference for visual debiasing in visually-aware recommendation. MM '21: ACM Multimedia Conference, Virtual, 20-24 October 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3474085.3475266
Mitigating Generation Shifts for Generalized Zero-Shot Learning
Chen, Zhi, Luo, Yadan, Wang, Sen, Qiu, Ruihong, Li, Jingjing and Huang, Zi (2021). Mitigating Generation Shifts for Generalized Zero-Shot Learning. MM '21: ACM Multimedia Conference, Online, 20 - 24 October 2021. Washington, DC United States: Association for Computing Machinery. doi: 10.1145/3474085.3475258
Semantics disentangling for generalized zero-shot learning
Chen, Zhi, Luo, Yadan, Qiu, Ruihong, Wang, Sen, Huang, Zi, Li, Jingjing and Zhang, Zheng (2021). Semantics disentangling for generalized zero-shot learning. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/iccv48922.2021.00859
Self-supervised adversarial distribution regularization for medication recommendation
Wang, Yanda, Chen, Weitong, PI, Dechang, Yue, Lin, Wang, Sen and Xu, Miao (2021). Self-supervised adversarial distribution regularization for medication recommendation. Thirtieth International Joint Conference on Artificial Intelligence, Montreal, Canada, 19-27 August 2021. California, United States: International Joint Conferences on Artificial Intelligence Organization. doi: 10.24963/ijcai.2021/431
ZSTAD: Zero-Shot Temporal Activity Detection
Zhang, Lingling, Chang, Xiaojun, Liu, Jun, Luo, Minnan, Wang, Sen, Ge, Zongyuan and Hauptmann, Alexander (2020). ZSTAD: Zero-Shot Temporal Activity Detection. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA United States, 13-19 June 2020. Piscataway, NJ United States: IEEE. doi: 10.1109/CVPR42600.2020.00096
Collective protection: Preventing sensitive inferences via integrative transformation
Zhang, Dalin, Yao, Lina, Chen, Kaixuan, Long, Guodong and Wang, Sen (2019). Collective protection: Preventing sensitive inferences via integrative transformation. 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 8-11 November 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2019.00197
Learning attentional temporal cues of brainwaves with spatial embedding for motion intent detection
Zhang, Dalin, Chen, Kaixuan, Jian, Debao, Yao, Lina, Wang, Sen and Li, Po (2019). Learning attentional temporal cues of brainwaves with spatial embedding for motion intent detection. 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 8-11 November 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2019.00189
Learning to hash for efficient search over incomplete knowledge graphs
Wang, Meng, Shen, Haomin, Wang, Sen, Yao, Lina, Jiang, Yinlin, Qi, Guilin and Chen, Yang (2019). Learning to hash for efficient search over incomplete knowledge graphs. 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 8-11 November 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2019.00174
Temporal self-attention network for medical concept embedding
Peng, Xueping, Long, Guodong, Shen, Tao, Wang, Sen, Jiang, Jing and Blumenstein, Michael (2019). Temporal self-attention network for medical concept embedding. 19th IEEE International Conference on Data Mining (ICDM), Beijing, China, 8-11 November 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2019.00060
Detecting suicidal ideation with data protection in online communities
Ji, Shaoxiong, Long, Guodong, Pan, Shirui, Zhu, Tianqing, Jiang, Jing and Wang, Sen (2019). Detecting suicidal ideation with data protection in online communities. DASFAA 2019: Database Systems for Advanced Applications , Chiang Mai, Thailand, 22-25 April, 2019. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-18590-9_17
EEG-based motion intention recognition via multi-task RNNs
Chen, Weitong, Wang, Sen, Zhang, Xiang, Yao, Lina, Yue, Lin, Qian, Buyue and Li, Xue (2018). EEG-based motion intention recognition via multi-task RNNs. 2018 SIAM International Conference on Data Mining, SDM 2018, San Diego, CA, United States, 3-5 May 2018. Society for Industrial and Applied Mathematics Publications. doi: 10.1137/1.9781611975321.32
PDD graph: bridging electronic medical records and biomedical knowledge graphs via entity linking
Wang, Meng, Zhang, Jiaheng, Liu, Jun, Hu, Wei, Wang, Sen, Li, Xue and Liu, Wenqiang (2017). PDD graph: bridging electronic medical records and biomedical knowledge graphs via entity linking. The Semantic Web – ISWC 2017: 16th International Semantic Web Conference Vienna, Austria, October 21–25, 2017 Proceedings, Part II, Vienna, Austria, 21-25 October 2017. Cham, Switzerland: Springer Nature. doi: 10.1007/978-3-319-68204-4_23
Uncovering locally discriminative structure for feature analysis
Wang, Sen, Nie, Feiping, Chang, Xiaojun, Li, Xue, Sheng, Quan Z. and Yao, Lina (2017). Uncovering locally discriminative structure for feature analysis. 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016, Riva del Garda, Italy, 19 - 23 September 2016. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-46128-1_18
Classification based on compressive multivariate time series
Utomo, Chandra, Li, Xue and Wang, Sen (2016). Classification based on compressive multivariate time series. 27th Australasian Database Conference on Databases Theory and Applications, ADC 2016, Sydney Australia, 28-29 September 2016. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-46922-5_16
Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing data
Yao, Lina, Sheng, Quan Z., Li, Xue, Wang, Sen, Gu, Tao, Ruan, Wenjie and Zou, Wan (2016). Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing data. 15th IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, United States, 14-17 November 2015. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDM.2015.102
Learning from less for better: semi-supervised activity recognition via shared structure discovery
Yao, Lina, Nie, Feiping, Sheng, Quan Z., Gu, Tao, Li, Xue and Wang, Sen (2016). Learning from less for better: semi-supervised activity recognition via shared structure discovery. 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016, Heidelberg, Germany, 12-16 September 2016. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2971648.2971701
Yao, Lina, Sheng, Quan Z., Ruan, Wenjie, Li, Xue, Wang, Sen and Yang, Zhi (2016). Unobtrusive posture recognition via online learning of multi-dimensional RFID received signal strength. 2015 IEEE 21st International Conference on Parallel and Distributed Systems, ICPADS 2015, Melbourne, Victoria, Australia, 14- 17 December 2015. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPADS.2015.23
Unsupervised feature analysis with class margin optimization
Wang, Sen, Nie, Feiping, Chang, Xiaojun, Yao, Lina, Li, Xue and Sheng, Quan Z. (2015). Unsupervised feature analysis with class margin optimization. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Porto, Portugal, 7-11 September 2015. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-23528-8_24
Mining personal health index from annual geriatric medical examinations
Chen, Ling, Li, Xue, Wang, Sen, Hu, Hsiao-Yun, Huang, Nicole, Sheng, Quan Z. and Sharaf, Mohamed (2014). Mining personal health index from annual geriatric medical examinations. 2014 IEEE International Conference on Data Mining, Shenzhen, China, 14-17 December 2014. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDM.2014.32
Semi-supervised feature analysis for multimedia annotation by mining label correlation
Chang, Xiaojun, Shen, Haoquan, Wang, Sen, Liu, Jiajun and Li, Xue (2014). Semi-supervised feature analysis for multimedia annotation by mining label correlation. 18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2014, Tainan, Taiwan, 13 - 16 May 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-06605-9_7
Effective approaches in human action recognition
Li, Xue, Sheng, Quan Z., Pang, Chaoyi, Zhao, Xin and Wang, Sen (2013). Effective approaches in human action recognition. 2013 International Conference on Advanced Computer Science and Information Systems (ICACSIS), Bali, Indonesia, 28-29 September 2013. Piscataway, NJ, United States: IEEE Computer Society. doi: 10.1109/ICACSIS.2013.6761544
Fall detection in multi-camera surveillance videos: experimentations and observations
Wang, Sen, Xu, Zhongwen, Yang, Yi, Li, Xue, Pang, Chaoyi and Haumptmann, Alexander G. (2013). Fall detection in multi-camera surveillance videos: experimentations and observations. 1st ACM International Workshop on Multimedia Indexing and Information Retrieval for Heathcare (MIIRH 2013), Barcelona, Spain, 22 October 2013. New York, United States: ACM. doi: 10.1145/2505323.2505331
Online action recognition by template matching
Zhao, Xin, Wang, Sen, Li, Xue and Zhang, Hao Lan (2013). Online action recognition by template matching. 2nd International Conference on Health Information Science, HIS 2013, London, United Kingdom, 25-27 March 2013. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-37899-7_25
Action recognition by exploring data distribution and feature correlation
Wang, Sen, Yang, Yi, Ma, Zhigang, Li, Xue, Pang, Chaoyi and Hauptmann, Alexander G. (2012). Action recognition by exploring data distribution and feature correlation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, United States, 16-21 June 2012. Washington, DC, United States: I E E E Computer Society. doi: 10.1109/CVPR.2012.6247823
On the prediction of re-tweeting activities in social networks – a report on WISE 2012 Challenge
Unankard, Sayan, Chen, Ling, Li, Peng, Wang, Sen, Huang, Zi, Sharaf, Mohamed A. and Li, Xue (2012). On the prediction of re-tweeting activities in social networks – a report on WISE 2012 Challenge. 13th International Conference on Web Information Systems Engineering (WISE 2012), Paphos, Cyprus, 28 - 30 November 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-35063-4_61
Effective Algorithms for Human Action Recognition
Wang, Sen (2014). Effective Algorithms for Human Action Recognition. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland.
ARC Training Centre for Information Resilience
(2021–2026) ARC Industrial Transformation Training Centres
Towards Explainable Multi-source Multivariate Time-series Analysis
(2020–2022) ARC Discovery Early Career Researcher Award
Collaborative Lab of Health Informatics with Neusoft
(2019–2022) Neusoft Research ot Intelligent Healthcare Technology, Co Ltd
Towards Explainable Multi-source Multivariate Time-series Analysis
Doctor Philosophy — Principal Advisor
Other advisors:
Towards Explainable Multi-source Multivariate Time-series Analysis
Doctor Philosophy — Principal Advisor
Other advisors:
Towards Explainable Multi-source Multivariate Time-series Analysis
Doctor Philosophy — Principal Advisor
Other advisors:
Towards Explainable Multi-source Multivariate Time-series Analysis
Doctor Philosophy — Principal Advisor
Other advisors:
Towards Explainable Multi-source Multivariate Time-series Analysis
Doctor Philosophy — Principal Advisor
Other advisors:
Explainable Learning of Multivariate Time-Series
Doctor Philosophy — Principal Advisor
Other advisors:
Application of Deep Machine Learning to Model New Perovskite-Type Materials for High Temperature Solid Oxide Cells (SOC)
Doctor Philosophy — Associate Advisor
Other advisors:
Joint Feature Learning for Recommender System
Doctor Philosophy — Associate Advisor
Other advisors:
Deep understanding of large scale image data
Doctor Philosophy — Associate Advisor
Other advisors: