Professor Zi (Helen) Huang

Big Media Intelligence (BMI) Research Group
Data Science Discipline School of Electrical Engineering & Computer Science The University of Queensland
huang@itee.uq.edu.au +61 7 336 53239
Overview Publications Grants Awards Activities Team

Overview

Helen Huang is a Professor and the Discipline Leader for Data Science in the School of EECS at The University of Queensland. She received her BSc degree from Department of Computer Science, Tsinghua University, China, and her PhD in Computer Science from School of EECS, The University of Queensland in 2001 and 2007 respectively. Helen's research interests mainly include multimedia indexing and search, computer vision, recommender systems, social data analysis and knowledge discovery. She has published 200+ papers in prestigious venues, and has served as an Associate Editor for The VLDB Journal, ACM Transactions on Information Systems (TOIS), IEEE Transactions on Multimedia (TMM), Pattern Recognition Journal, etc and also a member of the VLDB Endowment Board of Trustees. Helen has been elevated to IEEE Fellow for her contributions to multi-modal data management and recognised as an ACM Distinguished Member for her contributions to multimedia computing research.

Helen Huang has received 2016 Chris Wallace Award from Computing Research and Education (CORE) Australasia for a notable breakthrough or a contribution of particular significance in Computer Science, and Women in Technology (WiT) Infotech Research Award 2014, Queensland. She was also a recipient of the Excellence in Higher Degree by Research Supervision Award, University of Queensland, 2018.

Research Interest

  • Big Database Management: Data quality; Data linkage and fusion; Indexing structures; Query processing; Dimensionality reduction; spatio-temporal data management
  • Machine Learning: Few-shot Learning; Zero-shot Learning; Domain adaptation; Adversarial learning; Graph learning
  • Multimedia Search: Visual content (image and videos) understanding and analysis; Multimedia indexing and retrieval; Ranking and recommendation; Visual question answering;
  • Information systems: Privacy-aware information retrieval; cross-modal retrieval; Heterogeneous data fusion; Knowledge distillation
  • Social Media Analytics: Event detection and monitoring; User behaviour modelling and prediction; Social interactions analysis; Web data mining

For Prospective Students

We are always looking for highly motivated Ph.D students. The research topics include multimedia, computer vision, spatial&temporal database, and knowledge discovery. UQ ranks among the world’s top universities, as measured by several key independent rankings, including the U.S. News Best Global Universities Rankings 2023 (36), the Performance Ranking of Scientific Papers for World Universities 2023 (37), CWTS Leiden Ranking 2023 (35), QS World University Rankings 2024 (43), Academic Ranking of World Universities 2023 (51), and Times Higher Education World University Rankings 2024 (70).

Honours and Master thesis project students from UQ are also welcome.

Selected Journals

  1. J. Yu, H. Yin, X. Xia, T. Chen, J. Li, and Z. Huang. "Self-Supervised Learning for Recommender Systems: A Survey". IEEE Trans. Knowl. Data Eng. 36(1): 335-355 (2024)
  2. M. Zhao, X. Qi, Z. Hu, L. Li, Y. Zhang, Z. Huang, and X. Yu. "Calligraphy Font Generation via Explicitly Modeling Location-Aware Glyph Component Deformations". IEEE Trans. Multim. 26: 5939-5950 (2024)
  3. J. Li, Y. Bin, Y. Ma, Y. Yang, Z. Huang, TS. Chua. "Filter-based Stance Network for Rumor Verification". ACM Trans. Inf. Syst. 42(4): 108:1-108:28 (2024)
  4. Y. Luo, Z. Wang, Z. Chen, Z. Huang, M. Baktashmotlagh. "Progressive Graph Learning for Open-Set Domain Adaptation". IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 45(9): 11240-11255, 2023
  5. T. Niu, S. Dong, Z. Chen, X. Luo, Z. Huang, S. Guo, X. Xu. "A multi-layer memory sharing network for video captioning". Pattern Recognit (PR) 136: 109202, 2023
  6. T. Chen, H. Yin, J. Ren, Z. Huang, X. Zhang and H. Wang. "Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning". IEEE Transactions on Knowledge and Data Engineering 35(2): 2103-2117, 2023
  7. M. Imran, H. Yin, T. Chen, Z. Huang, K. Zheng. "DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks". IEEE Transactions on Knowledge and Data Engineering 35(4): 3645-3657, 2023
  8. Y. Luo, Z. Huang, H. Chen, Y. Yang, H. Yin, M. Baktashmotlagh. "Interpretable Signed Link Prediction With Signed Infomax Hyperbolic Graph". IEEE Transactions on Knowledge and Data Engineering 35(4): 3991-4002, 2023
  9. P. Zhang, G. Bai, H. Yin, Z. Huang. "Proactive Privacy-preserving Learning for Cross-modal Retrieval". ACM Transactions on Information Systems (TOIS) 41(2): 35:1-35:23, 2023
  10. J. Duan, P. Zhang, R. Qiu, Z. Huang. "Long short-term enhanced memory for sequential recommendation". World Wide Web: 1-23, 2022
  11. M. Imran, H. Yin, T. Chen, Z. Huang, K. Zheng. "DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks". IEEE Transactions on Knowledge and Data Engineering: 2022
  12. Y. Luo, Z. Huang, H. Chen, Y. Yang, H. Yin, M. Baktashmotlagh. "Interpretable signed link prediction with signed infomax hyperbolic graph". IEEE Transactions on Knowledge and Data Engineering: 2021
  13. R. Qiu, Z. Huang, T. Chen, H. Yin. "Exploiting positional information for session-based recommendation". ACM Transactions on Information Systems (TOIS): 40(2):1-24, 2021
  14. T. Chen, H. Yin, X. Zhang, Z. Huang, Y. Wang, M. Wang. “Quaternion Factorization Machines: A Lightweight Solution to Intricate Feature Interaction Modeling”. IEEE Transactions on Neural Networks and Learning Systems: 2021
  15. Y. Li, T. Chen, Z. Huang. "Attribute-aware explainable complementary clothing recommendation". World Wide Web 24: 1885–190, 2021
  16. T. Chen, H. Yin, J. Ren, Z. Huang, X. Zhang and H. Wang, "Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning" in IEEE Transactions on Knowledge and Data Engineering: 2021
  17. S. Ji, X. Li, Z. Huang, E. Cambria, "Suicidal ideation and mental disorder detection with attentive relation networks". Neural Comput & Applic: 1-11, 2021
  18. P. Zhang, Y. Luo, Z. Huang, X. Xu, J. Song, “High-order nonlocal Hashing for unsupervised cross-modal retrieval”. World Wide Web 24(2):563-83, 2021
  19. P. Zhang, Y. Li, Z. Huang and X. Xu, "Aggregation-Based Graph Convolutional Hashing for Unsupervised Cross-Modal Retrieva," in IEEE Transactions on Multimedia: 24:466-79, 2021
  20. S. Ji, S. Pan, X. Li, E. Cambria, G. Long and Z. Huang, "Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications". IEEE Transactions on Computational Social Systems, 8(1): 214-226, 2021
  21. J. Li, K. Lu, Z. Huang, and H. T. Shen. "On Both Cold-Start and Long-Tail Recommendation with Social Data". IEEE Transactions on Knowledge and Data Engineering (TKDE), 33(1): 194-208, 2021
  22. P. Zhang, Y. Luo, Z. Huang, X. Xu, and J. Song. "High-order nonlocal Hashing for unsupervised cross-modal retrieval". World Wide Web 24(2):563-583, 2021
  23. L. Peng, Y. Yang, Z. Wang, Z. Huang, and H. T. Shen, "MRA-Net: Improving VQA via Multi-modal Relation Attention Network". IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI). (accepted)
  24. X. Ren, H. Yin, T. Chen, H. Wang, N. Huang, Z. Huang, and X. Zhang, "CRSAL: Conversational Recommender Systems with Adversarial Learning". ACM Transactions on Information Systems. 38(4): 34:1-34:40, 2020
  25. R. Qiu, Z. Huang, J. Li, H. Yin, "Exploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks". ACM Transactions on Information Systems. 38(3): 22:1-22:23, 2020
  26. J. Li, K. Lu, Z. Huang, L. Zhu, and H. T. Shen, "Transfer Independently Together: A Generalized Framework for Domain Adaptation". IEEE Trans. Cybernetics 49(6): 2144-2155 (2019)
  27. X. Luo, P. Zhang, Z. Huang,L. Nie, and X. Xu, "Discrete Hashing With Multiple Supervision". IEEE Trans. Image Processing 28(6): 2962-2975 (2019)
  28. Z. Zhang, Z. Lai, Z. Huang, W. Wong, G. Xie, L. Liu, and L. Shao, "Scalable Supervised Asymmetric Hashing With Semantic and Latent Factor Embedding". IEEE Trans. Image Processing 28(10): 4803-4818 (2019)
  29. Y. Yang, Y. Duan, X. Wang, Z. Huang, N. Xie and H. T. Shen, "Hierarchical Multi-Clue Modelling for POI Popularity Prediction with Heterogeneous Tourist Information". IEEE Transactions on Knowledge and Data Engineering (TKDE)31(4): 757-768 (2019)
  30. J, Li, K. Lu, Z Huang, L. Zhu, and H. T. Shen, "Heterogeneous Domain Adaptation Through Progressive Alignment". IEEE Trans. Neural Netw. Learning Syst. 30(5): 1381-1391 (2019)
  31. Z. Liu, Y. Yang, Z Huang, F. Shen, D. Zhang, and H. T. Shen, "Embedding and predicting the event at early stage". World Wide Web 22(3): 1055-1074 (2019)
  32. H. Yin, W. Wang, L. Chen, X. Du, Q. Nguyen and Z. Huang. "Mobi-SAGE-RS: A sparse additive generative model-based mobile application recommender system". Knowledge Based Systems. 157:68-80, 2018
  33. F. Shen, Y. Xu, L Liu, Y. Yang, Z. Huang, and H. T. Shen, "Unsupervised Deep Hashing with Similarity-Adaptive and Discrete Optimization". IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 40(12): 3034-3044, 2018
  34. Y. Luo, Y. Yang, F. Shen, Z. Huang, P. Zhou, and H. T. Shen, "Robust Discrete Code Modeling for Supervised Hashing". Pattern Recognition 75: 128-135, 2018
  35. L. Zhu, Z. Huang, Z. Li, L. Xie, and H. T. Shen, "Exploring Auxiliary Context: Discrete Semantic Transfer Hashing for Scalable Image Retrieval". IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 29(11): 5264-5276, 2018
  36. X. Du, H. Yin, Z. Huang, Y. Yang, and X. Zhou, "Exploiting detected visual objects for frame-level video filtering". World Wide Web 21(5): 1259-1284, 2018
  37. H. Cai, V. Zheng, F. Zhu, K. Chang, and Z. Huang, "From Community Detection to Community Profiling". PVLDB 10(7): 817-828, 2017
  38. C. Li, Z. Huang, Y. Yang, J. Cao, X. Sun, and H. T. Shen, "Hierarchical Latent Concept Discovery for Video Event Detection". IEEE Trans. Image Processing 26(5): 2149-2162, 2017
  39. L. Yu, Z. Huang, F. Shen, J. Song, H. T. Shen, and X. Zhou, "Bilinear Optimized Product Quantization for Scalable Visual Content Analysis". IEEE Trans. Image Processing 26(10): 5057-5069, 2017
  40. Y. Yang, F. Shen, Z. Huang, H. T. Shen, and X. Li, "Discrete Nonnegative Spectral Clustering". IEEE Transactions on Knowledge and Data Engineering (TKDE) 29(9):1834-1845, 2017
  41. Y. Shao, K. Lei, L. Chen, Z. Huang, B. Cui, Z. Liu, Y. Tong, and J. Xu, "Fast Parallel Path Concatenation for Graph Extraction". IEEE Transactions on Knowledge and Data Engineering. 29(10): 2210-2222, 2017
  42. L. Zhu, Z. Huang, X. Liu, X. He, J. Sun, and X. Zhou, "Discrete Multimodal Hashing With Canonical Views for Robust Mobile Landmark Search". IEEE Trans. Multimedia 19(9): 2066-2079, 2017
  43. X. Li, L. Chang, K. Zheng, Z. Huang, and X. Zhou, "Ranking weighted clustering coefficient in large dynamic graphs". World Wide Web 20(5): 855-883, 2017
  44. L. Yu, X. Sun, Z. Huang, "Robust Spatial-temporal Deep Model for Multimedia Event Detection". Neurocomputing 213: 48-53, 2016
  45. L. Yu, Y. Yang, Z. Huang, P. Wang, J. Song, H. T. Shen, "Web Video Event Recognition by Semantic Analysis from Ubiquitous Documents". IEEE Transactions on Image Processing 25(12): 5689-5701, 2016
  46. J. Song, H. T. Shen, J. Wang, Z. Huang, N. Sebe, J. Wang, "A Distance-Computation-Free Search Scheme for Binary Code Databases". IEEE Transactions on Multimedia 18(3): 484-495, 2016
  47. L. Yu, Z. Huang, J. Cao, H. T. Shen, "Scalable Video Event Retrieval by Visual State Binary Embedding". IEEE Transactions on Multimedia 18(8): 1590-1603, 2016
  48. H. Yin, B. Cui, X. Zhou, Weiqing Wang, Z. Huang, Shazia W. Sadiq, "Joint Modeling of User Check-in Behaviors for Real-time Point-of-Interest Recommendation". ACM Transactions on Information Systems. 35(2): 11:1-11:44, 2016
  49. H. Cai, Z. Huang, D. Srivastava, and Q. Zhang, "Indexing Evolving Events from Tweet Streams". IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(11): 3001-3015, 2015
  50. X. Li, H. Cai, Z. Huang, Y. Yang and X. Zhou, "Social event identification and ranking on Flickr", World Wide Web 18(5):1219-1245, 2015
  51. X. Lian, L. Chen, and Z. Huang, "Keyword Search Over Probabilistic RDF Graphs". IEEE Transactions on Knowledge and Data Engineering, 27(5): 1246-1260, 2015.
  52. N. Xu, B. Cui, Lei Chen, Z. Huang, and Y. Shao, "Heterogeneous Environment Aware Streaming Graph Partitioning", IEEE transactions on Knowledge and Data Engineering (TKDE), 27(6): 1560-1572, 2015
  53. J. Song, Y. Yang, X. Li, Z. Huang, and Y. Yang, "Robust Hashing with Local Models for Effective Similarity Search". IEEE Transactions on Systems, Man, and Cybernetics - PART B: Cybernetics, 44(7): 1225-1236, 2014.
  54. J. Liu, Y. Yang, Z. Huang, Y. Yang and H. T. Shen, "On the Influence Propagation of Web Videos". IEEE transactions on Knowledge and Data Engineering, 26(8): 1961-1973, 2014.
  55. E. Belisle, Z. Huang, S. Le Digabel and A. Gheribi, "Evaluation of machine learning interpolation techniques for prediction of physical properties". Computational Materials Science, 98:170-177, 2014
  56. J. Song, Y. Yang, Z. Huang, H. T. Shen and J. Luo, "Effective Multiple Feature Hashing for Large-scale Near-duplicate Video Retrieval". IEEE Transactions on Multimedia, 5(8): 1997-2008, 2013.
  57. J. Liu, Z. Huang, H. Cai, H. T. Shen, C. W. Ngo and W. Wang, "Near-duplicate Video Retrieval: Current Research and Future Trends". ACM Computing Surveys, 45(4):44, 2013
  58. X. Zhu, Z. Huang, H. Cheng, J. Cui and H. T. Shen, "Sparse Hashing for Fast Multimedia Search". ACM Transactions on Information Systems, 31(2): 9, 2013.
  59. Y. Yang, J. Song, Z. Huang, Z. Ma, N. Sebe and A. G. Hauptmann, "Multi-Feature Fusion via Hierarchical Regression for Multimedia Analysis". IEEE Transactions on Multimedia (TMM), 15(3): 572-581, 2013.
  60. Z. Huang, J. Liu, B. Cui and X. Du, "Gram-based String Paradigm for Efficient Video Subsequence Search". IEEE Transactions on Multimedia, 15(3): 608-620, 2013.
  61. X. Zhu, Z. Huang, J. Cui, and H. T. Shen, "Video-to-Shot Tag Propagation by Graph Sparse Group Lasso". IEEE Transactions on Multimedia, 15(3): 633-646, 2013.
  62. Y. Han, Z. Xu, Z. Ma and Z. Huang, "Image classification with manifold learning for out-of-sample data". Signal Processing, 93(8): 2169-2177, 2013.
  63. Y. Yang, Z. Huang, Y. Yang, H. T. Shen and J. Luo, "Local Image Tagging via Graph Regularized Joint Group Sparsity". Pattern Recognition, 46(5): 1358-1368, 2013.
  64. X. Zhu, Z. Huang, Y. Yang, H. T. Shen, C. Xu and J. Luo, "Self-taught Dimensionality Reduction on the High-dimensional Small-sized Data". Pattern Recognition, 46(1): 215-229, 2013.
  65. K. Zheng, Z. Huang, A. Zhou and X. Zhou, "Discovering the Most Influential Sites over Uncertain Data: A Rank Based Approach". IEEE Transactions on Knowledge and Data Engineering, 24(12): 2156-2169, 2012.
  66. X. Zhu, Z. Huang, H. T. Shen, J Cheng and C Xu, "Dimensionality Reduction by Mixed Kernel Canonical Correlation Analysis". Pattern Recognition, 45(8): 3003-3016, 2012.
  67. X. Zhang, Z. Huang, H. T. Shen and Y. Yang and Z. Li, "Automatic Tagging by Exploring Tag Information Capability and Correlation". World Wide Web Journal (WWWJ), 15(3): 233-256, 2012.
  68. Z. Zhao, B. Cui, G. Cong, Z. Huang, and H. T. Shen, "Extracting Representative Motion Flows for Effective Video Retrieval". Multimedia Tools and Applications (MTAP), 58(3): 687-711, 2012.
  69. J. Liu, Z. Huang, H. T. Shen and B. Cui, "Correlation-based Retrieval for Heavily Changed Near-duplicate Videos". ACM Transactions on Information Systems, 29(4), 2011
  70. Y. Yang, Z. Huang, H. T. Shen and X. Zhou, "Mining Multi-tag Association for Image Tagging". World Wide Web Journal (WWWJ), 14(2): 133-156, 2011.
  71. Q. Xie, Z. Huang, H. T. Shen, X. Zhou and C. Pang, "Quick Identification of Near-duplicate Video Sequences with Cut Signature". World Wide Web Journal (WWWJ), 15(3): 355-382, 2011.
  72. J. Shao, H. T. Shen, Z. Huang and X. Zhou, "Exploring Distributional Discrepancy for Multi-dimensional Point Set Retrieval". IEEE Transactions on Multimedia (TMM), 13(1): 71-81, 2011.
  73. Z. Huang, H. T. Shen, J. Shao, B. Cui and X. Zhou, "Practical Online Near-duplicate Subsequence Detection for Continuous Video Streams". IEEE Transactions on Multimedia, 12(5): 386-398, 2010.
  74. Z. Huang, B. Hu, H. Cheng, H. T. Shen, H. Liu and X. Zhou, "Mining Near-duplicate Graph for Cluster-based Reranking of Web Video Search Results". ACM Transactions on Information Systems, 28(4), 2010.
  75. Z. Huang, H. T. Shen, J. Shao, X. Zhou and B. Cui, "Bounded Coordinate System Indexing for Real-time Video Clip Search". ACM Transactions on Information System, 27(3), 2009.
  76. H. T. Shen, S. Jiang, K.-L. Tan, Z. Huang and X. Zhou, "Speed Up Interactive Image Retrieval". VLDB Journal, 18(1): 329-343, 2009.
  77. H. T. Shen, J. Shao, Z. Huang and X. Zhou, "Effective and Efficient Query Processing for Video Subsequence Identification", IEEE Transactions on Knowledge and Data Engineering (TKDE), 21(3): 321-334, 2009.
  78. Z. Huang, H. T. Shen, and X. Zhou, "Localized Co-occurrence Model for Fast Approximate Search in 3D Structure Databases". IEEE Transactions on Knowledge and Data Engineering (TKDE), 20(4): 519-531, 2008.
  79. J. Shao, Z. Huang, H. T. Shen, X. Zhou, E.-P. Lim and Y. Li, "Batch Nearest Neighbor Search for Video Retrieval". IEEE Transactions on Multimedia (TMM), 10(3): 409-420, 2008.
  80. Selected Conference Papers

  81. A. Zhu, P. Zhang, R. Qiu, Z. Zheng, Z. Huang, J. Shao. "Abstract and Explore: A Novel Behavioral Metric with Cyclic Dynamics in Reinforcement Learning". AAAI 2024: 17150-17158
  82. Y. Tang, R. Qiu, Z. Zheng, Y. Liu, X. Li, and Z. Huang. "CaseGNN: Graph Neural Networks for Legal Case Retrieval with Text-Attributed Graphs". ECIR (2) 2024: 80-95
  83. Z. Chen, Y. Luo, Z. Wang, M. Baktashmotlagh, Z. Huang. "Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling". ICCV 2023: 3691-3703
  84. Z. Wang, Y. Luo, L. Zheng, Z. Huang, and M. Baktashmotlagh. "How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability". ICCV 2023: 5526-5535
  85. Y. Luo, Z. Chen, Z. Fang, Z. Zhang, M. Baktashmotlagh, Z. Huang. "Kecor: Kernel Coding Rate Maximization for Active 3D Object Detection". ICCV 2023: 18233-18244
  86. Y. Liu, R. Qiu, Z. Huang. "CaT: Balanced Continual Graph Learning with Graph Condensation". ICDM 2023: 1157-1162
  87. Y. Zhang, Z. Wang, Y. Luo, X. Yu, and Z. Huang. "Learning Efficient Unsupervised Satellite Image-based Building Damage Detection". ICDM 2023: 1547-1552
  88. Z. Wang, Y. Luo, Z. Chen, S. Wang, and Z. Huang. "Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration Error". ACM Multimedia 2023: 1167-1178 (Best Student Paper Award)
  89. Z. Chen, P. Zhang, J. Li, S. Wang, and Z. Huang. "Zero-Shot Learning by Harnessing Adversarial Samples". ACM Multimedia 2023: 4138-4146
  90. P. Zhang and Z. Huang. "Multi-head Siamese Prototype Learning against both Data and Label Corruption". MMAsia 2023: 61:1-61:7 (Outstanding Reserach Award)
  91. A. Zhu, P. Zhang, Y. Zhang, Z. Huang, J. Shao. “Abstract then Play: A Skill-centric Reinforcement Learning Framework for Text-based Games”. ACL (Findings):13225-13236, 2023
  92. Y. Luo, Z. Chen, Z. Wang, X. Yu, Z. Huang, M. Baktashmotlagh. “Exploring Active 3D Object Detection from a Generalization Perspective”. ICLR, 2023
  93. Z. Wang, Y. Luo, Z. Huang, M. Baktashmotlagh. "FFM: Injecting Out-of-Domain Knowledge via Factorized Frequency Modification". WACV: 4124-4133, 2023
  94. L. Qu, N. Tang, R. Zheng, Q. Nguyen, Z. Huang, Y. Shi, H. Yin. "Semi-decentralized Federated Ego Graph Learning for Recommendation". WWW: 339-348, 2023
  95. T. Chen, H. Yin, J. Ren, Z. Huang, X. Zhang, H. Wang. "Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning". ICDE: 1533-1534, 2022
  96. R. Qiu, Z. Huang, H. Yin. "Beyond Double Ascent via Recurrent Neural Tangent Kernel in Sequential Recommendation". ICDM: 428-437, 2022
  97. Z. Wang, Y. Luo, P. Zhang, S. Wang, Z. Huang. "Discovering Domain Disentanglement for Generalized Multi-Source Domain Adaptation". ICME: 1-6, 2022
  98. F. Xie, Y. Zhang, C. Yan, S. Li, L. Bu, K. Chen, Z. Huang, G. Bai. "Scrutinizing Privacy Policy Compliance of Virtual Personal Assistant Apps". ASE: 90:1-90:13, 2022
  99. P. Zhang, G. Bai, Z. Huang, X. Xu. "Machine Unlearning for Image Retrieval: A Generative Scrubbing Approach". ACM Multimedia: 237-245, 2022
  100. P. Zhang, Z. Huang, G. Bai, Xi. Xu. "IDEAL: High-Order-Ensemble Adaptation Network for Learning with Noisy Labels". ACM Multimedia: 325-333, 2022
  101. P. Zhang, Z. Huang, X. Luo, P. Zhao. "Robust Learning with Adversarial Perturbations and Label Noise: A Two-Pronged Defense Approach". MMAsia: 23:1-23:7, 2022
  102. Y. Chen, S. Wang, J. Liu, X. Xu, F. Hoog, Z. Huang. "Improved Feature Distillation via Projector Ensemble". NeurIPS, 2022
  103. S. Zhang, H. Yin, T. Chen, Z. Huang, Q. Nguyen, L. Cui. "PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion". WSDM: 1415-1423, 2022
  104. R. Qiu, Z. Huang, H. Yin, Z. Wang. "Contrastive learning for representation degeneration problem in sequential recommendation". WSDM 2022: 813-823
  105. R. Qiu, Z. Huang, H. Yin. "Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation". ICDM 2021: 519-528
  106. Y. Chen, S. Wang, J. Lu, Z. Chen, Z. Zhang, Z. Huang. "Local Graph Convolutional Networks for Cross-Modal Hashing". ACM Multimedia 2021: 1921-1928
  107. Z. Du, J. Li, K. Lu, L. Zhu, Z. Huang. "Learning Transferrable and Interpretable Representations for Domain Generalization". ACM Multimedia 2021: 3340-3349
  108. P. Zhang, J. Duan, Z. Huang, H. Yin. "Joint-teaching: Learning to refine knowledge for resource-constrained unsupervised cross-modal retrieval". ACM Multimedia 2021: 1517-1525
  109. R. Qiu, S. Wang, Z. Chen, H. Yin, Z. Huang. "Causalrec: Causal inference for visual debiasing in visually-aware recommendation". ACM Multimedia 2021: 3844-3852
  110. X. Li, J. Li, L. Zhu, G. Wang, Z. Huang. "Imbalanced Source-free Domain Adaptation". ACM Multimedia 2021: 3330-3339
  111. F. You, J. Li, L. Zhu, Z. Chen, Z. Huang "Domain adaptive semantic segmentation without source data". ACM Multimedia 2021: 3293-3302
  112. Z. Chen, Y. Luo, S. Wang, R. Qiu, J. Li, Z. Huang, "Mitigating generation shifts for generalized zero-shot learning". ACM Multimedia 2021: 844-852
  113. T. Chen, H. Yin, Y. Zheng, Z. Huang, Y. Wang, M. Wang, "Learning elastic embeddings for customizing on-device recommenders". SIGKDD 2021: 138-147
  114. P. Zhang, Y. Li, Z. Huang, H. Yin, "Privacy protection in deep multi-modal retrieval". SIGIR 2021: 634-643
  115. X. Ren, H. Yin, T. Chen, H. Wang, Z. Huang, K. Zheng, "Learning to ask appropriate questions in conversational recommendation". SIGIR 2021: 808-817
  116. P. Zhang, Z. Huang, X. Xu, "Proactive Privacy-preserving Learning for Retrieval". AAAI 2021: 3369-3376
  117. M. Imran, H. Yin, T. Chen, Z. Huang, X. Zhang and K. Zheng, "DDHH: A Decentralized Deep Learning Framework for Large-scale Heterogeneous Networks". ICDE 2021: 2033-2038
  118. S. Zhang, H. Yin, T. Chen, Z. Huang, L. Cui, X. Zhang, "Graph embedding for recommendation against attribute inference attacks". the Web Conference 2021: 3002-3014
  119. J. Alghamdi, Z. Huang, "Modeling Daily Crime Events Prediction Using Seq2Seq Architecture". ADC 2021: 192-203
  120. Z. Chen, Z. Huang, J. Li, Z. Zhang, "Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning". ADC 2021: 139-151
  121. Z. Wang, Z. Huang and Y. Luo, "Human Consensus-Oriented Image Captioning". IJCAI 2021: 659-665
  122. Z. Wang, Y. Luo, R. Qiu, Z. Huang, M. Baktashmotlagh, "Learning To Diversify for Single Domain Generalization". ICCV 2021: 834-843
  123. Z. Chen, Y. Luo, R. Qiu, S. Wang, Z. Huang, J. Li, Z. Zhang. "Semantics disentangling for generalized zero-shot learning". ICCV 2021: 8712-8720
  124. P. Zhang, Y. Li, Z. Huang, H. Yin. "Privacy Protection in Deep Multi-modal Retrieval". SIGIR 2021: 634-643
  125. Y. Luo, Z. Huang, Z. Wang, Z. Zhang, and M. Baktashmotlagh. "Adversarial Bipartite Graph Learning for Video Domain Adaptation". ACM Multimedia 2020:19-27
  126. Z. Chen, S. Wang, J. Li, and Z. Huang. "Rethinking Generative Zero-Shot Learning: An Ensemble Learning Perspective for Recognising Visual Patches". ACM Multimedia 2020: 3413-3421
  127. Z. Wang, Y. Luo, Z. Huang, and M. Baktashmotlagh. "Prototype-Matching Graph Network for Heterogeneous Domain Adaptation". ACM Multimedia 2020: 2104-2112
  128. M. Jing, J. Li, L. Zhu, K. Lu, Y. Yang, and Z. Huang. "Incomplete Cross-modal Retrieval with Dual-Aligned Variational Autoencoders". ACM Multimedia 2020: 3283-3291
  129. Y. Luo, Z. Wang, Z. Huang, M. baktashmotlagh. "Progressive Graph Learning for Open-Set Domain Adaptation". ICML 2020: 6468-6478
  130. R. Qiu, H. Yin, Z. Huang, and T. Chen. "GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation". SIGIR 2020: 669-678
  131. T. Chen, H. Yin, G. Ye, Z. Huang, Y. Wang, and M. Wang. "Try This Instead: Personalized and Interpretable Substitute Recommendation". SIGIR 2020: 891-900
  132. S. Zhang, H. Yin, T. Chen, N. Huang, Z. Huang, and L. Cui. "GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Identification". SIGIR 2020: 689-698
  133. Z. Wang Z. Huang, and Y. Luo. "Human Consensus-Oriented Image Captioning". IJCAI 2020: 659-665
  134. Y. Luo, Z. Huang, Z. Zhang, Z. Wang, M. Baktashmotlagh, and Y. Yang. "Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural Networks". AAAI 2020: 5021-5028
  135. L. Guo, H. Yin, Q. Wang, B. Cui, Z. Huang, and L. Cui. "Group Recommendation with Latent Voting Mechanism". ICDE 2020:121-132
  136. Q. Wang, H. Yin, T. Chen, Z. Huang, H. Wang, Y. Zhao, and N. Hung. "Next Point-of-Interest Recommendation on Resource-Constrained Mobile Devices". WWW 2020:906-916
  137. Z. Chen, J. Li, Y. Luo, Z. Huang, and Y. Yang. "CANZSL: Cycle-Consistent Adversarial Networks for Zero-Shot Learning from Natural Language". WACV 2020, 874-883
  138. Z. Wang, Z. Huang, and Y. Luo. "PAIC: Parallelised Attentive Image Captioning". ADC 2020:16-28 (Best Paper Award)
  139. Y. Luo, Z. Huang, Z. Zhang, Z. Wang, J. Li and Y. Yang. "Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation". ACM Multimedia 2019: 2341-2350
  140. L. Peng, Y. Yang, Z. Wang, X. Wu and Z. Huang. "CRA-Net: Composed Relation Attention Network for Visual Question Answering". ACM Multimedia 2019: 1202-1210
  141. J. Li, M. Jing, K. Lu, L. Zhu, Y. Yang and Z. Huang. "Alleviating Feature Confusion for Generative Zero-shot Learning". ACM Multimedia 2019: 1587-1595
  142. J. Li, E. Chen, Z. Ding, L. Zhu, K. Lu and Z. Huang. "Cycle-consistent Conditional Adversarial Transfer Networks". ACM Multimedia 2019: 747-755
  143. R. Qiu, J. Li, Z. Huang, and H. Yin. "Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks". CIKM 2019:579-588
  144. Q. Wang, H. Yin, H. Wang, Q. Nguyen, Z. Huang and L Cui. "Enhancing Collaborative Filtering with Generative Augmentation". SIGKDD 2019: 548-556
  145. J. Li, M. Jing, K. Lu, Z. Ding, L. Zhu and Z. Huang. "Leveraging the Invariant Side of Generative Zero-Shot Learning". CVPR 2019 (oral, accepted)
  146. J. Li, M. Jing, K. Lu, Z. Ding, L. Zhu, Y. Yang and Z. Huang. "From Zero-Shot Learning to Cold-Start Recommendation". AAAI 2019:4189-4196
  147. Y. Bin, C. Tao, Y. Yang, Z. Huang, J. Li, and H. T. Shen, "MR-NET: Exploiting Mutual Relation for Visual Relationship Detection". AAAI 2019:8110-8117
  148. Z. Zhang, Y. Li, S. Li, G. Xie and Z. Huang. "SADIH: Semantic-Aware DIscrete Hashing" AAAI 2019: 5853-5860
  149. Q. Wang, H. Yin, H. Wang and Z. Huang. "TSAUB: A Temporal-Sentiment-Aware User Behavior Model for Personalized Recommendation". ADC 2018:211-233 (Best Paper Award)
  150. Y. Luo, Z. Wang, Z. Huang, Y. Yang, and C Zhao. "Coarse-to-Fine Annotation Enrichment for Semantic Segmentation Learning". CIKM 2018: 237-246
  151. W. Wang, H. Yin, Z. Huang, X. Sun, and Q Nguyen, "Restricted Boltzmann Machine Based Active Learning for Sparse Recommendation". DASFAA (1) 2018:100-115
  152. L. Liu, X. Du, L. Zhu, F. Shen and Z. Huang, "Discrete Binary Hashing Towards Efficient Fashion Recommendation". DASFAA (1) 2018:116-132
  153. L. Liu, Y. Yang, M. Hu, X. Xu, F. Shen, N. Xie and Z. Huang, "Index and Retrieve Multimedia Data: Cross-Modal Hashing by Learning Subspace Relation". DASFAA (2) 2018:606-621
  154. H. Yin, L. Zou, Q. Nguyen, Z. Huang, and X. Zhou, "Joint Event-Partner Recommendation in Event-Based Social Networks". ICDE 2018: 929-940
  155. Y. Shao, K. Lei, L. Chen, Z. Huang, B. Cui, Z. Liu, Y. Tong, and J. Xu: "Fast Parallel Path Concatenation for Graph Extraction". ICDE 2018: 1753-1754
  156. Q. Wang, H. Yin, Z. Hu, D. Lian, H. Wang and Z. Huang, "Neural Memory Streaming Recommender Networks with Adversarial Training". SIGKDD 2018: 2467-2475
  157. X. Xu, J. Song, H. Lu, Y. Yang, F. Shen and Z. Huang. "Modal-adversarial Semantic Learning Network for Extendable Cross-modal Retrieval". ICMR 2018:46-54
  158. B. Ke, J. Shao, Z. Huang, and H. T. Shen, "Feature Reconstruction by Laplacian Eigenmaps for Efficient Instance Search". ICMR 2018: 231-239
  159. J. Li, L. Zhu, Z. Huang, K Lu and J. Zhao, "I read, I saw, I tell: Texts Assisted Fine-Grained Visual Classification". ACM Multimedia 2018: 663-671
  160. Z. Wang, Y. Luo, Y Li, Z. Huang and H. Yin, "Look Deeper See Richer: Depth-aware Image Paragraph Captioning". ACM Multimedia 2018: 672-680
  161. W. Wang, H. Yin, Z. Huang, Q. Wang, X. Du and Q Nguyen, "Streaming Ranking Based Recommender Systems". SIGIR 2018: 525-534
  162. Y. Zhang, H. Yin, Z. Huang, X. Du, G. Yang and D. Lian, "Discrete Deep Learning for Fast Content-Aware Recommendation". WSDM 2018:717-726
  163. X. Sun, Z. Huang, H. Yin, H. T. Shen, "An Integrated Model for Effective Saliency Prediction". AAAI 2017:274-281
  164. L. Gao, P. Wang, J. Song, Z. Huang, Jie Shao, H. T. Shen, "Event Video Mashup: From Hundreds of Videos to Minutes of Skeleton". AAAI 2017: 1323-1330
  165. C. Li, Y. Yang, J. Cao, and Z. Huang, "Jointly Modeling Static Visual Appearance and Temporal Pattern for Unsupervised Video Hashing". CIKM 2017: 9-17
  166. P. Wang, L. Liu, C. Shen, Z. Huang, A. van den Hengel, and H. T. Shen, "Multi-attention Network for One Shot Learning". CVPR 2017: 6212-6220
  167. C. Li, J. Cao, Z. Huang, and H. T. Shen, "Leveraging Weak Semantic Relevance for Complex Video Event Classification". ICCV 2017: 3667-3676
  168. H. Cai, V. W. Zheng, P. Chen, F. Zhu, K. Chang and Z. Huang, "SocialLens: Searching and Browsing Communities by Content and Interaction". ICDE2017: 1397-1398
  169. X. Xu, F. Shen, Y. Yang, J. Shao, and Zi Huang, "Transductive Visual-Semantic Embedding for Zero-shot Learning". ICMR 2017: 41-49
  170. J. Cao, Z. Huang, and H. T. Shen, "Local Deep Descriptors in Bag-of-Words for Image Retrieval". ACM Multimedia (Thematic Workshops) 2017: 52-58
  171. L. Zhu, Z. Huang, X. Chang, J. Song, and H. T. Shen, "Exploring Consistent Preferences: Discrete Hashing with Pair-Exemplar for Scalable Landmark Search". ACM Multimedia 2017: 726-734
  172. J. Li, K. Lu, Z. Huang, and H. T. Shen, "Two Birds One Stone: On both Cold-Start and Long-Tail Recommendation". ACM Multimedia 2017: 898-906
  173. Y. Bin, Y. Yang, J. Zhou, Z. Huang, and H. T. Shen, "Adaptively Attending to Visual Attributes and Linguistic Knowledge for Captioning". ACM Multimedia 2017: 1345-1353
  174. G. Hu, J. Shao, F. Shen, Z. Huang, and H. T. Shen, "Unifying Multi-Source Social Media Data for Personalized Travel Route Planning". SIGIR 2017: 893-896
  175. Z. Liu, Y. Yang, Z. Huang, F. Shen, D. Zhang, H. T. Shen, "Event Early Embedding: Predicting Event Volume Dynamics at Early Stage". SIGIR 2017: 997-1000
  176. Y. Duan, X. Wang, Y. Yang, Z. Huang, N. Xie, H. T. Shen, "POI Popularity Prediction via Hierarchical Fusion of Multiple Social Clues". SIGIR 2017: 1001-1004
  177. X. Du, H. Yin, Z. Huang, Y. Yang, and X. Zhou, "Using Detected Visual Objects to Index Video Database". ADC 2016: 333-345 (Best Paper Award)
  178. T. Yan, X. Xu, S. Guo, Z. Huang, and X. Wang, "Supervised Robust Discrete Multimodal Hashing for Cross-Media Retrieval". CIKM 2016: 1271-1280
  179. P. Wang, L. Liu, C. Shen, Z. Huang, A. van den Hengel, and H. T. Shen, "What's Wrong with That Object? Identifying Images of Unusual Objects by Modelling the Detection Score Distribution". CVPR 2016: 1573-1581
  180. H. Cai, Z. Huang, D. Srivastava, and Q. Zhang, "Indexing evolving events from tweet streams", ICDE 2016: 1538-1539
  181. Y. Yang, F. Shen, Z. Huang, and H. T. Shen, "A Unified Framework for Discrete Spectral Clustering". IJCAI 2016: 2273-2279
  182. H. Cai, Y. Yang, X. Li and Z. Huang, "What are Popular: Exploring Twitter Features for Event Detection, Tracking and Visualization". In Proceedings of 23rd ACM International Conference on Multimedia (ACM MM), 89-98, 2015.
  183. J. Cao, Z. Huang and Y. Yang, "Spatial-aware Multimodal Location Estimation for Social Images". In Proceedings of 23rd ACM International Conference on Multimedia (ACM MM), 119-128, 2015.
  184. H. Yin, B. Cui, Z. Huang, W. Wang, X. Wu and X. Zhou, "Joint Modeling of Users' Interests and Mobility Patterns for Point-of-Interest Recommendation". In Proceedings of 23rd ACM International Conference on Multimedia (ACM MM), 819-822, 2015
  185. E. Bélisle, Z. Huang, and A. Gheribi, "Truth Discovery in Material Science Databases.", In Proceedings of ADC 2015: 269-280
  186. H. Cai, Z. Tang, Y. Yang, and Z. Huang, "EventEye: Monitoring Evolving Events from Tweet Streams". In Proceedings of 22nd ACM International Conference on Multimedia (ACM MM), 747-748, 2014
  187. P. Wang, Y. Yang, Z.Huang, J. Cao, and H. T. Shen, "WeMash: An Online System for Web Video Mashup". In Proceedings of 22nd ACM International Conference on Multimedia (ACM MM), 753-754, 2014
  188. Y. Liu, J. Cui, Z. Huang, H. Li, and H. T. Shen. "SKLSH : An Efficient Index Structure for Approximate Nearest Neighbor Search". In Proceedings of 40th VLDB (PVLDB), 7(9): 745-756, 2014.
  189. H. Yin, B. Cui, L. Chen, Z. Hu, and Z. Huang. "A Temporal Context-Aware Model for User Behavior Modeling in Social Media Systems". In Proceedings of 33rd ACM SIGMOD International Conference on Management of Data, 1543-1554, 2014
  190. H. Cai, Z. Huang, X. Zhu, Q. Zhang, and X. Li. "Multi-Output Regression with Tag Correlation Analysis for Effective Image Tagging". In proceedings of 19th International Conferences on Databases Systems for Advanced Systems (DASFAA) (2) 2014: 31-46.
  191. X. Li, H. Cai, Z. Huang, Y. Yang, and X. Zhou. "Spatio-temporal Event Modeling and Ranking". In Proceedings of 14th International Conference on Web Information System Engineering (WISE), 361-374, 2013. (Best Paper Award)
  192. B. Luo and Z. Huang. "Imagilar: A Real-time Image Similarity Search System on Mobile Platform". In Proceedings of 14th International Conference on Web Information System Engineering (WISE), 535-538, 2013.
  193. X. Zhu, Z. Huang, H. T. Shen and X. Zhao. "Linear Cross-Modal Hashing for Effective Multimedia Search". In Proceedings of 21st ACM International Conference on Multimedia (ACM MM), 143-152, 2013.
  194. J. Song, Y. Yang, Y. Yang, Z. Huang and H. T. Shen. "Inter-Media Hashing for Large-scale Retrieval from Heterogeneous Data Sources". In Proceedings of 32nd International Conference on Management of Data (SIGMOD), 785-796, 2013.
  195. J. Liu, Z. Huang, H. T. Shen, H. Cheng and Y. Chen. "Presenting Diverse Location Views with Real-time Near-duplicate Photo Elimination ". In Proceedings of 29th IEEE International Conference on Data Engineering (ICDE), pages 505-516, 2013.
  196. X. Zhu, Z. Huang, and X. Wu. "Multi-view Visual Classification via a Mixed-norm Regularizer". In proceedings of 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pages 520-531, 2013.
  197. J. Cui, Z. Huang, B. Wang, and Y. Liu. "Near-optimal Partial Linear Scan for Nearest Neighbor search in high-dimensional space". In proceedings of 18th International Conferences on Databases Systems for Advanced Systems (DASFAA), pages 101-115, 2013.
  198. S. Unankard, L. Chen, P. Li, S. Wang, Z. Huang, M. Sharaf, and X. Li (2012), On the Prediction of Re-tweeting Activities in Social Networks - a Report on WISE 2012 Challenge, WISE, 744-754, 2012. (CHAMPION: Data Mining Track)
  199. J. Liu, Z. Huang, L. Chen, H. T. Shen, and Z. Yan. "Discovering and Ranking Areas of Interest with Geo-tagged Images and Check-ins". In Proceedings of 20th ACM International Conference on Multimedia (ACM MM), pages 589-598, 2012.
  200. Y. Yang, Y. Yang, Z. Huang, J. Liu and Z. Ma. "Robust Cross-Media Transfer for Visual Event Detection". In Proceedings of 20th ACM International Conference on Multimedia (ACM MM), pages 1045-1048, 2012.
  201. H. Cai, Z. Huang, J. Shao, and X Li. "Context Sensitive Tag Expansion with Information Inference". In proceedings of 17th International Conferences on Databases Systems for Advanced Systems (DASFAA), pages 440-454, 2012. (Best Paper Award)
  202. J. Song, Y. Yang, Z. Huang, H. T. Shen, and R. Hong. "Multiple Feature Hashing for Real-time Large Scale Near-duplicate Video Retrieval". In Proceedings of 19th ACM International Conference on Multimedia (ACM MM), 423-432, 2011.
  203. Y. Yang, Y. Yang, Z. Huang and H. T. Shen. "Transfer Tagging from Image to Video". In Proceedings of 19th ACM International Conference on Multimedia (ACM MM), 1137-1140, 2011.
  204. X. Zhu, Z. Huang and H. T. Shen. "Video-to-Shot Tag Allocation by Weighted Sparse Group Lasso". In Proceedings of 19th ACM International Conference on Multimedia (ACM MM), 1501-1504, 2011.
  205. Z. Huang, H. T. Shen, J. Liu and X. Zhou (2011). "Effective Data Co-Reduction for Multimedia Similarity Search". In Proceedings of 30th ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 1021-1032, 2011.
  206. Y. Yang, Y. Yang, Z. Huang, H. T. Shen and F. Nie. "Tag Localization with Spatial Correlations and Joint Group Sparsity". In Proceedings of IEEE Computer Vision and and Pattern Recognition (CVPR), pages 881-888, 2011.
  207. Y. Yang, H. T. Shen, Z. Ma, Z. Huang and X. Zhou. "L21-Norm Regularized Discriminative Feature Selection for Unsupervised Learning". In Proceedings of the 22nd International Joint Conferences on Artificial Intelligence (IJCAI), 1589-1594, 2011.
  208. X. Zhang, Z. Huang, H. T. Shen and Z. Li (2011). "Probabilistic Image Tagging with Tags Expanded by Text-based Search". In proceedings of 16th International Conferences on Databases Systems for Advanced Systems (DASFAA), pages 269-283, 2011.
  209. J. Liu, Z. Huang, H. T. Shen, and X. Zhou (2011). "Efficient Histogram-based Similarity Search in Ultra-high Dimensional Space". In proceedings of 16th International Conferences on Databases Systems for Advanced Systems (DASFAA), pages 1-15, 2011.
  210. Q. Xie, Z. Huang, H. T. Shen, X. Zhou and C. Pang (2010). "Efficient and Continuous Near-duplicate Video Detection". In proceedings of 12th International Asia-Pacific Web Conference (APWEB), pages 260-266, 2010. (Best Paper Award)
  211. R. Cheng, Z. Huang, H. T. Shen and X. Zhou. "Interactive Near-Duplicate Video Retrieval and Detection". In Proceedings of 17th ACM International Conference on Multimedia (ACM MM), pages 1001-1002, 2009. (demo)
  212. H. T. Shen, Z. Huang, J. Cao and X. Zhou (2009). "High-dimensional indexing with oriented cluster representation for multimedia database". In Proceedings of ITEE International Conference on Multimedia & Expo (ICME), pages 1628-1631, 2009.
  213. Z. Huang, H. T. Shen, D. Song, X. Li and S. Rueger (2009). "Dimension-specific Search for Multimedia Retrieval". In proceedings of 14th International Conferences on Databases Systems for Advanced Systems (DASFAA), pages 693-698, 2009.
  214. Z. Huang, L. Wang, H. T. Shen, J. Shao and X. Zhou, "Online Near-Duplicate Video Clip Detection and Retrieval: An Accurate and Fast System". In Proceedings of 25th IEEE International Conference on Data Engineering (ICDE), pages 1511-1514, 2009.
  215. Z. Huang, H. T. Shen, J. Shao, S. Rueger and X. Zhou (2008). "Locality Condensation: A New Dimensionality Reduction Method for Image Retrieval". In Proceedings of 16th ACM International Conference on Multimedia (ACM MM), pages 219-228, 2008.
  216. J. Shao, Z. Huang, H. T. Shen, J. Shen and X. Zhou (2008). "Distribution-based Similarity Measures for Multi-dimensional Point Set Retrieval Applications". In Proceedings of 16th ACM International Conference on Multimedia (ACM MM), pages 429-438, 2008.
  217. R. Hu, S. Rueger, D. Song, H. Liu, and Z. Huang (2008). "Dissimilarity Measures for Content-based Image Retrieval". In Proceedings of ITEE International Conference on Multimedia & Expo (ICME), pages 1365-1368, 2008.
  218. H. T. Shen, X. Zhou, Z. Huang, and J. Shao, "Statistical Summarization of Content Features for Fast Near-duplicate Video Detection". In Proceedings of 15th ACM International Conference on Multimedia (ACM MM), pages 164-165, 2007. (demo).
  219. H. T. Shen, X. Zhou, Z. Huang, J. Shao and E. Zhou, "UQLIPS: A Real-time Near-duplicate Video Clip Detection System", In Proceedings of 33rd VLDB, pages 1374-1377, 2007.
  220. Z. Huang, H. T. Shen, X. Zhou, D. Song and S. Rueger, "Dimensionality Reduction for Dimension-specific Search". In Proceedings of 30th ACM SIGIR, pages 849-850, 2007.
  221. J. Shao, Z. Huang, H. T. Shen, X. Zhou and Y. Li (2007). "Dynamic Batch Nearest Neighbour Search in Video Retrieval". In Proceedings of 23rd IEEE International Conference on Data Engineering (ICDE), pages 1395-1399, 2007.
  222. H.T. Shen, B. C. Ooi, X. Zhou and Z. Huang (2005). “Towards effective indexing for large video sequence data”, In Proceedings of 24th ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 730-741, 2005.

2020 INFS3202/7202 Web Information Systems

Demonstration of Selected Course Projects

2020 Sem 2, Thesis Project (call for project students)

Big Media Intelligence Super Project - Sem 2, 2020

This super project consists of a series of independent tasks in large scale multimedia data analytics. Students will select ONE task from any research directions to undertake their thesis project.


Research Direction 1 - Ambulance Data Analysis and Visualization
Task 1 - Ambulance Data Analysis and Visualization

Task 1.1: Data visualization: In this task, students are required to visualize the compelling stories by transforming the data and decide the right type of visualization. Besides, a dashboard is expected to be designed for demonstrating this dataset on a user-friendly interface. Students participating in this project are expected to have the following skills:

  • good Web development skills including both frontend and backend system development. A dashboard is expected to be implemented.
  • good understanding of database management
  • experiences of data mining (INFS4203/7203) or related areas

Task 1.2: Data Analysis: Before conducting data analysis, detecting and correcting corrupt or inaccurate records has to be done on the dataset, i.e., data cleaning. With the goal of discovering useful information, informing conclusions and supporting decision-making, students are required to have in-depth understanding of the interesting patterns inside the provided dataset.

  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), or pattern recognition and analysis (INFS3710)
  • good programming skills

Task 2 - Traffic Data Analysis and Visualization

Task 2.1: Data Visualization. In this task, the students are expected to (1) visualize the real world traffic data (i.e., goCard transactions) provided by TransLink and help staff to understand the passenger flow; (2) Find the relevance between traffic data and social events (e.g., major uni events). Students participating in this project are expected to have the following skills:

  • good Web development skills including both frontend and backend system development. A dashboard is expected to be implemented
  • good understanding of database management
  • experiences of data mining (INFS4203/7203) or related areas

Task 2.2: Traffic Prediction. Generally, students are required to model session-based traffic data with sequential model or graph model and estimate the variance of people flow. Students participating in this project are expected to have the following skills:

  • experiences of machine learning (COMP4702), data mining (INFS4203/7203; INFS7450), high-dimensional data processing (INFS4205/7205), information retrieval (INFS7410) or pattern recognition and analysis (INFS3710)
  • strong programming skills


Research Direction 2 - Content-based Image Understanding
Task 3 - Curb & Channel Crack Detection

Task 3.1: Road Scene Segmentation: Students are required to study pixel-labeling approaches using semantic segmentation for road scene understanding. Students participating in this project are expected to have the following skills:

  • image processing
  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), or pattern recognition and analysis (INFS3710)
  • Strong programming skills

Task 3.2: Crack Detection: Automatic detection of pavement cracks is an important task in transportation maintenance for driving safety assurance.However, it remains a challenging task due to the intensity inhomogeneity of cracks and complexity of the background, e.g., the low contrast with surrounding pavement and possible shadows with similar intensity. Students participating in this project are expected to have the following skills:

  • image processing
  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), pattern recognition and analysis (INFS3710)
  • Strong programming skills


Research Direction 3 - Social Data Analysis and Visualization
Task 4 - Event Detection

Crawl and analyse news or tweets for public event detection. A dashboard (or other interactive methods) is expected to be designed for demonstrating the event.

  • Web development skills including both frontend and backend system development. A dashboard is expected to be implemented.
  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205)

Task 5 - Sentiment Detection

Crawl and analyse news or tweets for event sentiment analysis. This will be focused on the the analysis of public reactions to big social events. Students are required to visualize the compelling stories by transforming the data and decide the right type of visualization. Students participating in this project are expected to have the following skills:

  • Web development skills including both frontend and backend system development. A dashboard is expected to be implemented.
  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205)

Task 6 - Community Profiling

Crawl and analyse news or tweets for community analysis. This will be focused on graph construction, summarisation and profiling. Students are required to visualize the compelling stories by transforming the data and decide the right type of visualization. Students participating in this project are expected to have the following skills:

  • Web development skills including both frontend and backend system development. A dashboard is expected to be implemented.
  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205)

2020 Sem 1, Thesis Project

Big Media Intelligence Super Project - Sem 1, 2020

This super project consists of a series of independent tasks in large scale multimedia data analytics. Students will select ONE task from any research directions to undertake their thesis project.


Research Direction 1 - Ambulance Data Analysis and Visualization
Task 1 - Ambulance Data Analysis and Visualization

Task 1.1: Data visualization: In this task, students are required to visualize the compelling stories by transforming the data and decide the right type of visualization. Besides, a dashboard is expected to be designed for demonstrating this dataset on a user-friendly interface. Students participating in this project are expected to have the following skills:

  • good Web development skills including both frontend and backend system development. A dashboard is expected to be implemented.
  • good understanding of database management
  • experiences of data mining (INFS4203/7203) or related areas

Task 1.2: Data Analysis: Before conducting data analysis, detecting and correcting corrupt or inaccurate records has to be done on the dataset, i.e., data cleaning. With the goal of discovering useful information, informing conclusions and supporting decision-making, students are required to have in-depth understanding of the interesting patterns inside the provided dataset.

  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), or pattern recognition and analysis (INFS3710)
  • good programming skills

Task 2 - Traffic Data Analysis and Visualization

Task 2.1: Data Visualization. In this task, the students are expected to (1) visualize the real world traffic data (i.e., goCard transactions) provided by TransLink and help staff to understand the passenger flow; (2) Find the relevance between traffic data and social events (e.g., major uni events). Students participating in this project are expected to have the following skills:

  • good Web development skills including both frontend and backend system development. A dashboard is expected to be implemented
  • good understanding of database management
  • experiences of data mining (INFS4203/7203) or related areas

Task 2.2: Traffic Prediction. Generally, students are required to model session-based traffic data with sequential model or graph model and estimate the variance of people flow. Students participating in this project are expected to have the following skills:

  • experiences of machine learning (COMP4702), data mining (INFS4203/7203; INFS7450), high-dimensional data processing (INFS4205/7205), information retrieval (INFS7410) or pattern recognition and analysis (INFS3710)
  • strong programming skills


Research Direction 2 - Content-based Image Understanding
Task 3 - Curb & Channel Crack Detection

Task 3.1: Road Scene Segmentation: Students are required to study pixel-labeling approaches using semantic segmentation for road scene understanding. Students participating in this project are expected to have the following skills:

  • image processing
  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), or pattern recognition and analysis (INFS3710)
  • Strong programming skills

Task 3.2: Crack Detection: Automatic detection of pavement cracks is an important task in transportation maintenance for driving safety assurance.However, it remains a challenging task due to the intensity inhomogeneity of cracks and complexity of the background, e.g., the low contrast with surrounding pavement and possible shadows with similar intensity. Students participating in this project are expected to have the following skills:

  • image processing
  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), pattern recognition and analysis (INFS3710)
  • Strong programming skills


Research Direction 3 - Deep Learning for Video Generation
Task 4 - Everybody Dance Now

Task 4.1 Dancing Video Generation Given a source picture (video) of a person dancing, this project aims to transfer that performance to a novel (amateur) target performing the same moves. Students participating in this project will investigate applying the Generative Adversarial Nets (GAN) to synthesize the target video based on the pose estimation from the source video and the feature extraction from the target image.

  • Deep Learning
  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), pattern recognition and analysis (INFS3710)
  • https://arxiv.org/abs/1808.07371, https://github.com/GordonRen/pose2pose

Task 5 - Super Slomo

Task 5.1 SlowMotion Video Generation Given two consecutive frames, video interpolation aims at generating intermediate frame(s) to form both spatially and temporally coherent video sequences. The purpose is to interpolate natural images between consecutive frames in a normal video. Students participating in this project will investigate applying Generative Adversarial Nets (GAN) to generate reasonable interval frames.

  • Deep Learning
  • experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), pattern recognition and analysis (INFS3710)
  • https://arxiv.org/abs/1712.00080, https://github.com/avinashpaliwal/Super-SloMo

2019 Sem 2, Thesis Project

Big Media Intelligence Super Project - Sem 2, 2019
15 students max

This super project consists of a series of independent tasks in large scale multimedia data analytics. Students will select ONE task from any research directions to undertake their thesis project.


Research Direction 1 - 3D Data Generation and Analysis

Task 1.1: Dataset Construction: In this task, the students are expected to (1) learn how to use Kinect and/or 3D scanner; (2) collect 3D meta-data for target objects (3) clean the data and store data into database (4) analyse statistics of collected datasets compared with existing datasets. Students participating in this project are expected to have the following skills: frontend (or) backend system development experiences, or experiences in 3D data processing, or experiences in image processing, and good programming skills

Task 1.2: Pattern Recognition for 3D Data: Generally, students are required to understand and improve state-of-the-art 3D object retrieval / 3D reconstruction algorithms. Students participating in this project are expected to have the following skills: experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205) strong programming skills


Research Direction 2 - Traffic Data Analysis

Task 2.1: Data Visualization: In this task, the students are expected to (1) visualize the real world traffic data provided by TransLink and help staffs to understand people flow; (2) Find the relevance between traffic data and social events (e.g., major uni events). Students participating in this project are expected to have the following skills: frontend (or) backend system development experiences (for data visualisation. A dashboard is expected to be implemented) good understanding of database management data mining (INFS4203/7203) good programming skills

Task 2.2: Traffic Prediction: Generally, students are required to model session-based traffic data with sequential model or graph model and estimate the variance of people flow. Students participating in this project are expected to have the following skills: experiences of machine learning (COMP4702), data mining (INFS4203/7203; INFS7450), high-dimensional data processing (INFS4205/7205), information retrieval (INFS7410) pattern recognition and analysis (INFS3710) strong programming skills


Research Direction 3 - E-health Data Analysis

Task 3.1: Sleep Data Analysis: Predict the sleep status (e.g., non-rapid eye movement (NREM)) with provided sensor data. Students participating in this project are expected to have the following skills: experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), pattern recognition and analysis (INFS3710) strong programming skills

Task 3.2: EGG Data Analysis: The students are expected to use electroencephalogram (EEG) data to detect fatigue during driving or under other scenarios. Students participating in this project are expected to have the following skills: experiences of machine learning (COMP4702), data mining (INFS4203/7203), high-dimensional data processing (INFS4205/7205), pattern recognition and analysis (INFS3710) strong programming skills


Research Direction 4 - Automatic Scientific Literature Analysis

Task 4.1: The students are expected to develop an intelligent scientific data exploration software that leverages natural language processing, data mining and machine learning techniques for automatic scientific literature analysis and implicit knowledge discovery. Students participating in this project are expected to have the following skills: frontend (or) backend system development experiences (for data visualisation. A dashboard is expected to be implemented) good understanding of database management data mining (INFS4203/7203; INFS7450) information retrieval (INFS7410) good programming skills

2018 Thesis Project (there is more to come ...)

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Hayley Faulkner

Now Pose! Makeup Transformation

This thesis explores various methods of improving the performance of a CycleGAN makeup transfer network on faces with pose. Generally, face transformation networks are mostly trained on fully-frontal images and lack the exibility to be able to perform well on faces with pose or profile images. Speciffically, this project investigates the impact of training with combinations of datasets with varying pose diversity, the affect of the generator architecture and the addition of facial feature segmentation masks to aid the network in it's transformations.

Learn More
Junhao Lin

Online Action Detection and Multi-Task Predictions with Kinect and Deep Learning

This work investigates online action analysis which is a crucial component for various real-time applications, based on the Kinect sensor and the popular deep learning approach these days. Skeleton data is the chosen modality rather than RGB or depth data, because of its low dimensionality as well as effectiveness shown in previous researches. In terms of neural networks, a RNN-based model has been selected which is suitable for sequence learning while having probably less complexity and shorter latency than CNN-based models.

Nhan Tri Luong

Action Recognition by Pose Estimation

His study investigates the sibility of using machine learning models to automate these processes. It works by training the models to recognize human actions in the videos and useiJ output to categorize videos or block offensive videos that contain inappropriate actions. The results showed that by combining different architectures, the accuracy of the whole system increased because more information was extracted from the videos.

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Zijian Wang

Deep Collaborative Supervised Hashing for Efficient Image Retrieval

This work investigates online action analysis which is a crucial component for various real-time applications, based on the Kinect sensor and the popular deep learning approach these days. Skeleton data is the chosen modality rather than RGB or depth data, because of its low dimensionality as well as effectiveness shown in previous researches.

Ryan Garthwaite

Temporal Action Recognition Via Pose Estimation

Action recognition from videos is an active area of research tackling wide ranging problems from violence in CCTV streams to monitoring disabled or elderly people for urgent medical situations. The goal of this project is to apply techniques of action recognition to the situation of human gesture recognition commonly performed in public speaking situations. The actions of clap, cough, wave and point are detected within untrimmed videos that may include multiple instances of these actions.

Shunjia Tao

An Intelligent Fashion Closet System

This study develops e-commercial website called fashion closet. Aside from developed user interface with general online shopping features, the recommendation algorithm is also developed for assisting people to get recommendation and find the clothes that close to their preference more easily.

Major Research Projects

  • ARC Discovery Project: Z. Huang, T. Chen, Y. Luo, S. Wang and S. Sadiq, "Embracing Changes for Responsive Video-sharing Services", Amount: $515,000 (2024-2026)
  • ARC Discovery Project: Z. Huang and G. Bai, "Responsible modelling respecting privacy, data quality, and green computing", Amount: $485,000 (2023-2025)
  • ARC Discovery Project: Z. Huang, "Deep Attribute-aware Hashing for Cross Retrieval", Amount: $262,000 (2019-2021)
  • University of Queensland Development Fellowship, "Deeply mining user online behaviour with social event influence" (2018 - 2021)
  • ARC Discovery Project: Z. Huang and H. Yin, "Monitoring Social Events for User Online Behaviour Analytics", Amount: $268,500 (2017-2019)
  • Advance Queensland Women's Academic Fund, 2016
  • ARC Discovery Project: X. Zhou, Z. Huang, S. Sadiq and D. Srivastava, "Declaration, Exploration, Enhancement and Provenance: The DEEP Approach to Data Quality Management Systems", Amount: $452,000 (2014-2016)
  • ARC Future Fellowship: Z. Huang, "Real-time Event Detection, Prediction, and Visualization for Emergency Response", Amount: $720,320 (2014-2017)
  • The University of Queensland: Z. Huang. ResTeach Grant. Amount: $41,000 (2012-2013)
  • ARC Australian Postdoctoral Fellowship (APD): Z. Huang, "Monitoring online topic evolvements with near-duplicate videos", Amount: $267,000 (2011-2013)
  • The University of Queensland, UQ Early Career Researcher Grant, Amount: $26,000 (2011)
  • The University of Queensland, ResTeach Grant, Amount: $35,000 (2010-2011)

Major Cross Disciplinary Projects

  • ARC Research Hub for Future Digital Manufacturing, Amount: $5M (2023-2027), Key personnel
  • ARC Training Centre in Predictive Breeding for Agricultural Futures, Amount: $5M (2023-2027), Key personnel
  • GRDC, Analytics for the Australian Grains Industry (AAGI), Amount: $12M (2023 - 2027)
  • Logan City Council, "Road Atlas: AI-power platform for automated road distress detection and asset management", Y. Luo and Z.Huang, Amount: $435,000 (2023 - 2026)
  • ARC Linkage Project, "Sewer Monitoring and Management in the Digital Era", D. Batstone, Z. Huang, et al., Amount: $880,000 (2022-2026)
  • Australian Academy of Technological Sciences and Engineering, "Developing a proof-of-concept self-contact tracing app to support epidemiological investigations and outbreak response" (Australia-Korea Joint Call for Joint Research Projects - ATSE Tech Bridge Grant), Z. Huang, et al., Amount: $128,500 (2022 - 2024)
  • ARC Centre of Excellence for Children and Families over the Life Course: Co-CI; Funding: $32.1 million over 7 years (media)
    • IEEE Fellow for contributions to multi-modal data management
    • ACM Distinguished Member for contributions to multimedia computing research
    • Lifetime Contriubtion Award, 2024 Australasian Database Conference
    • 2023 National Transport Research Organisation (NTRO) Local Government Innovation Award for the cutting edge work in the application of artificial intelligence in asset management area focusing on assets such as footpath considering a wide range of factors such as network condition level, mobility and access.
    • 2021 Outstanding Service to the ACM Multimedia Asia in recognition of the excellent contribution to ACM Multimedia Asia 2021, ACM Multimedia Asia Steering Committee
    • Excellence in Higher Degree by Research Supervision Award, University of Queensland, 2018 (media)
    • 2016 Chris Wallace Award from Computing Research and Education (CORE) Australasia for a notable breakthrough or a contribution of particular significance in Computer Science
    • 2014 Women in Technology (WiT) Infotech Research Award 2014, Queensland
    • ARC Future Fellow 2014
    • ARC Australian Postdoctoral Fellow 2011
    • Early Career Researcher Award, Faculty of Engineering, Architecture and Information Technology, The University of Queensland, 2011
    • Best Student Paper Award, 2023 ACM Multimedia Conference
    • Outstanding Research Award, 2023 ACM Multimedia Asia Conference
    • Best Paper Award, 2020 Australasian database Conference
    • Best Paper Award, 2018 Australasian database Conference
    • Best Paper Award, 2016 Australasian database Conference
    • Best Paper Award, the 14th International Conference on Web Information System Engineering (WISE 2013), 2013
    • Best Paper Award, the 17th International Conference on Database Systems for Advanced Applications (DASFAA 2012), 2012
    • Best Paper Award, 12th International Asia-Pacific Web Conference (APWeb), 2010

    Team Members' Awards and Recognitions

    • Outstanding Service Award, 2024 ACM Multimedia Conference
    • Best Demo Award, 2023 ACM Multimedia Conference
    • The 1st Place at the competition of CVPPA@ICCV'23: Image Classification of Nutrient Deficiencies in Winter Wheat and Winter Rye
    • Mahsa Baktash was awarded Future Fellowship (2023)
    • Yadan Luo was awarded DECRA Fellowship (2023)
    • Sen Wang was awarded Citations for Excellence in Student Learning, Faculty of EAIT (2021)
    • Yadan Luo was awarded the Google PhD Fellowship 2020 as a recognition of her research in the machine learning area and her strong potential of influencing the future of technology (2020)
    • Yadan Luo was awarded the ICT Young Achiever Award, Women in Technology (WiT.org) (2018)
    • Class of 2023 Valedictorian (Dec 2023, ITEE): Danny Wang
    • Class of 2022 Valedictorian (Dec 2022, ITEE): Djamahl Etchegaray
    • Class of 2022 Valedictorian (Jul 2022, ITEE): Yiyun Zhang
    • Class of 2021 Valedictorian (Dec 2021, ITEE): Ivan Zhuoxiao Chen
    • Class of 2019 Valedictorian (Dec 2019, ITEE): Junhao Lin
    • Class of 2018 Valedictorian (Dec 2018, ITEE): Khoi Phan media

    Steering Committee Member

    • International Conferences on Database Systems for Advanced Applications (2021 - )
    • Australasian Database Conferences (2022 - ), Chair

    Editorial Board Member

    • ACM transactions on Information Systems (TOIS) (2021 - )
    • Pattern Recognition Journal (2021 - )
    • IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) (2020 - 2023)
    • Foundations and Trends® in Information Retrieval (2019 - )
    • VLDB Journal (2018 - 2023)
    • IEEE Transactions on Multimedia (2024 - )

    Conference Chair (selected)

    • [PC Chair] The Web Conference 2025
    • [Plenary Chair] ACM Multimedia 2024
    • [PC Chair] ACM International Conference on Multimedia Retrieval (ICMR) 2023
    • [Demo Chair] ACM Multimedia 2023
    • [PC Chair] WISE: Web Information Systems Engineering 2022
    • [General Chair] ACM Multimedia Asia 2021
    • [PC Chair] The Conference on Information and Knowledge Management (CIKM) 2021
    • [Panel Chair] International Conference on Database Systems for Advanced Applications (DASFAA) 2021
    • [PC Chair] Australasian database Conference 2017

    Other Committees

    • Vice Chair for the Sydney ACM SIGMOD Chapter (2024 - )
    • Member of the Australian Research Council (ARC) College of Experts (2022 - )
    • Member of the VLDB Endowment Board of Trustees (2021 - )
    • Committee Chair for CORE Conference rankings in the field of Computer Vision and Multimedia Computation (2021)
    • Selection committee Chair for CORE Chris Wallace Award for Outstanding Research (2022 - )

    Reviewer

    • Australian Research Council Discovery Projects
    • External Ph.D. and MSc. theses reviewer for many Universities in Australia and overseas
    • Regular reviewers for a number of Australian and international journals, conferences

    Team members

    ...
    Mahsa Baktashmotlagh
    ARC Future Fellow
    Senior Lecturer
    ...
    Xin Yu
    DECRA
    Senior Lecturer
    ...
    Sen Wang
    DECRA
    Senior Lecturer
    ...
    Yadan Luo
    DECRA
    Lecturer
    ...
    Ruihong Qiu
    Postdoc
    ...
    Zhi Chen
    Postdoc
    ...
    Pengfei Zhang
    Postdoc
    ...
    Zijian Wang
    Postdoc

    Current Research Students

    ...
    Jason Zhao
    (Oct 2024 - )
    ...
    Boyu Luo
    (July 2024 - )
    ...
    Bowen Yuan
    (Jan 2024 - )
    ...
    Danny Wang
    (Jan 2024 - )
    ...
    Yan Jiang
    (Jan 2024 - )
    ...
    Yanran Tang
    (Jan 2023 - )
    ...
    Tianqi Wei
    (Jan 2023 - )
    ...
    Yilun Allen Liu
    (Jan 2023 - )
    ...
    Yiyun Zhang
    (July 2022 - )
    ...
    Ivan (Zhuoxiao) Chen
    (Jan 2022 - )

    Cross-disciplinary Collaborators

    ...
    Professor Scott Chapman
    Professor in Crop Physiology
    School of Agriculture and Food Sustainability
    Faculty of Science
    University of Queensland
    ...
    Professor Han Huang
    School of Mechanical and Mining Engineering
    Faculty of Engineering, Architecture and Information Technology
    University of Queensland
    ...
    Professor Lianzhou Wang
    ARC Laureate Fellow
    Australian Institute for Bioengineering and Nanotechnology
    Faculty of Engineering, Architecture and Information Technology
    University of Queensland
    ...
    Professor John Zhu
    School of Chemical Engineering
    Faculty of Engineering, Architecture and Information Technology
    University of Queensland
    ...
    Professor Zhiguo Yuan
    Chair Professor of Urban Water Management
    Director, JC STEM Lab of Sustainable Urban Water Management
    School of Energy and Environment
    City University of Hong Kong

    Previous Postdoc Research Fellow

    ...
    Dr Zheng Zhang
    (Sep 2018 - Sep 2018)
    Associate Professor
    Harbin Institute of Technology (Shen Zhen)
    ...
    Dr Jingjing Li
    (Oct 2016 - Oct 2017,
    Feb 2019 - Apr 2019)
    Professor
    University of Electronic Science and Technology of China
    ...
    Dr Weiqing Wang
    (Jul 2017 - Jun 2018)
    Lecturer
    Monash University
    ...
    Dr Lei Zhu
    (Aug 2016 - Aug 2017)
    Professor
    Shandong Normal University, China
    ...
    Dr Xiaoshuai Sun
    (Sep 2015 - Dec 2016)
    Associate Professor
    Xiamen University

    Completed Research Students

    ...
    Jiewei Cao
    (Feb 2015 - Aug 2018)
    Senior Research Scientist
    Bosch China
    ...
    Chao Li
    (Aug 2014 - May 2018)
    Buidu Research
    ...
    Hongyun Cai
    (Oct 2012 - Jul 2016)
    Senior Researcher at Tencent, China;
    Advanced Digital Sciences Center
    (ADSC), Singapore
    ...
    Xuefei Li
    (Apr 2012 - Mar 2016)
    Amazon Web Service, Canada
    ...
    MPhil Eve Belisle
    (Oct 2014 - Jun 2015)
    École Polytechnique de Montréal;
    a Canadian curler and amateur
    ornithologist from Montreal
    ...
    Ziwei Wang
    (Jul 2017 - Jul 2021)
    Postdoc
    CSIRO
    ...
    Luyao Liu
    (Jan 2017 - Jul 2021)
    ...
    Yadan Luo
    (Jan 2018 - Jul 2021)
    Postdoc
    The University of Queensland
    ...
    Jiasheng Duan
    (Oct 2018 - 2022)
    ...
    Ruihong Qiu
    (Jan 2019 - Sep 2022)
    Postdoc
    The University of Queensland
    ...
    Zhi Chen
    (Apr 2019 - Aug 2022)
    Postdoc
    The University of Queensland
    ...
    Yang Li
    (Jul 2018 - Oct 2022)
    Research Fellow
    CSIRO
    ...
    Mr Pengfei Zhang
    (Oct 2019 - July 2023)
    ...
    Mr Zijian Wang
    (Oct 2019 - July 2023)

    Address: Room 630, Building 78, The University of Queensland, St Lucia, Brisbane

    Website: https://staff.itee.uq.edu.au/huang/