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Dr Hao Xue

Dr Hao Xue

Postdoctoral Fellow
Engineering
Computer Science and Engineering

Dr Hao Xue is a Lecturer at the School of Computer Science and Engineering, UNSW Sydney. After obtaining his PhD from The University of Western Australia in 2020, he was a Research Fellow at the School of Computing Technologies, RMIT University (2020-2022). He was awarded the DAAD AInet Fellowship in 2022 and is a member of the Research Infrastructure Committee (Transport/Mobility Focus Area) at ADMS. His research interests include spatio-temporal data modelling, time series forecasting, and data-efficient time series representation learning. He has years of experience analysing human mobility behaviours and contributed to several research projects. He also serves as a program committee member for several esteemed conferences such as AAAI, CIKM, and NeurIPS. 
E-mail
hao.xue1@unsw.edu.au
  • Book Chapters | 2023
    Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, 'Continually Learning Out-of-Distribution Spatiotemporal Data for Robust Energy Forecasting', in , pp. 3 - 19, http://dx.doi.org/10.1007/978-3-031-43430-3_1
    Book Chapters | 2023
    Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, 'Correction to: Continually Learning Out-of-Distribution Spatiotemporal Data for Robust Energy Forecasting', in Lecture Notes in Computer Science, Springer Nature Switzerland, pp. C1 - C2, http://dx.doi.org/10.1007/978-3-031-43430-3_34
    Book Chapters | 2020
    Xue H; Huynh DQ; Reynolds M, 2020, 'Take a NAP: Non-Autoregressive Prediction for Pedestrian Trajectories', in , pp. 544 - 556, http://dx.doi.org/10.1007/978-3-030-63830-6_46
    Book Chapters | 2019
    Xue H; Huynh DQ; Reynolds M, 2019, 'Pedestrian Trajectory Prediction Using a Social Pyramid', in , pp. 439 - 453, http://dx.doi.org/10.1007/978-3-030-29911-8_34
    Book Chapters | 2016
    Sun P; Tian R; Xue H; Wan K, 2016, 'Development and analysis of police digital trunking channel technology of PDT', in , pp. 189 - 199, http://dx.doi.org/10.1007/978-81-322-2580-5_19
  • Journal articles | 2024
    Khaokaew Y; Xue H; Salim FD, 2024, 'MAPLE: Mobile App Prediction Leveraging Large Language Model Embeddings', Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 8, http://dx.doi.org/10.1145/3643514
    Journal articles | 2024
    Prabowo A; Xue H; Shao W; Koniusz P; Salim FD, 2024, 'Traffic forecasting on new roads using spatial contrastive pre-training (SCPT)', Data Mining and Knowledge Discovery, 38, pp. 913 - 937, http://dx.doi.org/10.1007/s10618-023-00982-0
    Journal articles | 2024
    Si Y; Xue H; Liao H; Xie Y; Xu DR; Kumi Smith M; Yip W; Cheng W; Tian J; Tang W; Sylvia S, 2024, 'The quality of telemedicine consultations for sexually transmitted infections in China', Health Policy and Planning, 39, pp. 307 - 317, http://dx.doi.org/10.1093/heapol/czad119
    Journal articles | 2024
    Wang Z; Jiang R; Xue H; Salim FD; Song X; Shibasaki R; Hu W; Wang S, 2024, 'Learning spatio-temporal dynamics on mobility networks for adaptation to open-world events', Artificial Intelligence, 335, http://dx.doi.org/10.1016/j.artint.2024.104120
    Journal articles | 2024
    Xue H; Salim FD, 2024, 'PromptCast: A New Prompt-Based Learning Paradigm for Time Series Forecasting', IEEE Transactions on Knowledge and Data Engineering, 36, pp. 6851 - 6864, http://dx.doi.org/10.1109/TKDE.2023.3342137
    Journal articles | 2024
    Züfle A; Salim F; Anderson T; Scotch M; Xiong L; Sokol K; Xue H; Kong R; Heslop D; Paik HY; Macintyre CR, 2024, 'Leveraging Simulation Data to Understand Bias in Predictive Models of Infectious Disease Spread', ACM Transactions on Spatial Algorithms and Systems, 10, http://dx.doi.org/10.1145/3660631
    Journal articles | 2022
    Deldari S; Xue H; Saeed A; Smith DV; Salim FD, 2022, 'COCOA: Cross Modality Contrastive Learning for Sensor Data', Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 6, http://dx.doi.org/10.1145/3550316
    Journal articles | 2022
    Gao N; Xue H; Shao W; Zhao S; Qin KK; Prabowo A; Rahaman MS; Salim FD, 2022, 'Generative Adversarial Networks for Spatio-temporal Data: A Survey', ACM Transactions on Intelligent Systems and Technology, 13, http://dx.doi.org/10.1145/3474838
    Journal articles | 2022
    Wang Z; Jiang R; Xue H; Salim FD; Song X; Shibasaki R, 2022, 'Event-Aware Multimodal Mobility Nowcasting', Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, 36, pp. 4228 - 4236, http://dx.doi.org/10.1609/aaai.v36i4.20342
    Journal articles | 2021
    Dong B; Liu Y; Fontenot H; Ouf M; Osman M; Chong A; Qin S; Salim F; Xue H; Yan D; Jin Y; Han M; Zhang X; Azar E; Carlucci S, 2021, 'Occupant behavior modeling methods for resilient building design, operation and policy at urban scale: A review', Applied Energy, 293, http://dx.doi.org/10.1016/j.apenergy.2021.116856
    Journal articles | 2021
    Xu L; Xue H; Bennamoun M; Boussaid F; Sohel F, 2021, 'Atrous convolutional feature network for weakly supervised semantic segmentation', Neurocomputing, 421, pp. 115 - 126, http://dx.doi.org/10.1016/j.neucom.2020.09.045
    Journal articles | 2021
    Xue H; Huynh DQ; Reynolds M, 2021, 'PoPPL: Pedestrian Trajectory Prediction by LSTM with Automatic Route Class Clustering', IEEE Transactions on Neural Networks and Learning Systems, 32, pp. 77 - 90, http://dx.doi.org/10.1109/TNNLS.2020.2975837
    Journal articles | 2021
    Yang X; Yu X; Xie L; Xue H; Zhou M; Jiang Q, 2021, 'Sleep Apnea Monitoring System Based on Commodity WiFi Devices', Computers, Materials and Continua, 69, pp. 2793 - 2806, http://dx.doi.org/10.32604/cmc.2021.016298
    Journal articles | 2020
    Xue H; Huynh DQ; Reynolds M, 2020, 'A Location-Velocity-Temporal Attention LSTM Model for Pedestrian Trajectory Prediction', IEEE Access, 8, pp. 44576 - 44589, http://dx.doi.org/10.1109/ACCESS.2020.2977747
    Journal articles | 2016
    Feng G; Ma L; Tan X; Xue H; Guan K, 2016, 'Visual Location Recognition Based on Coarse-to-Fine Image Retrieval and Epipolar Geometry Constraint for Urban Environment', International Journal of Signal Processing, Image Processing and Pattern Recognition, 9, pp. 25 - 36, http://dx.doi.org/10.14257/ijsip.2016.9.11.03
  • Preprints | 2025
    Ju C; Liu J; Sinha S; Xue H; Salim F, 2025, TrajLLM: A Modular LLM-Enhanced Agent-Based Framework for Realistic Human Trajectory Simulation, http://arxiv.org/abs/2502.18712v1
    Conference Papers | 2024
    Khaokaew Y; Xue H; Rahaman MS; Salim FD, 2024, 'WorkR: Occupation Inference for Intelligent Task Assistance', in ISWC 2024 - Proceedings of the 2024 ACM International Symposium on Wearable Computers, pp. 118 - 124, http://dx.doi.org/10.1145/3675095.3676622
    Preprints | 2024
    Khaokaew Y; Xue H; Rahaman MS; Salim FD, 2024, WorkR: Occupation Inference for Intelligent Task Assistance, http://dx.doi.org/10.48550/arxiv.2407.18518
    Conference Papers | 2024
    Li L; Xue H; Song Y; Salim F, 2024, 'T-JEPA: A Joint-Embedding Predictive Architecture for Trajectory Similarity Computation', in 32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL 2024, pp. 569 - 572, http://dx.doi.org/10.1145/3678717.3691271
    Preprints | 2024
    Li L; Xue H; Song Y; Salim F, 2024, T-JEPA: A Joint-Embedding Predictive Architecture for Trajectory Similarity Computation, http://dx.doi.org/10.48550/arxiv.2406.12913
    Conference Papers | 2024
    Li P; De Rijke M; Xue H; Ao S; Song Y; Salim FD, 2024, 'Large Language Models for Next Point-of-Interest Recommendation', in SIGIR 2024 - Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1463 - 1472, http://dx.doi.org/10.1145/3626772.3657840
    Preprints | 2024
    Li P; Rijke MD; Xue H; Ao S; Song Y; Salim FD, 2024, Large Language Models for Next Point-of-Interest Recommendation, http://dx.doi.org/10.1145/3626772.3657840
    Preprints | 2024
    Lin X; Prabowo A; Razzak I; Xue H; Amos M; Behrens S; Salim FD, 2024, A Gap in Time: The Challenge of Processing Heterogeneous IoT Data in Digitalized Buildings, http://dx.doi.org/10.48550/arxiv.2405.14267
    Preprints | 2024
    Prabowo A; Lin X; Razzak I; Xue H; Yap EW; Amos M; Salim FD, 2024, BTS: Building Timeseries Dataset: Empowering Large-Scale Building Analytics, http://arxiv.org/abs/2406.08990v2
    Conference Papers | 2024
    Xue H; Tang T; Payani A; Salim FD, 2024, 'Prompt Mining for Language Models-based Mobility Flow Forecasting', in Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, ACM, pp. 113 - 122, presented at SIGSPATIAL '24: The 32nd ACM International Conference on Advances in Geographic Information Systems, http://dx.doi.org/10.1145/3678717.3691232
    Preprints | 2024
    Xue H; Tang T; Payani A; Salim FD, 2024, Prompt Mining for Language-based Human Mobility Forecasting, http://arxiv.org/abs/2403.03544v1
    Conference Papers | 2024
    Yang R; Salim FD; Xue H, 2024, 'SSTKG: Simple Spatio-Temporal Knowledge Graph for Intepretable and Versatile Dynamic Information Embedding', in WWW 2024 - Proceedings of the ACM Web Conference, pp. 551 - 559, http://dx.doi.org/10.1145/3589334.3645441
    Preprints | 2024
    Yang R; Salim FD; Xue H, 2024, SSTKG: Simple Spatio-Temporal Knowledge Graph for Intepretable and Versatile Dynamic Information Embedding, , http://arxiv.org/abs/2402.12132v1
    Conference Papers | 2024
    Yin D; Deng J; Ao S; Li Z; Xue H; Prabowo A; Jiang R; Song X; Salim F, 2024, 'Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned', in Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, ACM, pp. 42 - 53, presented at SIGSPATIAL '24: The 32nd ACM International Conference on Advances in Geographic Information Systems, http://dx.doi.org/10.1145/3678717.3691216
    Preprints | 2024
    Yin D; Deng J; Ao S; Li Z; Xue H; Prabowo A; Jiang R; Song X; Salim F, 2024, Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned, http://dx.doi.org/10.48550/arxiv.2406.12709
    Conference Papers | 2023
    Khaokaew Y; Salim FD; Xue H, 2023, 'Understanding Mobile Information Needs and Behaviours', in UbiComp/ISWC 2023 Adjunct - Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2023 ACM International Symposium on Wearable Computing, pp. 210 - 214, http://dx.doi.org/10.1145/3594739.3610760
    Preprints | 2023
    Khaokaew Y; Xue H; Salim FD, 2023, MAPLE: Mobile App Prediction Leveraging Large Language Model Embeddings, http://dx.doi.org/10.48550/arxiv.2309.08648
    Conference Papers | 2023
    Liu J; Deldari S; Xue H; Nguyen V; Salim FD, 2023, 'Self-supervised Activity Representation Learning with Incremental Data: An Empirical Study', in Proceedings - IEEE International Conference on Mobile Data Management, pp. 39 - 44, http://dx.doi.org/10.1109/MDM58254.2023.00019
    Preprints | 2023
    Liu J; Deldari S; Xue H; Nguyen V; Salim FD, 2023, Self-supervised Activity Representation Learning with Incremental Data: An Empirical Study, http://dx.doi.org/10.48550/arxiv.2305.00619
    Conference Papers | 2023
    Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, 'Navigating Out-of-Distribution Electricity Load Forecasting during COVID-19: Benchmarking energy load forecasting models without and with continual learning', in BuildSys 2023 - Proceedings of the10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, pp. 41 - 50, http://dx.doi.org/10.1145/3600100.3623726
    Preprints | 2023
    Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, Continually learning out-of-distribution spatiotemporal data for robust energy forecasting, http://dx.doi.org/10.1007/978-3-031-43430-3_1
    Preprints | 2023
    Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, Navigating Out-of-Distribution Electricity Load Forecasting during COVID-19: Benchmarking energy load forecasting models without and with continual learning, http://dx.doi.org/10.1145/3600100.3623726
    Conference Papers | 2023
    Prabowo A; Shao W; Xue H; Koniusz P; Salim FD, 2023, 'Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting', in ACM International Conference Proceeding Series, pp. 93 - 104, http://dx.doi.org/10.1145/3576842.3582362
    Preprints | 2023
    Prabowo A; Shao W; Xue H; Koniusz P; Salim FD, 2023, Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting, http://dx.doi.org/10.1145/3576842.3582362
    Preprints | 2023
    Prabowo A; Xue H; Shao W; Koniusz P; Salim FD, 2023, Message Passing Neural Networks for Traffic Forecasting, http://arxiv.org/abs/2305.05740v1
    Preprints | 2023
    Prabowo A; Xue H; Shao W; Koniusz P; Salim FD, 2023, Traffic Forecasting on New Roads Using Spatial Contrastive Pre-Training (SCPT), http://dx.doi.org/10.1007/s10618-023-00982-0
    Conference Papers | 2023
    Xue H; Salim FD, 2023, 'Artificial General Intelligence for Human Mobility (Vision Paper)', in GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, http://dx.doi.org/10.1145/3589132.3625652
    Conference Papers | 2023
    Xue H; Salim FD, 2023, 'Utilizing Language Models for Energy Load Forecasting', in BuildSys 2023 - Proceedings of the10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, pp. 224 - 227, http://dx.doi.org/10.1145/3600100.3623730
    Preprints | 2023
    Xue H; Salim FD, 2023, Human Mobility Question Answering (Vision Paper), http://arxiv.org/abs/2310.04443v2
    Preprints | 2023
    Xue H; Salim FD, 2023, Utilizing Language Models for Energy Load Forecasting, http://arxiv.org/abs/2310.17788v1
    Preprints | 2022
    Abushaqra FM; Xue H; Ren Y; Salim FD, 2022, SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time Series, , http://arxiv.org/abs/2212.03560v3
    Preprints | 2022
    Deldari S; Xue H; Saeed A; He J; Smith DV; Salim FD, 2022, Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data, http://arxiv.org/abs/2206.02353v2
    Preprints | 2022
    Deldari S; Xue H; Saeed A; Smith DV; Salim FD, 2022, COCOA: Cross Modality Contrastive Learning for Sensor Data, http://dx.doi.org/10.1145/3550316
    Conference Papers | 2022
    Xue H; Salim FD; Ren Y; Clarke CLA, 2022, 'Translating human mobility forecasting through natural language generation', in WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining, pp. 1224 - 1233, http://dx.doi.org/10.1145/3488560.3498387
    Preprints | 2022
    Xue H; Salim FD, 2022, PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecasting, http://arxiv.org/abs/2210.08964v5
    Conference Papers | 2022
    Xue H; Voutharoja BP; Salim FD, 2022, 'Leveraging language foundation models for human mobility forecasting', in GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, http://dx.doi.org/10.1145/3557915.3561026
    Preprints | 2022
    Xue H; Voutharoja BP; Salim FD, 2022, Leveraging Language Foundation Models for Human Mobility Forecasting, , http://arxiv.org/abs/2209.05479v2
    Conference Papers | 2021
    Abushaqra FM; Xue H; Ren Y; Salim FD, 2021, 'PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series', in Proceedings - IEEE International Conference on Data Mining, ICDM, pp. 976 - 981, http://dx.doi.org/10.1109/ICDM51629.2021.00109
    Preprints | 2021
    Abushaqra FM; Xue H; Ren Y; Salim FD, 2021, PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series, , http://arxiv.org/abs/2110.00071v2
    Conference Papers | 2021
    Deldari S; Smith DV; Xue H; Salim FD, 2021, 'Time series change point detection with self-supervised contrastive predictive coding', in The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021, pp. 3124 - 3135, http://dx.doi.org/10.1145/3442381.3449903
    Preprints | 2021
    Wang Z; Jiang R; Xue H; Salim FD; Song X; Shibasaki R, 2021, Event-Aware Multimodal Mobility Nowcasting, , http://arxiv.org/abs/2112.08443v1
    Preprints | 2021
    Xue H; Salim FD; Ren Y; Clarke CLA, 2021, Translating Human Mobility Forecasting through Natural Language Generation, , http://arxiv.org/abs/2112.11481v1
    Conference Papers | 2021
    Xue H; Salim FD; Ren Y; Oliver N, 2021, 'MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction', in Advances in Neural Information Processing Systems, pp. 30380 - 30391
    Preprints | 2021
    Xue H; Salim FD; Ren Y; Oliver N, 2021, MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction, , http://arxiv.org/abs/2110.01401v1
    Conference Papers | 2021
    Xue H; Salim FD, 2021, 'Exploring Self-Supervised Representation Ensembles for COVID-19 Cough Classification', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1944 - 1952, http://dx.doi.org/10.1145/3447548.3467263
    Conference Papers | 2021
    Xue H; Salim FD, 2021, 'TERMCast: Temporal Relation Modeling for Effective Urban Flow Forecasting', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 741 - 753, http://dx.doi.org/10.1007/978-3-030-75762-5_58
    Preprints | 2021
    Xue H; Salim FD, 2021, Exploring Self-Supervised Representation Ensembles for COVID-19 Cough Classification, http://dx.doi.org/10.1145/3447548.3467263
    Preprints | 2020
    Deldari S; Smith DV; Xue H; Salim FD, 2020, Time Series Change Point Detection with Self-Supervised Contrastive Predictive Coding, http://dx.doi.org/10.1145/3442381.3449903
    Preprints | 2020
    Gao N; Xue H; Shao W; Zhao S; Qin KK; Prabowo A; Rahaman MS; Salim FD, 2020, Generative Adversarial Networks for Spatio-temporal Data: A Survey, http://dx.doi.org/10.1145/3474838
    Preprints | 2020
    Xue H; Huynh DQ; Reynolds M, 2020, Scene Gated Social Graph: Pedestrian Trajectory Prediction Based on Dynamic Social Graphs and Scene Constraints, , http://arxiv.org/abs/2010.05507v1
    Preprints | 2020
    Xue H; Huynh DQ; Reynolds M, 2020, Take a NAP: Non-Autoregressive Prediction for Pedestrian Trajectories, , http://arxiv.org/abs/2004.09760v1
    Preprints | 2020
    Xue H; Salim FD, 2020, TERMCast: Temporal Relation Modeling for Effective Urban Flow Forecasting, http://dx.doi.org/10.1007/978-3-030-75762-5_58
    Conference Papers | 2019
    Xue H; Huynh DQ; Reynolds M, 2019, 'Location-velocity attention for pedestrian trajectory prediction', in Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019, pp. 2038 - 2047, http://dx.doi.org/10.1109/WACV.2019.00221
    Conference Papers | 2019
    Xue H; Huynh DQ; Reynolds M, 2019, 'Pedestrian tracking and stereo matching of tracklets for autonomous vehicles', in IEEE Vehicular Technology Conference, http://dx.doi.org/10.1109/VTCSpring.2019.8746329
    Conference Papers | 2018
    Xue H; Huynh DQ; Reynolds M, 2018, 'SS-LSTM: A Hierarchical LSTM Model for Pedestrian Trajectory Prediction', in Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018, pp. 1186 - 1194, http://dx.doi.org/10.1109/WACV.2018.00135
    Conference Papers | 2017
    Ma L; Xue H; Jia T; Tan X, 2017, 'A Fast C-GIST Based Image Retrieval Method for Vision-Based Indoor Localization', in IEEE Vehicular Technology Conference, http://dx.doi.org/10.1109/VTCSpring.2017.8108338
    Conference Papers | 2017
    Xue H; Huynh DQ; Reynolds M, 2017, 'Bi-prediction: Pedestrian trajectory prediction based on bidirectional LSTM classification', in DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications, pp. 1 - 8, http://dx.doi.org/10.1109/DICTA.2017.8227412
    Conference Papers | 2016
    Xue H; Ma L; Tan X, 2016, 'A fast visual map building method using video stream for visual-based indoor localization', in 2016 International Wireless Communications and Mobile Computing Conference, IWCMC 2016, pp. 650 - 654, http://dx.doi.org/10.1109/IWCMC.2016.7577133

DAAD AInet Fellowship 2022