By Dr Arian Prabowo

Books

Prabowo A; Chen K; Xue H; Sethuvenkatraman S; Salim FD, 2023, Correction to: Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track (LNAI 14175 (10.1007/978-3-031-43430-3_1)), http://dx.doi.org/10.1007/978-3-031-43430-3_34

Book Chapters

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

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

Journal articles

Lin X; Prabowo A; Razzak I; Xue H; Amos M; Behrens S; Salim FD, 2025, 'A Gap in Time: The Challenge of Processing Heterogeneous IoT Data in Digitalized Buildings', IEEE Pervasive Computing, http://dx.doi.org/10.1109/MPRV.2025.3542061

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

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

Shao W; Prabowo A; Zhao S; Koniusz P; Salim FD, 2022, 'Predicting flight delay with spatio-temporal trajectory convolutional network and airport situational awareness map', Neurocomputing, 472, pp. 280 - 293, http://dx.doi.org/10.1016/j.neucom.2021.04.136

Conference Papers

Prabowo A; Lin X; Razzak I; Xue H; Amos M; White SD; Salim FD, 2025, 'Brick-by-Brick: Cyber-Physical Building Data Classification Challenge', in Companion Proceedings of the ACM on Web Conference 2025, ACM, pp. 3021 - 3025, presented at WWW '25: The ACM Web Conference 2025, http://dx.doi.org/10.1145/3701716.3718483

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 32nd ACM Sigspatial International Conference on Advances in Geographic Information Systems ACM Sigspatial 2024, pp. 42 - 53, http://dx.doi.org/10.1145/3678717.3691216

Lin X; Prabowo A; Razzak I; Xue H; Amos M; Behrens S; Salim FD, 2024, 'BiTSA: Leveraging Time Series Foundation Model for Building Energy Analytics', in IEEE International Conference on Data Mining Workshops Icdmw, pp. 891 - 894, http://dx.doi.org/10.1109/ICDMW65004.2024.00122

Prabowo A; Lin X; Razzak I; Xue H; Yap EW; Amos M; Salim FD, 2024, 'BTS: Building Timeseries Dataset: Empowering Large-Scale Building Analytics', in Advances in Neural Information Processing Systems

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

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

Prabowo A; Koniusz P; Shao W; Salim FD, 2019, 'COLTRANE: ConvolutiOnaL TRAjectory network for deep map inference', in Buildsys 2019 Proceedings of the 6th ACM International Conference on Systems for Energy Efficient Buildings Cities and Transportation, pp. 21 - 30, http://dx.doi.org/10.1145/3360322.3360853

Shao W; Prabowo A; Zhao S; Tan S; Koniusz P; Chan J; Hei X; Feest B; Salim FD, 2019, 'Flight delay prediction using airport situational awareness map', in GIS Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, pp. 432 - 435, http://dx.doi.org/10.1145/3347146.3359079

Preprints

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

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

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

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

Prabowo A; Xue H; Shao W; Koniusz P; Salim FD, 2023, Message Passing Neural Networks for Traffic Forecasting, http://arxiv.org/abs/2305.05740v1

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

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

Shao W; Prabowo A; Zhao S; Koniusz P; Salim FD, 2021, Predicting Flight Delay with Spatio-Temporal Trajectory Convolutional Network and Airport Situational Awareness Map, http://dx.doi.org/10.1016/j.neucom.2021.04.136

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

Shao W; Prabowo A; Zhao S; Tan S; Konuiusz P; Chan J; Hei X; Feest B; Salim FD, 2019, Flight Delay Prediction using Airport Situational Awareness Map, http://arxiv.org/abs/1911.01605v1

Prabowo A; Koniusz P; Shao W; Salim FD, 2019, COLTRANE: ConvolutiOnaL TRAjectory NEtwork for Deep Map Inference, http://dx.doi.org/10.1145/3360322.3360853

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