Conference Publications

  1. F. Chen, D. Wang, J. He, S. Lei and C.T. Lu, “Optimizing Transit Network Expansion with Gated Attentive Graph Reinforcement Learning,” Proceeding of the 2022 SIAM International Conference on Data Mining (SIAM DM), Alexandria, Virginia, May 1-3, 2025. (Acceptance rate: 26.7%)

  2. M.Y, Aktas, T. Ji, C.T. Lu, “Time Series Forecasting with GCN-LSTM Based Unified Model for Product Demand Prediction,” Proceedings of the 2024 IEEE International Conference on Big Data (IEEE BigData), Special Session: Machine Learning on Big Data (MLBD 2024), pp. 5901-5906, Washington, DC, Dec. 15-18, 2024. DOI: 10.1109/BigData62323.2024.10825969
  3. R. Lyu, L. Wang, Y. Sun, H. Bai, and C.T. Lu, “Downscaling Precipitation with Bias-informed Conditional Diffusion Model,” Proceedings of the 2024 IEEE International Conference on Big Data (IEEE BigData), pp. 8768-8770, Washington, DC, Dec. 15-18, 2024. DOI: 10.1109/BigData62323.2024.10825056
  4. Y. Sun, J. Yu, C.T. Lu, “Empowering Cross-Patient Epilepsy Diagnosis from Diverse-Sampling Low-Quality EEG Signals,” Proceedings of the 2024 IEEE International Conference on Bioinformatics and Biomedicine(BIBM), pp. 2460-2467, Dec. 3-6, 2024. (Acceptance rate: 20%) DOI: 10.1109/BIBM62325.2024.10822406 (Best Student Paper Award)
  5. L. Wang, K. Cheng, S. Lei, S. Wang, W. Yin, C. Lei, X. Long, C.T. Lu, “DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam Videos,” Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), pp. 99898-99920, Vancouver, Canada, Dec. 9-15, 2024. Slides, GitHub: https://linhanwang.github.io/dcgaussian/
  6. M. ALMutairi, L. AlKulaib, S. Wang, Z. Chen, Y. ALMutiari, T. M. Alenazi, K. Luther, C.T. Lu, “FHIRViz: Multi-Agent Platform for FHIR Visualization to Advance Healthcare Analytics,” Proceedgins of the 15th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Article No.: 38, pp. 1-7. Shenzhen, China, Nov. 22-25, 2024. DOI: https://doi.org/10.1145/3698587.3701392
  7. M. Beigi, Y. Shen, R. Yang, Z. Lin, Q, Wang, A. Mohan, J. He, M. Jin, C.T. Lu, L. Huang, “InternalInspector I2: Robust Confidence Estimation in LLMs through Internal States,” Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 12847–12865, Miami, Florida, Nov. 12-16, 2024. DOI: 10.18653/v1/2024.findings-emnlp.751
  8. J. He, R. Yang, L. Yu, C. Li, R. Jia, F. Chen, M. Jin, C.T. Lu, “Can We Trust the Performance Evaluation of Uncertainty Estimation Methods in Text Summarization?” Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 16514–16575, Miami, Florida, Nov. 12-16, 2024. DOI: 10.18653/v1/2024.emnlp-main.923
  9. A. Alhamadani, K. Althubiti, J. He, S. Sarkar, L. Alkulaib, A.R. Shaik, S. Lee, M. Khan, C.T. Lu, “Empowering Airline Route Decisions with LLMGenerated Pseudo-Labels and Zero-Shot Review Prediction,” Proceedings of the 2024 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 119-136, Calabria, Italy, Sept. 02-05, 2024. DOI: https://doi.org/10.1007/978-3-031-78554-2_8
  10. A.R. Shaik, A. Alhamadani, S. Sarkar, C.T. Lu, “Optimizing Airline Destinations with AIRNODE: A Graph Attention Network Approach,” Proceedings of the 2024 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 154-170, Calabria, Italy, Sept. 02-05, 2024. DOI: https://doi.org/10.1007/978-3-031-78554-2_10
  11. A. Khatri, N. Egierski, A. Pochamreddy, A. Alhamadani, S. Sarkar and C.T. Lu, “IntelliSMART: Intelligent Semantic Machine-Assisted Research Tool,” Proceedings of the 2024 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 187-196, Calabria, Italy, September 02-05, 2024. DOI: https://doi.org/10.1007/978-3-031-78554-2_12
  12. M.Y. Aktas, A. Khatri, M. Almutairi, L. Alkulaib, C.T. Lu, “Enhancing School Success Prediction with FRC and Merged GNN,” Proceedings of the 2024 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 262-277, Calabria, Italy, Sept. 02-05, 2024.
  13. L. AlKulaib, and C.T. Lu, “HyperSMOTE-MC: Enhancing Multiclass Bot Detection on X through Hypergraph-based Resampling,” Proceedings of the 2024 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 171-186, Calabria, Italy, Sept. 02-05, 2024. DOI: https://doi.org/10.1007/978-3-031-78554-2_11
  14. M. ALMutairi, L. AlKulaib, M. Aktas, S. Alsalamah, C.T. Lu, “Synthetic Arabic Medical Dialogues Using Advanced Multi-Agent LLM Techniques,” Proceedings of the Second Arabic Natural Language Processing Conference, pp. 11-26, Bangkok, Thailand, Aug. 16, 2024. DOI: 10.18653/v1/2024.arabicnlp-1.2
  15. M. Zhang, J. He, T. Ji, C.T. Lu, “Don't Go to Extremes: Revealing the Excessive Sensitivity and Calibration Limitations of LLMs in Implicit Hate Speech Detection,” Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), pp. 12073–12086, Bangkok, Thailand, Aug. 11–16, 2024. DOI: 10.18653/v1/2024.acl-long.652
  16. J. He, L. Yu, S. Lei, C.T. Lu, F. Chen, “Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission,” Findings of the Association for Computational Linguistics: Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), pp. 2823–2835, Mexico City, Mexico, June 2024. DOI: 10.18653/v1/2024.findings-naacl.180
  17. S. Wang, T. Ji, J. He, M. Almutairi, D. Wang, L. Wang, M. Zhang, C.T. Lu, “AMA-LSTM: Pioneering Robust and Fair Financial Audio Analysis for Stock Volatility Prediction,” Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), pp. 379-386, 2024. DOI: 10.18653/v1/2024.naacl-industry.32
  18. S. Chen, Yanshen Sun, Peihan Li, Lifeng Zhou, C.T. Lu, “Learning Decentralized Flocking Controllers with Spatio-Temporal Graph Neural Network,” Proceedings of the 2024 IEEE International Conference on Robotics and Automation (ICRA), May 13-17, 2024, Yokohama, Japan. DOI: 10.1109/ICRA57147.2024.10610627
  19. R. Shang, S. Chen, Z. Chen, C.T. Lu, “GraphNILM: A Graph Neural Network for Energy Disaggregation” Proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 431-443, Taipei, Taiwan, May 7-10, 2024. DOI: https://doi.org/10.1007/978-981-97-2253-2_34
  20. M. Zhang, J. He, S. Lei, M. Yue, L. Wang, C.T. Lu, “Can LLM Find the Green Circle? Investigating Human-Guided Tool Manipulation for Compositional Generalization,” Proceedings of the 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024), Seoul, Korea, April 14-19, 2024. DOI: 10.1109/ICASSP48485.2024.10446355

  21. M.Y. Aktas, L. AlKulaib, C.T. Lu, “UniMHe: Unified Multi Hyperedge Prediction A Case Study on Crime Dataset,” Proceedings of the 2023 IEEE International Conference on Big Data, Special Session: Machine Learning on Big Data (MLBD 2023), pp. 5134-5139, Sorrento, Italy, December 15-18, 2023. DOI: 10.1109/BigData59044.2023.10386448
  22. L. AlKulaib, C.T. Lu, “Balancing the Scales: HyperSMOTE for Enhanced Hypergraph Classification,” Proceedings of the 2023 IEEE International Conference on Big Data, Special Session: Machine Learning on Big Data (MLBD 2023), pp. 5140-5145, Sorrento, Italy, December 15-18, 2023. DOI: 10.1109/BigData59044.2023.10386107
  23. R. Zhang, S. Sarkar, A. Alhamadani, C.T. Lu, “More than Just a Diagnosis: A Multi-Task Approach to Analyzing Bipolar Disorder on Reddit via DeMHeM,” Proceedings of the 2023 IEEE International Conference on Big Data, Special Session: HealthCare Data, pp. 5014-5023, Sorrento, Italy, December 15-18, 2023. DOI: 10.1109/BigData59044.2023.10386934
  24. Y. Sun, K. Fu, C.T. Lu, “RoadFormer: Road-Anchored Adversarial Dynamic Graph Transformer for Unlimited-Range Traffic Incident Impact Prediction,” Proceedings of the 2023 IEEE International Conference on Big Data, Sorrento, Italy, pp. 895-904, December 15-18, 2023. (Acceptance rate: 17.5%, Regular Paper) DOI: 10.1109/BigData59044.2023.10386290
  25. S. Wang, Y.X. Bai, T. Ji, K. Fu, L. Wang, C.T. Lu, “Stock Movement and Volatility Prediction from Tweets, Macroeconomic Factors and Historical Prices,” Proceedings of the 2023 IEEE International Conference on Big Data, pp. 1863-1872, Sorrento, Italy, December 15-18, 2023. DOI: 10.1109/BigData59044.2023.10386368
  26. A. Alhamadani, X. Zhang, J. He, A. Khatri, C.T. Lu, “LANS: Large-scale Arabic News Summarization Corpus,” Proceedings of the 1st Arabic Natural Language Processing Conference, Singapore, December 7, 2023.
  27. Y. Sun, J. Yu, C.T. Lu, “LightK-DSGCN: Depression Detection in EEGs with Lightweight Kalman Filter-aided Dual-Stream Graph Convolutional Networks,” Proceedings of the 2023 IEEE International Conference on Bioinformatics and Biomedicine(BIBM), pp. 1429-1436, Dec. 5-8, 2023. (Acceptance rate: 19.5%, Regular Paper) DOI: 10.1109/BIBM58861.2023.10385659
  28. L. Zhang, Q. Zhang, Z. Chen, Y. Sun, C.T. Lu, L. Zhao, “Infinitely Deep Graph Transformation Networks,” Proceedings of the 23rd IEEE International Conference on Data Mining (ICDM), pp. 778-787, Dec. 1-4, 2023. (Acceptance rate: 9.37%, Regular Paper) DOI: 10.1109/ICDM58522.2023.00087
  29. A. Alhamadani, K. Althubiti, S. Sarkar, J. He, L. Alkulaib, S. Behal, M. Khan, C.T. Lu, “From Guest to Family: An Innovative Framework for Enhancing Memorable Experiences in the Hotel Industry,” Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 492-501, Kusadasi, Turkey, Nov. 6-9, 2023. DOI: https://doi.org/10.1145/3625007.3632331
  30. S. Wang, Y. Bai, K. Fu, L. Wang, C.T. Lu, T. Ji, “ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction,” Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 538-542, Kusadasi, Turkey, Nov. 6-9, 2023. DOI: https://doi.org/10.1145/3625007.3627488
  31. L. Alkulaib, A. Alhamadani, S. Sarkar and C.T. Lu, “Hypergraph Text Classification for Mental Health Misleading Advice,” Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 522-529, Kusadasi, Turkey, Nov. 6-9, 2023. DOI: https://doi.org/10.1145/3625007.3627500
  32. L. Wang, S. Lei, J. He, S. Wang, M. Zhang, C.T. Lu, “Self-Correlation and Cross-Correlation Learning for Few-Shot Remote Sensing Image Semantic Segmentation,” Proceedings of the 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Article No.: 25, Pages 1-10, Hamburg, Germany, Nov. 13-16, 2023. DOI: https://doi.org/10.1145/3589132.3625570 (Acceptance rate: 20%)
  33. S. Chen, Y. Sun, P. Li, L. Zhou, C.T. Lu, “Spatial Temporal Graph Neural Networks for Decentralized Control of Robot Swarms (Demo Paper),” Proceedings of the 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Article No.: 80, Pages 1-4, Hamburg, Germany, Nov. 13-16, 2023. DOI: https://doi.org/10.1145/3589132.3625630
  34. J. He, X. Zhang, S. Lei, A. Alhamadani, F. Chen, B. Xiao, C.T. Lu, “CLUR: Uncertainty Estimation for Few-Shot Text Classification with Contrastive Learning,” Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 698–710, Long Beach, CA, Aug. 6-10, 2023. (Acceptance rate: 22%) (Slides) DOI: https://doi.org/10.1145/3580305.3599276
  35. S. Lei, X. Zhang, J. He, F. Chen and C.T. Lu, “TART: Improved Few-shot Text Classification Using Task-Adaptive Reference Transformation,” Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp.11014–11026, Toronto, Canada, July 9-14, 2023. DOI: 10.18653/v1/2023.acl-long.617
  36. J. He, S.Y. Wu, A. Alhamadani, C.F. Chen, W.F. Lu, C.T. Lu, D. Solnick, Y. Li, “MetroScope: An Advanced System for Real-Time Detection and Analysis of Metro-Related Threats and Events via Twitter,” Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 3130-3134, July 23-27, Taipei, Taiwan, 2023. (Poster) Link-1, Link-2 DOI: https://doi.org/10.1145/3539618.3591807
  37. F. Chen, S. Biswas, Z. Chen, S. Lei, N. Ramakrishnan, C.T. Lu, “Exploring Tradeoffs in Automated School Redistricting: Computational and Ethical Perspectives,” Proceedings of the AAAI Conference on Artificial Intelligence, EAAI Symposium, 37(13), pp.15912-15920, February 26-27, 2023. (Slides, Interview) DOI: https://doi.org/10.1609/aaai.v37i13.26889

  38. C. Duong, L. Zhang, and C.T. Lu, “HateNet: A Graph Convolutional Network Approach to Hate Speech Detection,” Proceedings of the 2022 IEEE International Conference on Big Data (IEEE BigData)-Special Session on Privacy and Security of Big Data, pp. 5698-5707, 2022. DOI: 10.1109/BigData55660.2022.10020510
  39. A. Alhamadani, S. Sarkar, L. Alkulaib, and C.T. Lu, “DOD-Explainer: Explainable Drug Overdose Deaths Predictor from Crime and Socioeconomic Data,” Proceedings of the 2022 IEEE International Conference on Big Data (IEEE BigData)-Special Session on HealthCare Data, pp. 5153-5162, 2022. DOI: 10.1109/BigData55660.2022.10021054
  40. S.A. Alsalamah, S. AlSalamah, W.N. Ismail, H. Alsalamah, and C.T. Lu, “Building a Patient-Centered Virtual Hospital Ecosystem Using Both Access Control and CNN-Based Models,” Proceedings of the 2022 IEEE International Conference on Big Data (IEEE BigData)-Special Session on HealthCare Data, pp. 5190-5199, 2022. DOI: 10.1109/BigData55660.2022.10020421
  41. S. Sarkar, A. Alhamadani, and C.T. Lu, “Explainable Prediction of the Severity of COVID-19 Outbreak for US Counties,” Proceedings of the 2022 IEEE International Conference on Big Data (IEEE BigData)-Special Session on HealthCare Data, pp. 5338-5345, 2022. DOI: 10.1109/BigData55660.2022.1002096
  42. L. AlKulaib, A. Alhamadani, S. Sarkar, and C.T. Lu, “HyperTwitter: A Hypergraph-based Approach to Identify Influential Twitter Users and Tweets,” Proceedings of the 2022 IEEE International Conference on Big Data (IEEE BigData), pp. 693-700, 2022. DOI: 10.1109/BigData55660.2022.10020571(Acceptance rate: 18.6%) (Slides)
  43. L. Alkulaib, Y. Sun, L. Zhang, and C.T. Lu, “Twitter Bot Identification: An Anomaly Detection Approach,” Proceedings of the 2022 IEEE International Conference on Big Data (IEEE BigData), Workshop on Multimodal Big Data, pp. 3567-3575, 2022. (Slides)
  44. S. Sarkar, A. Alhamadani, L. Alkulaib and C.T. Lu, “Predicting Depression and Anxiety on Reddit: A Multi-task Learning Approach,” Proceedings of the 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 427-435, 2022. Best Paper Award DOI:10.1109/ASONAM55673.2022.10068655 (Slides, Poster, VT News)
  45. A. Alhamadani, S. Sarkar, L. Alkulaib and C.T. Lu, “PRISTINE: Semi-supervised Deep Learning Opioid Crisis Detection on Reddit,” Proceedings of the 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 444-453, 2022. DOI:10.1109/ASONAM55673.2022.10068721 (Poster)
  46. S. Lei, X. Zhang, J. He, F. Chen, B. Du, and C.T. Lu, “Cross-Domain Few-Shot Semantic Segmentation,” Proceedings of the European Conference on Computer Vision, pp. 73-90, Oct. 23-27, 2022. (Acceptance rate: 26%) DOI: https://doi.org/10.1007/978-3-031-20056-4_5
  47. S.A. Alsalamah, S. Alsalamah, H. Alsalamah, C.T. Lu, “Towards a Patient-Centered Virtual Hospital Ecosystem: A Fine Grained VHealth-AC Model for Hospitals' Legacy Information Systems,” Proceedings of the 20th IEEE International Conference on Dependable, Autonomic & Secure Computing, Sept. 12-15, 2022. DOI: 10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927701
  48. L. Zhang, K. Fu, T. Ji,  C.T. Lu, “Granger Causal Inference for Interpretable Traffic Prediction,” Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, pp. 1645-1651, 2022.
  49. S. Lei, X. Zhang, J. He, F. Chen, C.T. Lu, “Uncertainty-Aware Cross-Lingual Transfer with Pseudo Partial Labels,” Findings of the Association for Computational Linguistics: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), pp.1987-1997, 2022. https://aclanthology.org/2022.findings-naacl.153/ Video: https://aclanthology.org/2022.findings-naacl.153.mp4 (Poster)
  50. G. Meng, Q. Jiang, K. Fu, B. Lin, C.T. Lu, Z. Chen, “Early Forecasting of the Impact of Traffic Accidents Using a Single Shot Observation,” Proceeding of the 2022 SIAM International Conference on Data Mining (SIAM DM), pp. 100-108, Alexandria, Virginia, April 27-29, 2022. (Acceptance rate: 27.8%)
  51. Z. Zhang, S. Biswas, F. Chen, K. Fu, T. Ji, C.T. Lu, N. Ramakrishnan, Z. Chen, “Blocking Influence at Collective Level with Hard Constraints,” Proceedings of the Thirty-sixth AAAI Conference on Artificial Intelligence (AAAI-22), pp. 13115-13116, February 22-March 1, 2022.
  52. L. Zhang, Z. Chen, C.T. Lu and L. Zhao, “From “Dynamics on Graphs” to “Dynamics of Graphs”: an Adaptive Echo-State Network Solution,” Proceedings of the Thirty-sixth AAAI Conference on Artificial Intelligence (AAAI-22), pp. 13111-13112, February 22-March 1, 2022.
  53. J. Wang, K. Fu, Z. Chen, C.T. Lu, “Augmentation of Chinese Character Representations with Compositional Graph Learning,” Proceedings of the Thirty-sixth AAAI Conference on Artificial Intelligence (AAAI-22), pp. 13075-13076, February 22-March 1, 2022.

  54. K. Fu, T. Ji, N. Self, Z. Chen, and C.T. Lu, “A Hierarchical Attention-Based Spatiotemporal Graph Convolutional Network for Traffic Incident Impact Forecasting,” Proceedings of the 2021 IEEE International Conference on Big Data (IEEE BigData 2021), pp. 1616-1624, Dec 15-18, 2021. DOI: 10.1109/BigData52589.2021.9672030 (Acceptance rate: 19%)
  55. A. Alhamadani, S. Sarkar, L. Zhang, L. Alkulaib, C.T. Lu, “Forecasting High-risk Areas of COVID-19 Infection Through Socioeconomic and Static Spatial Analysis,” Proceedings of the 2021 IEEE International Conference on Big Data (IEEE BigData), pp. 4313-4322, Dec 15-18, 2021. DOI: 10.1109/BigData52589.2021.9671896 (Acceptance rate: 19%)
  56. P. Roy, S. Sarkar, S. Biswas, F. Chen, Z. Chen, N. Ramakrishnan, C.T. Lu, “Deep Diffusion-Based Forecasting of COVID-19 by Incorporating Network-Level Mobility Information,” Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 168-175, Nov. 8-11, 2021. DOI: https://doi.org/10.1145/3487351.3488334
  57. D. Wang, K. Liu, D. Mohaisen, P. Wang, C.T. Lu, Y. Fu, “Automated Feature-Topic Pairing: Aligning Semantic and Embedding Spaces in Spatial Representation Learning,” Proceedings of the 29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), Nov. 2-5, 2021. DOI: https://doi.org/10.1145/3474717.3484212
  58. J. He, B. Xiao, X. Zhang, S. Lei, S. Wang, C.T. Lu, “Reducing Noise Pixels and Metric Bias in Semantic Inpainting on Segmentation Map,” Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 1876-1885, Oct. 11-17, 2021. DOI: 10.1109/ICCVW54120.2021.00214
  59. S. Lei, X. Zhang, J. He, F. Chen, C.T. Lu, “Few-Shot Semantic Segmentation via Prototype Augmentation with Image-level Annotations,” Proceedings of IEEE International Conference on Multimedia and Expo (ICME), July 5-9, Shenzhen, China, 2021. DOI: 10.1109/ICME51207.2021.9428300
  60. T. Ji, N. Self, K. Fu, Z. Chen, N. Ramakrishnan, C.T. Lu, “Dynamic Multi-Context Attention Networks for Citation Forecasting of Scientific Publications,” Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), pp. 7953-7960, Feb. 2-9, 2021. https://ojs.aaai.org/index.php/AAAI/article/view/16970 (Acceptance rate: 21.4%) 

  61. O. Zulfiqar, Y.C. Chang, P.H. Chen, K. Fu, C.T. Lu, Y. Li, “RISECURE: Metro Incidents and Threat Detection Using Social Media,” Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 531-535, Dec. 7-10, 2020. DOI: 10.1109/ASONAM49781.2020.9381317 (Youtube Video)
  62. J. Wang, K. Fu, C.T. Lu, “SOSNet: A Graph Convolutional Network Approach to Fine-Grained Cyberbullying Detection,” Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), pp. 1699-1708, December 10-13, 2020. DOI: 10.1109/BigData50022.2020.9378065
    Fine-grained Balanced Cyberbullying Dataset
    Publicity DAC, Publicity TJ High School, Regeneron Science Talent Scholar, Presidential Scholar Award
  63. J. He, X. Zhang, S. Lei, Z. Chen, F. Chen, A, Alhamadani, B. Xiao. C.T. Lu, “Towards More Accurate Uncertainty Estimation in Text Classification,” Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 8362–8372, Nov. 16-20, 2020. Poster (Acceptance rate: 24.6%)
  64. F. Chen, Z. Chen, S. Biswas, S. Lei, N. Ramakrishnan, C.T. Lu, “Graph Convolutional Networks with Kalman Filtering for Traffic Prediction,” Proceedings of the 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), pp. 135-138, Nov. 3-6, 2020.
  65. S. Biswas, F. Chen, Z. Chen, C.T. Lu, N. Ramakrishnan, “Incorporating Domain Knowledge into Memetic Algorithms for Solving Spatial Optimization Problems,” Proceedings of the 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), pp. 25-35, Nov. 3-6, 2020. DOI: https://dl.acm.org/doi/pdf/10.1145/3397536.3422265 (Acceptance rate: 22.1%) - Best Paper Award
  66. D. Wang, Y. Fu, P. Wang, B. Huang, C.T. Lu, “Reimagining City Configuration: Automated Urban Planning via Adversarial Learning,” Proceedings of the 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), pp. 497-506, Nov. 3-6, 2020. DOI: https://doi.org/10.1145/3397536.3422268 (Acceptance rate: 22.1%) - Best Paper Candidate
  67. S. Biswas, F. Chen, A. Sistrunk, S. Muthiah, Z. Chen, N. Self, C.T. Lu and N. Ramakrishnan, “Geospatial Clustering for Balanced and Proximal Schools,” Proceedings of the AAAI Conference on Artificial Intelligence, EAAI Symposium, Vol. 34,  No. 09, pp.13358-13365, New York, NY, February 8-9, 2020.
  68. X. Zhang, F. Chen, L. Zhao, C.T. Lu, “Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data,” Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), pp. 6853-6860, New York, NY, Feb 7-12, 2020. DOI: https://doi.org/10.1609/aaai.v34i04.6166 (Acceptance rate: 20.6%)
  69. X. Zhang, Y. Gao, J. Lin, C.T. Lu, “TapNet: Multivariate Time Series Classification with Attentional Prototype Network,” Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), pp. 6845-6852, New York, NY, Feb 7-12, 2020. DOI: https://doi.org/10.1609/aaai.v34i04.6165 (Acceptance rate: 20.6%)
  70. Z. Chen, G. Kolhe, S. Rafatirad, C.T. Lu, S. Manoj, P. Dinakarrao, H. Homayoun, and Liang Zhao, “Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning,” Proceedings of the 2020 Design, Automation & Test in Europe (DATE), pp. 358-363, Grenoble, France, March 9-13, 2020. (Acceptance rate: 26%)

  71. S. Biswas, F. Chen, Z. Chen, A. Sistrunk, N. Self, C.T. Lu, N. Ramakrishnan, “REGAL: A Regionalization framework for school boundaries,” Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), Paper ID: 258, Chicago, IL, Nov. 5-8, 2019.
  72. K. Fu, T. Ji, L. Zhao, C.T. Lu, “TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction,” Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), Paper ID: 271, pp. 329-388, Chicago, IL, Nov. 5-8, 2019. (Acceptance rate: 21.7%)
  73. X. Zhang, D. Rajagopal, M. Gamon, S. K. Jauhar, C.T. Lu, “Modeling the Relationship between User Comments and Edits in Document Revision,” Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 5002-5010, Hong Kong, China, Nov. 3-7, 2019. (Acceptance rate: 23.8%)
  74. L. Alkulaib, A. Alhamadani, T. Ji, C.T. Lu, “Collect Ethically: Reduce Bias in Twitter Datasets,” Proceedings of the 6th International Conference on Information Management and Big Data (SIMBig), pp. 106-114, Lima, Peru, Aug. 21-23, 2019.
  75. Y. Ning, L. Zhao, F. Chen, C.T. Lu, H. Rangwala, “Spatio-Temporal Event Forecasting and Precursor Identification,” Tutorial in 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (ACM KDD 2019), pp. 3237-3238, Anchorage, AK, Aug. 4-8, 2019.
  76. T. Ji, X. Zhang, N. Self, K. Fu, C.T. Lu, N. Ramakrishnan, “Feature Driven Learning Framework for Cybersecurity Event Detection,” Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 196-203, Vancouver, Canada, Aug. 27-30, 2019. (Acceptance rate: 14.3% Full Paper) DOI: https://doi.org/10.1145/3341161.3342871
  77. T. Ji, Z. Chen, N. Self, K. Fu, C.T. Lu, N. Ramakrishnan, “Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks,” Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), pp. 2621-2627, Macao, China, Aug. 10-16, 2019. (Acceptance rate: 17.8%)
  78. X. Zhang*, F. Chen*, C.T. Lu and N. Ramakrishnan, “Mitigating Uncertainty in Document Classification,” Proceedings of the 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 3126-3136, June 2-7, 2019. (Acceptance rate: 22.6%)

  79. L. Zhang, L. Zhao, X. Zhang, W. Kong, Z. Sheng, C.T. Lu, “Situation-Based Interaction Learning for Personality Prediction on Facebook,” Proceedings of the IEEE International Conference on Big Data, pp. 1553-1561, Seattle, WA, Dec. 10-13, 2018. (Acceptance rate: 18.9)
  80. Z. Chen, F. Chen, R. Lai, X. Zhang, C.T. Lu, “Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator,” Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 59-68, Singapore, Nov. 17-20, 2018. DOI 10.1109/ICDM.2018.00021 (Acceptance rate: 8.86% Full Paper)
  81. X. Zhang, S. Lei, L. Zhao, A. Boedihardjo, C.T. Lu, “Robust Regression via Online Feature Selection under Adversarial Data Corruption,” Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 1440-1445, Singapore, Nov. 17-20, 2018. DOI 10.1109/ICDM.2018.00199 (Acceptance rate: 19.94%)
  82. K. Fu, Z. Chen, C.T. Lu, “StreetNet: Preference Learning with Convolutional Neural Network on Urban Crime Perception,” Proceeding of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), Seattle, WA, Nov. 6-9, 2018. DOI:10.1145/3274895.3274975
  83. T. Ji, K. Fu, N. Self, C.T. Lu, R. Namakrishnan, “Multi-task Learning for Transit Service Disruption Detection,” Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 634-641, Barcelona, Spain, Aug. 28-31, 2018.
  84. T. Hua, C. Reddy, L. Zhang, L. Wang, L. Zhao, C.T. Lu, N. Ramakrishnan, “Social Media based Simulation Models for Understanding Disease Dynamics,” Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, pp. 3797-3804, Stockholm, Sweden, July 13-19, 2018. https://doi.org/10.24963/ijcai.2018/528 (Acceptance rate: 20.46%)
  85. X. Zhang, L. Zhao, Z. Chen, C.T. Lu, “Distributed Self-Paced Learning in Alternating Direction Method of Multipliers,” Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, pp. 3148-3154, Stockholm, Sweden, July 13-19, 2018. https://www.ijcai.org/proceedings/2018/437 (Acceptance rate: 20.46%)

  86. X. Zhang, L. Zhao, Z. Chen, A. Boedihardjo, D. Jing, C.T. Lu, “Trendi: Tracking Stories in News and Microblogs via Emerging, Evolving and Fading Topics,” Proceedings of the IEEE International Conference on Big Data, pp. 1590-1599, Boston, MA, Dec. 11-14, 2017. 
  87. X. Xhang, Z. Chen, L. Zhao, A. Boedihardjo, C.T. Lu, “TRACES: Generating Twitter Stories via Shared Subspace and Temporal Smoothness,” Proceedings of the IEEE International Conference on Big Data, pp. 1688-1693, Boston, MA, Dec. 11-14, 2017.
  88. X. Zhang, L. Zhao, A. Boedihardjo, C.T. Lu, “Online and Distributed Robust Regressions under Adversarial Data Corruption,” Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 625-634, New Orleans, Louisiana, Nov. 18-21, 2017. (Acceptance rate: 9.25%)
  89. Z. Chen, C.W. Wu, Y.C. Lu, C.T. Lu, “Learning to Fuse Music Genres with Generative Adversarial Dual Learning,” Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 817-822, New Orleans, Louisiana, Nov. 18-21, 2017. (Acceptance rate: 19.9%)
  90. R. Khandpur, T. Ji, S. Jan, G. Wang, C.T. Lu, N. Ramakrishnan, “Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media,” Proceedings of the 26th ACM International Conference on Information and Knowledge Management, Singapore, pp. 1049-1057, Nov. 6-10, 2017. (Acceptance rate: 22%) DOI: https://doi.org/10.1145/3132847.3132866
  91. X. Zhang, L. Zhao, A. Boedihardjo, C.T. Lu, N. Ramakrishnan, “Spatiotemporal Event Forecasting from Incomplete Hyper-local Price Data,” Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), pp. 507-516, Singapore, Nov. 6-10, 2017. (Acceptance rate: 21%).
  92. X. Zhang, L. Zhao, A. Boedihardjo, C.T. Lu, “Robust Regression via Heuristic Hard Thresholding,” Proceeding of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, August 19-25, 2017. (Acceptance rate: 26%)
  93. Z. Chen, X. Zhang, A. Boedihardjo, J. Dai, C.T. Lu, “Multimodal Storytelling via Generative Adversarial Imitation Learning,” Proceeding of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, August 19-25, 2017. (Acceptance rate: 26%)
  94. F. Jin, F. Chen, R.P. Khandpur. C.T. Lu, N. Ramakrishnan, “Absenteeism Detection in Social Media,” Proceeding of the 2017 SIAM International Conference on Data Mining (SIAM DM), Houston, Texas, April 27-29, 2017. (Acceptance rate: 26%)
  95. R. Khandpur, T. Ji, Y. Ning, L. Zhao, C.T. Lu, E. Smith, C. Adams, N. Ramakrishnan, “Determining Relative Airport Threats from News and Social Media,” Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI17), pp. 4701-4707, San Francisco, CA, Feb 4-9, 2017. (Acceptance rate: 24.6%) DOI: https://dl.acm.org/doi/10.5555/3297863.3297876

  96. M. Shukla*, A. Fong, R. Dos Santos, C.T. Lu, “DERIV: Distributed In-Memory Brand Perception Tracking Framework,” Proceeding of the 25th International Conference on Machine Learning and Applications, pp.387-393, Anaheim, CA, Dec. 18-20, 2016. DOI: 10.1109/ICMLA.2016.0069
  97. X. Zhang, Z. Chen, W. Zhong, A.P. Boedihardjo, C.T. Lu, “Storytelling in Heterogeneous Twitter Entity Network based on Hierarchical Cluster Routing,” Proceedings of the IEEE International Conference on Big Data, pp. 1522-1531, Washington, DC, Dec. 5-8, 2016.
  98. L. Zhao, F. Chen, C.T. Lu, N. Ramakrishnan, “Multi-resolution Spatial Event Forecasting in Social Media,” Proceedings of the IEEE International Conference on Data Mining (IEEE ICDM), Barcelona, Spain, Dec. 13-15, 2016. (Acceptance rate: 8.5%)
  99. T. Hua, X. Zhang, W. Wang, C.T. Lu, N. Ramakrishnan, “Automatical Storyline Generation with Help from Twitter,” Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM 2016), Indianapolis, IN, Oct. 24-28, 2016. (Acceptance rate: 28.8%)
  100. L. Zhao, J. Ye, F. Chen, C.T. Lu, N. Ramakrishnan, “Hierarchical Incomplete Multi-Source Feature Learning for Spatiotemporal Event Forecasting,” Proceedings of the 22th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM KDD 2016), pp. 2085-2094, San Francisco, CA, August 13-17, 2016. (Acceptance rate: 18%) https://doi.org/10.1145/2939672.2939847
  101. S. Muthiah, P. Butler, R. Khandpur, et al., “EMBERS at 4 years: Experiences operating an Open Source Indicators Forecasting System,” Proceedings of the 22th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM KDD 2016), pp. 205-214, San Francisco, CA, August 13-17, 2016. (Applied data science track; Acceptance rate: 12%)
  102. Y.C. Lu, C.W. Wu, A. Lerch, C.T. Lu, “Automatic Outlier Detection in Music Datasets,” Proceedings of the 17th International Society for Music Information Retrieval Conference (ISMIR), NYC, NY, August 7-11, 2016.
  103. Y.C. Lu, C.W. Wu, C.T. Lu, A. Lerch, “An Unsupervised Approach to Anomaly Detection in Music Datasets,” Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp. 749-752, Pisa, Italy, July 18-20, 2016. (Acceptance rate: 30%)
  104. M. Shukla, R. Dos Santos, A. Fong, C.T. Lu, “DISTL: Distributed In-Memory Spatio-Temporal Event-Based Storyline Categorization Platform in Social Media,” Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM), pp. 39-50, Rome, Italy, April 26-27, 2016. DOI: 10.5220/0005831200390050
  105. T. Hua, Y. Ning, F. Chen, C.T. Lu, N. Ramakrishnan, “Topical Analysis of Interactions Between News and Social Media,” Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI'16), pp. 2964-2971, Phoenix, AZ, Feb. 12-17, 2016. (Acceptance rate: 26%)

  106. L. Zhao, F. Chen, C.T. Lu, R. Ramakrishnan, “Dynamic Theme Tracking in Twitter” Proceedings of the IEEE International Conference on Big Data (IEEE BigData), pp. 561-570, Santa Clara, CA, Oct. 29 - Nov. 1, 2015. (Acceptance rate: 17%) DOI: 10.1109/BigData.2015.7363800
  107. L. Zhao, J. Chen, F. Chen, W. Wang, C.T. Lu, N. Ramakrishnan, “SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning,” Proceedings of the IEEE International Conference on Data Mining (IEEE ICDM), pp. 639-648, Atlantic City, NJ, Nov. 14-17, 2015. (Acceptance rate: 8.4%) DOI: 10.1109/ICDM.2015.39
  108. K. Fu, W. Zhong, C.T. Lu, A. Boedihardjo, “Find the Butterfly: A Social Media based Arterial Incidents Detection and Causality Analysis System,” Proceedings of the 23nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, WA, Nov. 3-6, 2015.
  109. K. Fu, C.T. Lu, R. Nune, J. Tao, “Steds: Social Media based Transportation Event Detection with Text Summarization,” Proceeding of the IEEE 18th International Conference on Intelligent Transportation Systems (ITSC-2015), pp. 1952-1957, September 15-18, Las Palmas de Gran Canaria, Spain, 2015.
  110. L. Zhao, Q. Sun, J. Ye, F. Chen, C.T. Lu, N. Ramakrishnan, “Multi-Task Learning for Spatio-Temporal Event Forecasting,” Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM KDD 2015), pp. 1503-1512, Sydney, Australia, Aug. 10-13, 2015. (Acceptance rate: 19%) Video: Youtube DOI: https://doi.org/10.1145/2783258.2783377
  111. M. Shukla, Z. Chen, C.T. Lu, “DIFPL: Distributed Drone Flight Path Builder System,” Proceedings of the 1st International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM), Barcelona, Spain, April 28-30, 2015. (Best Student Paper Award)
  112. L. Zhao, F. Chen, C.T. Lu, N. Ramakrishnan, “Spatiotemporal Event Forecasting in Social Media,” Proceedings of the 2015 SIAM International Conference on Data Mining (SDM15), pp. 963-971, Vancouver, Canada, TX, April 30-May 2, 2015. (Acceptance rate: 22%)

  113. Y. Wang, Y.C. Lu, I.R. Chen, J.H. Cho, A. Swami, C.T. Lu, “LogitTrust: A Logit Regression-based Trust Model for Mobile Ad Hoc Networks,” Proceedings of the 6th ASE International Conference on Privacy, Security, Risk and Trust, Cambridge, MA, Dec. 14-16, 2014.
  114. Andy Doyle, Graham Katz, Kristen Summers, Chris Ackermann, Ilya Zavorin, Zunsik Lim, Sathappan Muthiah, Liang Zhao, Chang-Tien Lu, Patrick Butler, Rupinder Paul Khandpur, “The EMBERS Architecture for Streaming Predictive Analytics,” Proceedings of the IEEE International Conference on Big Data (BigData 2014), pp. 11-13, 2014.
  115. K. Rathinavel, G. Dixit, M. Matarazzo, C.T. Lu, “SHOPAHOLIC: A Crowd-Sourced Spatio-Temporal Product-Deals Evaluation System” Proceedings of the 5th ACM SIGSPATIAL International Workshop on GeoStreaming (IWGS), Dallas, TX, Nov. 4-7, 2014. (http://dx.doi.org/10.1145/2676552.2676558)
  116. M. Liu, K. Fu, C.T. Lu, G. Chen, H. Wang, “A Search and Summary Application for Traffic Events Detection Based on Twitter Data” Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Dallas, TX, Nov. 4-7, 2014. (doi 10.1145/2666310.2666366)
  117. K. Fu, Y.C. Lu, C.T. Lu, “TREADS: A Safe Route Recommender using Social Media Mining and Text Summarization” Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Dallas, TX, Nov. 4-7, 2014. doi 10.1145/2666310.2666368
  118. N. Ramakrishnan, P. Butler, S. Muthiah, et al., “Beating the News’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators” Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM KDD), pp. 1799-1808, New York City, NY, Aug. 24-27, 2014. (doi 10.1145/2623330.2623373)

  119. B. Wang, H. Dong, C.T. Lu, “Using Step Variant Convolutional Neural Networks for Energy Disaggregation,” Neural Information Processing Systems (NIPS) Workshop on Machine Learning for Sustainability, Lake Tahoe, Nevada, Dec. 10, 2013.
  120. T. Hua, F. Chen, L. Zhao, C.T. Lu, N. Ramakrishnan, “STED: Semi-Supervised Targeted-Interest Event Detection in Twitter,” Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 1466-1469, August, 11-14, 2013. (doi 10.1145/2487575.2487712)
  121. A. Elbery, M. Elnainay, F. Chen, C.T. Lu, J. Kendall, “A Carpooling Recommendation System Based on Social VANET and Geo-social Data,” Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 546-549, Orlando, Florida, Nov. 5-8, 2013. (doi 10.1145/2525314.2525327)
  122. D. Grosvenor, J. Kendall, A. Sanders, C.T. Lu, “Kongress: A Search and Data Mining Application for U.S. Congressional Voting and Twitter Data,” Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 550-553, Orlando, Florida, Nov. 5-8, 2013. (doi 10.1145/2525314.2525328)
  123. H. Dong, B. Wang, C.T. Lu, “Deep Sparse Coding based Recursive Disaggregation Model for Water Conservation,” Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), pp. 2804-2810, Beijing, China, Aug. 3-9, 2013. (Acceptance rate: 28%) (PDF) (AAAI.org)
  124. Y.C. Lu, F. Chen, Y. Chen, C.T. Lu, “A Generalized Student-t based Approach to Mixed-Type Anomaly Detection,” Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI13), pp. 633-639, Bellevue, WA, July 16-18, 2013. (Acceptance rate:  29%)
  125. Q. Yan, M. Li, F. Chen, T. Jiang, W. Lou, Y.T. Hou, C.T. Lu, “Non-parametric Passive Traffic Monitoring in Cognitive Radio Networks,” Proceedings of the 32th IEEE International Conference on Computer Communications (IEEE INFOCOM 2013), pp. 1264-1272, Turin, Italy, April 14-19, 2013. (Acceptance rate: 17%) (DOI: 10.1109/INFCOM.2013.6566916)
  126. B. Wang, H. Dong, A. Boedihardjo, F. Chen, C.T. Lu, “A Hierarchical Probabilistic Model for Low Sample Rate Energy Disaggregation,” Proceedings of the 2013 SIAM International Conference on Data Mining (SDM13), pp. 704-712, Austin, TX, May 2-4, 2013. (Acceptance rate: 25.5%) DOI: https://doi.org/10.1137/1.9781611972832.78
  127. Contributor, “From GPS and Virtual Globes to Spatial Computing – 2012: The Next Transformative Technology,” A Community Whitepaper, Computing Community Consortium, January 20, 2013.

  128. F. Chen, J. Arredondo, R. P. Khandpur, C.T. Lu, D. Mares, D. Gupta, N. Ramakrishnan, “Spatial Surrogates to Forecast Social Mobilization and Civil Unrests,” White Papers: From GPS and Virtual Globes to Spatial Computing-2020, pp. 16-18, Sept. 10-11,2012.
  129. X. Liu, F. Chen, C.T. Lu, “Robust Prediction and Outlier Detection for Spatial Datasets,” Proceedings of the 12th IEEE International Conference on Data Mining (IEEE ICDM), pp. 469-478, Brussels, Belgium, Dec. 10-13, 2012. (Full paper, acceptance rate: 10.7%) DOI: 10.1109/ICDM.2012.147
  130. B. Wang, F. Chen, H. Dong, A. Boedihardjo, C.T. Lu, “Signal Disaggregation via Sparse Coding with Featured Discriminative Dictionary,” Proceedings of the 12th IEEE International Conference on Data Mining (IEEE ICDM), pp. 1134-1139, Brussels, Belgium, Dec. 10-13, 2012. (Short paper, acceptance rate: 20%) DOI: 10.1109/ICDM.2012.146
  131. B. Wang, H. Dong, A. Boedihardjo, C.T. Lu, H. Yu, I.R. Chen, J. Dai, “An Integrated Framework for Spatial-Temporal Textual Search and Mining (Demo Paper),” Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2011), pp. 570-573, Redondo Beach, CA, Nov. 6-9, 2012.
  132. R. Dos Santos, A. Boedihardjo, C.T. Lu, “Towards Ontological Similarity for Spatial Hierarchies," Proceeding of the ACM SIGSPATIAL International Workshop on Querying and Mining Uncertain Spatio-Temporal Data (QUeST 2012), pp. 26-33, Redondo Beach, CA, Nov. 6-9, 2012.
  133. Y.J. Wu, F. Chen, C.T. Lu, B. Smith, Y. Chen, “Traffic Flow Prediction for Urban Network Using Spatiotemporal Random Effects Model,” Transportation Research Board (TRB) 91st Annual Meeting, Paper: 12-4179, Washington DC, January 22-26, 2012.

  134. Y. Chen, M. Torii, C.T. Lu, H. Liu, “Learning from Positive and Unlabeled Documents for Automated Detection of Alternative Splicing Sentences in Medline Abstracts,” IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW 2011), pp. 530-537, Atlanta, GA, Nov. 12-15, 2011.
  135. S. Shah, F. Bao, C.T. Lu, I.R. Chen, “CROWDSAFE : Crowd Sourcing of Crime Incidents and Safe Routing on Mobile Devices  (Demo Paper),” Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2011), pp. 521-524, Chicago, Illinois, Nov. 1-4, 2011.
  136. X. Liu, F. Chen, C.T. Lu, “Spatial Categorical Outlier Detection: Pair Correlation Function Based Approach,” Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2011), pp. 465-468, Chicago, Illinois, Nov. 1-4, 2011.
  137. Y.C. Chang, C.T. Lu, H. Morris, P. Murray-Tuite, Q.B. Nguyen, “Community Situational Awareness and Resilience through Mobile Applications,” Proceedings of the 2011 IEEE International Conference on e-Business Engineering (IEEE ICEBE 2011), pp. 185-192, Beijing, China, Oct. 19-21, 2011.
  138. R. Dos Santos, A. Boedihardjo, C.T. Lu, “A Framework for the Expansion of Spatial Features Based on Semantic Footprints,” Proceedings of the 2011 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2011), pp. 3421-3426, Anchorage, Alaska, Oct. 9-12, 2011.
  139. F. Chen, J. Dai, B. Wang, S. Sahu, M. Naphade, C.T. Lu, “Activity Analysis Based on Low Sample Rate Smart Meters,” Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM KDD 2011), pp. 240-248, San Diego, CA, Aug. 21-24, 2011. https://doi.org/10.1145/2020408.2020450
  140. J. Dai, C.T. Lu, “DIME: Disposable Index for Moving Objects,” Proceedings of the 12th IEEE International Conference on Mobile Data Management,” pp. 68-77, Lulea, Sweden, June 6-9, 2011.

  141. Q. Li, C.T. Lu, “Appearance Based Recognition Using Spatial and Discriminant Influence,” Proceeding of the 9th International Conference on Machine Learning and Applications,” pp. 78-83, Washington DC, Dec. 12-14, 2010.
  142. J. Dai, C.T. Lu, X. Fei, “Traffic Analysis for Holidays and Planned Events,” the 2010 SIAM Conference on Data Mining, Workshop on Data Mining for Smarter Infrastructure, Columbus, Ohio, April 29-May 1, 2010.
  143. X. Liu, C. Jian, C.T. Lu, “Demo Paper: A Spatio-Temporal Crime Search Engine,” Proceedings of the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2010), pp. 528-529, San Jose, California, Nov. 2-5, 2010.
  144. X. Liu, C.T. Lu, F. Chen, “Spatial Outlier Detection: Random Walk Based Approaches,” Proceedings of the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2010), pp. 370-379, San Jose, California, Nov. 2-5, 2010.
  145. F. Chen, C.T. Lu, A. Boedihardjo, “GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection,” Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM KDD 2010), pp. 1069-1078, Washington DC, July 25-28, 2010.
  146. J. Dai, C.T. Lu, “C3: Concurrency Control on Continuous Queries over Moving Objects,” Proceedings of the 26th IEEE International Conference on Data Engineering (ICDE-2010), pp. 121-132, Long Beach, California, March 1-6, 2010.

  147. A. Boedihardjo, C.T. Lu, J. A. Shine, M. Tischler, “Fundamental Algorithms for Mining Data Streams,” Proceedings of the USACE Research and Development Conference, Nov. 17-20, 2009.
  148. J. Dai, C.T. Lu, L.F. Lai, “A Concurrency Control Protocol for Continuously Monitoring Moving Objects,” Proceedings of the 10th International Conference on Mobile Data Management: Systems, Services and Middleware (MDM 2009), pp. 132-141, Taipei, Taiwan, May 18-20, 2009.
  149. F. Chen, C.T. Lu, A. Boedihardjo, “On Locally Linear Classification by Pairwise Coupling,” Proceedings of the 8th IEEE International Conference on Data Mining, pp. 749-754, Pisa, Italy, Dec. 15-19, 2008.
  150. C.T. Lu, A. Boedihardjo, J. Dai, F. Chen, “HOMES: Highway Operations Monitoring and Evaluation System,” Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 529-530, Irvine, CA, Nov. 5-7, 2008.
  151. A. Boedihardjo, C.T. Lu, F. Chen, “A Framework for Estimating Complex Probability Density Structures in Data Streams,” Proceedings of the 17th ACM Conference on Information and Knowledge Management, pp. 619-628, Napa Valley, California, Oct. 26-30, 2008.
  152. X. Liu, C.T. Lu, F. Chen, “An Entropy-based Method for Assessing the Number of Spatial Outliers,” Proceedings of the 2008 IEEE International Conference on Information Reuse and Integration, pp. 244-249, Las Vegas, Nevada, July 13-15, 2008.

  153. J. Dai, C.T. Lu, “CLAM: Concurrent Location Management for Moving Objects,” Proceedings of the 15th ACM International Symposium on Advances in Geographic Information Systems, Seattle, Washington, Article No. 38, Nov. 7-9, 2007.
  154. Y. Kou, C.T. Lu, R. Dos Santos., “Spatial Outlier Detection: A Graph-based Approach,” Proceedings of the 19th International Conference on Tools with Artificial Intelligence, pp. 281-288, Patras, Greece, Oct 29-31, 2007.
  155. C.T. Lu, M. Shukla, S. Subramanya, Y. Wu, “Performance Evaluation of Desktop Search Engines,” Proceedings of the 2007 IEEE International Conference on Information Reuse and Integration, pp. 110-115, Las Vegas, Nevada, August 13-15, 2007.
  156. C.T. Lu, A. P. Boedihardjo, J. Zheng, "AITVS: Advanced Interactive Traffic Visualization System," Proceedings of the 22nd IEEE International Conference on Data Engineering (ICDE '06), pp. 167, Atlanta, GA, April 3-7, 2006. (PDF, PDF-P) DOI: 10.1109/ICDE.2006.14
  157. Y. Kou, C.T. Lu, D. Chen, "Spatial Weighted Outlier Detection," Proceedings of the 2006 SIAM Conference on Data Mining, pp. 613-617, Bethesda, Maryland, April 20-22, 2006. (PDP, PDF-P)
  158. Y. Jin, J. Dai, C.T. Lu, "Spatial-Temporal Data Mining in Traffic Incident Detection," the 2006 SIAM Conference on Data Mining, Workshop on Spatial Data Mining, Bethesda, Maryland, April 20-22, 2006. (PDP-P)
  159. A. Boedihardjo, C.T. Lu, "AOID: Adaptive Online Incident Detection System," the 9th International IEEE Conference on Intelligent Transportation Systems, Toronto, Canada, September 17-20, 2006. (PDF)
  160. C.T. Lu, A. P. Boedihardjo, J. Zheng, "Towards an Advanced Spatial-Temporal Visualization System for the Metropolitan Washington, D.C.,” the 2006 TRB International Visualization in Transportation Symposium and Workshop, Denver, Colorado, October 23-26, 2006. (PDF, Demo)
  161. C.T. Lu, A. P. Boedihardjo, "Advanced Traffic Visualization and Mining System," the 12th Annual ITSVA (Intelligent Transportation Society of Virginia) Conference & Exhibition, Arlington, VA, June 1-2, 2006. (PDF)
  162. K. Jefferson, C.T. Lu, X. Li, T.C. Hsu, T.F. Chu, "The Case for Using Spatiotemporal Traffic Data for Transportation Network Management," Managing Travel for Planned Special Events: Tools for Practitioners, Newport Beach, CA, Nov. 29-Dec. 1, 2006. (PDF)
  163. W. Fan, J. Mathuria, C.T. Lu, "Making Data Mining Models Useful to Model Non-paying Customers of Exchange Carriers," Proceedings of the 2005 SIAM International Conference on Data Mining, pp. 486-490, Newport Beach, CA, April 21-23, 2005. (PDF)
  164. J. Mathuria, C.T. Lu, J. Dai, "An Efficient Data Model for Sensor Networks," the 1st International Workshop on Data Mining, the 7th Joint Conference on Information Sciences, Salt Lake City, Utah, July 21-26, 2005. (PDF)
  165. C.T. Lu, Y. Kou, “A Web-based Data Analysis System for Watershed Management,” the 2005 Annual Meeting of the Associate of American Geographers(AAG), April 5-9, Denver, Colorado, 2005.
  166. C.T. Lu, A. P. Boedihardjo, P. Manalwar, “Exploiting Efficient Data Mining Techniques to Enhance Intrusion Detection Systems,” Proceedings of the 2005 IEEE International Conference on Information Reuse and Integration (IEEE IRI-2005 Knowledge Acquisition and Management), pp. 512-517, Las Vegas, Nevada, August 15-17, 2005. (PDF, PDF-P)
  167. Y. Kou, C.T. Lu, S. Sirwongwattana, Y.P. Huang, “Survey of Fraud Detection Techniques,” Proceedings of the 2004 International Conference on Networking, Sensing, and Control, pp. 749-754, Taipei, Taiwan, March 21-23, 2004. (PDF-P)
  168. L. Sripada, C.T. Lu, W. Wu, “Evaluating GML Support for Spatial Databases,” Proceedings of the Twenty-Eighth Annual International Computer, Software & Applications Conference (COMPSAC 04), Workshop on Geographic and Biological Data Management (GBDM’ 04), pp. 74-78, Hong Kong, China, September 28-30, 2004. (PDF)
  169. C.T. Lu, Lily R. Liang, “Wavelet Fuzzy Classification for Detecting and Tracking Region Outliers in Meteorological Data," Proceedings of the 12th ACM International Symposium on Advances in Geographic Information Systems, pp. 258-265, Washington DC, Nov. 12-13, 2004. (PDF-P)
  170. S. Nambiar, C.T. Lu, Lily R. Liang, "Analysis of Payment Transaction Security in Mobile Commerce," Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration (IEEE IRI-2004), pp. 475-480, Las Vegas, Nevada, November 8-10, 2004. (PDF, PDF-P)
  171. J. Ying, D. Gracanin, C.T. Lu, "Web Visualization of Geo-Spatial Data using SVG and VRML/X3D," Proceedings of the Third International Conference on Image and Graphics, pp. 497-500, Hong Kong, China, Dec.18-20, 2004. (PDF, CR).
  172. Y.P. Huang, G.L. Guo, C.T. Lu, "Using Back Propagation Model to Design a MIDI Music Classification System," Proceedings of the International Computer Symposium, pp. 253-258, Dec 15-17, 2004. (PDF)
  173. J. Zhao, C.T. Lu, Y. Kou, “Detecting Region Outliers in Meteorological Data,” Proceedings of the 11th ACM International Symposium on Advances in Geographic Information Systems, New Orleans, Louisiana, pp. 49-55, Nov. 7-8, 2003. (PDF-P)
  174. J. Zhao, C.T. Lu, Y. Kou, “Chang Detection in Meteorological Data,” Proceedings of the 7th Joint Conference on Information Sciences, Research Triangle Park, North Carolina, pp. 509-512, Sep. 26-30, 2003. (PDF)
  175. C.T. Lu, D. Chen, Y. Kou, “Algorithms for Spatial Outlier Detection,” Proceedings of the 3rd IEEE International Conference on Data Mining, Melbourne, Florida, pp. 597-600, Nov. 19-22, 2003. (PDF, PDF-P)
  176. C.T. Lu, D. Chen, Y. Kou, “Detecting Spatial Outliers with Multiple Attributes,” Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence, Sacramento, California, pp. 122-128, Nov. 3-5, 2003. (PDF-P)
  177. S. Shekhar, C.T. Lu, P. Zhang, "CubeView: A System for Traffic Data Visualization," Proceedings of the IEEE 5th International Conference on Intelligent Transportation Systems, 2002. (PostScript , PDF)
  178. S. Shekhar, C.T. Lu, P. Zhang, Rulin Liu, "Data Mining for Selective Visualization of Large Spatial Datasets," Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence, Washington DC, pp. 41-48, November 4-6, 2002. (PDF-P)
  179. S. Shekhar, C.T. Lu, P. Zhang, "Detecting Graph-based Spatial Outliers: Algorithms and Applications," Proceedings of the 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, California, pp. 365-370, August 26-29, 2001. (PS, PDF, PDF-P)
  180. S. Shekhar, C.T. Lu, X. Tan, S. Chawla, "Map Cube: A Visualization Tool for Spatial Data Warehouses - A Summary of Results" Proceedings of NSF workshop on Data Mining in GIS, March 1999. (PostScript , PDF)
  181. S. Shekhar, C.T. Lu, S. Ravada "Optimizing Join Index Based Join Processing," Proceedings of the 17th IEEE Symposium on Reliable Distributed Systems, West Lafayette, Indiana, October 1998. (PostScript (3M), PDF (2M))

Journal Publications

  1. S. Alsalamah, S. Alsalamah, H.A. Alsalamah, H.A. Sheera, K. Luther, and C.T. Lu, “Virtual Heathcare Bot (VHC-Bot): A Person-Centered AI Chatbot for Transforming Patient Care and Healthcare Workforce Dynamics,” To appear in Network Modeling Analysis in Health Informatics and Bioinformatics, 2025, (2.0 impact factor)

  2. H.A. Sheerah, S. AlSalamah, S.A. Alsalamah, C.T. Lu, A. Arafa, E. Zaatari, A. Alhomod, S. Pujari, and A. Labrique, “The Rise of Virtual Health Care: Transforming the Health Care Landscape in the Kingdom of Saudi Arabia: A Review Article,” Telemedicine and e-Health, Vol. 30, No. 10, pp. 2545-2554, Published: 2024-10-01. DOI:10.1089/tmj.2024.0114
  3. Z. Chen, F. Chen, L. Zhang, T. Ji, K. Fu, L. Zhao, F. Chen, L. Wu, C. Aggarwal, C.T. Lu, “Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks,” ACM Computing Surveys, Volume 56, Issue 5, Article No.: 126, pp. 1-42. (ACM Open Access) DOI: 10.1145/3627816 Published: 2024-05-01.
  4. T. Ji, Z. Chen, N. Self, K. Fu, N. Ramakrishnan, C.T. Lu. “Citation Forecasting with Multi-Context Attention-Aided Dependency Modeling,” ACM Transactions on Knowledge Discovery from Data, Volume 18, Issue 6 Article No.: 144, pp. 1-23, April 12, 2024. DOI: https://doi.org/10.1145/3649140
  5. W. M. Ahmed, A.A Azhari, A. Alfaraj, A. Alhamadani, M. Zhang, Chang-Tien Lu, “The Quality of AI-Generated Dental Caries Multiple Choice Questions: A Comparative Analysis of ChatGPT and Google Bard Language Models,” Heliyon, Vol. 10, Issue 7, e28198, April 2024. DOI: https://doi.org/10.1016/j.heliyon.2024.e28198

  6. L. Zhang, Z. Chen, C.T. Lu, L. Zhao, “Fast and Adaptive Dynamics-on-Graphs to Dynamics-of-Graphs Translation,” Frontiers in Big Data, Volume 6, Nov. 17, 2023. DOI: https://doi.org/10.3389/fdata.2023.1274135
  7. S. Biswas, F. Chen, Z. Chen, C.T. Lu, N. Ramakrishnan, “Memetic Algorithms for Spatial Partitioning Problems,” ACM Transactions on Spatial Algorithms and Systems, Vol. 9, No. 1. Article No.: 5, pp. 1-31, Jan. 12. 2023. DOI: https://dl.acm.org/doi/10.1145/3544779
  8. D. Wang, Y. Fu, K. Liu, F. Chen, P. Wang, C.T. Lu, “Automated Urban Planning for Reimagining City Configuration via Adversarial Learning: Quantification, Generation, and Evaluation,” ACM Transactions on Spatial Algorithms and Systems (TSAS), Volume 9, Issue 1, Article No.: 2, pp 1–24, Jan. 17, 2023. DOI: https://doi.org/10.1145/3524302
  9. Z. Guo, J.H. Cho, C.T. Lu, “Mitigating Influence of Disinformation Propagation Using Uncertainty-based Opinion Interactions,” IEEE Transactions on Computational Social Systems, Vol. 10, Issue: 2, pp. 434-447, April 2023. DOI: 10.1109/TCSS.2022.3225375
  10. J. He, X. Zhang, S. Lei, S. Wang, C.T. Lu, B. Xiao, “Semantic Inpainting on Segmentation Map via Multi-Expansion Loss,” Neurocomputing, Elsevier, Vol. 501, pp. 306-317, Aug. 28, 2022. DOI: https://doi.org/10.1016/j.neucom.2022.06.025
  11. F. Chen, D. Wang, S. Lei, J. He, Y. Fu, C.T. Lu, “Adaptive Graph Convolutional Imputation Network for Environmental Sensor Data Recovery,” Frontiers in Environmental Science, Vol. 10, Nov. 14, 2022. DOI: https://doi.org/10.3389/fenvs.2022.1025268
  12. L. Zhao, Y. Gao, J. Ye, F. Chen, Y. Ye, C.T. Lu, N. Ramakrishnan, “Spatio-Temporal Event Forecasting Using Incremental Multi-Source Feature Learning,” ACM Transactions on Knowledge Discovery from Data, 16(2): 40:1-28, April 2022. DOI: https://doi.org/10.1145/3464976
  13. Y. Sun, Y. Lu, K. Fu, F. Chen, C.T. Lu, “Detecting Anomalous Traffic Behaviors with Seasonal Deep Kalman Filter Graph Convolutional Neural Networks,” Journal of King Saud University - Computer and Information Sciences, Elsevier, 2022. DOI: https://doi.org/10.1016/j.jksuci.2022.05.017 (Impact Factor: 13.472)
  14. D. Wang, K. Liu, D. Mohaisen, P. Wang, C.T. Lu,  Y Fu, “Towards Semantically-Rich Spatial Network Representation Learning via Automated Feature Topic Pairing,” Frontiers in Big Data, 20 October 2021. DOI: https://doi.org/10.3389/fdata.2021.762899
  15. Z. Chen, L. Zhang, G. Kolhe, H. M. Kamali, S. Rafatirad, S. M. P. Dinakarrao, H. Homayoun, C.T. Lu, L. Zhao, “Deep Graph Learning for Circuit Deobfuscation,” Frontiers Big Data, 24 May 2021. DOI: https://doi.org/10.3389/fdata.2021.608286
  16. S. Lei, X. Zhang, L. Zhao, A. Boedihardjo, C.T. Lu, “Online and Distributed Robust Regressions with Extremely Noisy Labels,” ACM Transactions on Knowledge Discovery from Data, Volume 16, Issue 3, Article No.:41, pp. 1-24, Oct. 22, 2021. DOI: https://doi.org/10.1145/3473038
  17. M. Shukla, D. Dharme, P. Ramnarain, R. Dos Santos, C.T. Lu, “DIGDUG: Scalable Separable Dense Graph Pruning and Join Operations in MapReduce,” IEEE Transactions in Big Data, Vol. 7, Issue 6, pp. 930-951, Dec. 1, 2021. DOI: 10.1109/TBDATA.2020.2983650
  18. R. Wu, G. Luo, Q. Jin, J. Shao, C.T. Lu, “Learning Evolving User's Behaviors on Location-based Social Networks,” GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Springer, 24(3): 713-743 (2020) DOI:10.1007/s10707-020-00400-3
  19. T. Hua, C.T. Lu, J. Choo, C. Reddy, “Probabilistic Topic Modeling for Comparative Analysis of Document Collections,” ACM Transactions on Knowledge Discovery from Data, Vol. 14, Issue 2, Article No. 24, pp 1-27, April 2020. DOI: https://doi.org/10.1145/3369873
  20. L. Zhao, J. Chen, F. Chen, F. Jin, W. Wang, C.T. Lu, and N. Ramakrishnan, “Online Flu Epidemiological Deep Modeling on Disease Contact Network,” GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Springer, Vol. 24, Issue 2, pp. 443-475, April 2020. DOI https://doi.org/10.1007/s10707-019-00376-9 (Impact Factor: 2.392)
  21. Z. Ding, Z. Chen, T. Ma, C.T. Lu, W. Ma, L. Shaw, “Predicting the Hydrogen Release Ability of LiBH4-based Mixtures by Ensemble
    Machine Learning    ,” Energy Storage Materials, Elsevier, Vol. 27, pp. 466-477, May 2020. DOI: https://doi.org/10.1016/j.ensm.2019.12.010 (Impact Factor: 15.94)
  22. K. Fu, A. Alhamadani, T. Ji, C.T. Lu, “Batman or the Joker? The Powerful Urban Computing and its Ethics Issues,” Newsletter SIGSPATIAL Special, Vol. 11. No. 2, pp. 16-25, December 2019.
  23. X. Zhang, S. Lei, L. Zhao, A. Boedihardjo, C.T. Lu, “Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation,” ACM Transactions on Knowledge Discovery from Data, vol. 13, No. 3, Article 28, June 2019. (Impact Factor: 1.489)
  24. S. Dabiri, C.T. Lu, K. Heaslip, C. Reddy, “Semi-Supervised Deep Learning Approach for Transportation Mode Identification Using GPS Trajectory Data,” IEEE Trans. on Knowledge and Data Engineering, Vol. 32, Issue: 5, pp. 1010-1023, May 2020. DOI: https://doi.org/10.1109/TKDE.2019.2896985 (Impact Factor: 3.857)
  25. Y. Shi, M. Deng, J. Gong, C.T. Lu, X. Yang, H. Liu, “Detection of Clusters in Traffic Networks based on Spatio-temporal Flow Modeling,” Transactions in GIS, Vol. 23, No. 2, pp. 312-333, April 2019.
  26. C.T. Lu, “DIMPL: A Distributed In-memory Drone Flight Path Builder System,” Journal of Big Data, Springer, July 2018, Vol. 5, No.24. DOI https://doi.org/10.1186/s40537-018-0134-7
  27. Y. Wang, I.R. Chen, J.H. Cho, A. Swami, Y.C. Lu, C.T. Lu, and J.J.P. Tsai, “CATrust: Context-Aware Trust Management for Service-Oriented Ad Hoc Networks,” IEEE Transactions on Services Computing, vol. 11, no. 6, 2018, pp. 908-921. (Impact Factor: 4.418.)
  28. F. Chen, A. Boedihardjo, C.T. Lu, “Preface: Special Issue on Geo-social Media Analytics,” GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Springer, Vol. 22, pp 503–506, July 2018. DOI: https://doi.org/10.1007/s10707-018-0324-7
  29. B. Wang, Z. Chen, A. Boedihardjo, C.T. Lu, “Virtual Metering: An Efficient Water Disaggregation Algorithm via Non-Intrusive Load Monitoring,” ACM Transactions on Intelligent Systems and Technology, Vol. 9, Issue 4, Article No. 39, February 2018.
  30. M. Shukla, R. Dos Santos, F. Chen, and C.T. Lu, “DISCRN: A Distributed Storytelling Framework for Intelligence Analysis,” Big Data, 5(3): 225-245, September 2017.
  31. L. Zhao, J. Wang, F. Chen, C.T. Lu, N. Ramakrishnan, “Spatial Event Forecasting in Social Media With Geographically Hierarchical Regularization,” Proceedings of the IEEE, Vol. 105, No. 10, pp. 1953-1970, Oct. 2017. DOI: 10.1109/JPROC.2017.2719039
  32. M. Shukla, R. Dos Santos, A. Feng, C.T. Lu, “DERIV: Distributed Brand Perception Tracking Framework,” Journal of Big Data, Springer, December 2017, Vol. 4, No.17. DOI 10.1186/s40537-017-0078-3
  33. L. Zhao, Q. Sun, J. Ye, F. Chen, C.T. Lu, N. Ramakrishnan, “Feature Constrained Multi-Task Learning Models for Spatiotemporal Event Forecasting,” IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 29, No. 5, pp. 1059-1072, May 2017. DOI: 10.1109/TKDE.2017.2657624
  34. X. Liu, F. Chen, Y.C. Lu, C.T. Lu, “Spatial Prediction for Multivariate Non-Gaussian Data,” IEEE Transactions on Knowledge Discovery from Data (TKDD), Vol. 11, No. 3, Article 36, April 2017. DOI: http://dx.doi.org/10.1145/3022669
  35. T. Hua, F. Chen, L. Zhao, C.T. Lu, N. Ramakrishnan, “Automatic Targeted-Domain Spatiotemporal Event Detection in Twitter,” GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Springer, Vol. 20, pp. 765-795, October 2016. DOI: 10.1007/s10707-016-0263-0
  36. L. Zhao, F. Chen, C.T. Lu, N. Ramakrishnan, “Online Spatial Event Forecasting in Microblogs,” ACM Transactions on Spatial Algorithms and Systems (TSAS), Vol. 2, Issue 4, Article No. 15, November 2016. DOI: https://doi.org/10.1145/2997642
  37. Y. Shi, M. Deng, X. Yang, Q. Liu, L. Zhao, and C.T. Lu, “A Framework for Discovering Evolving Domain Related Spatio-Temporal Patterns in Twitter,” ISPRS International Journal of Geo-Information, Vol. 5, Issue 10, Article Number: 193, Oct. 2016. DOI: 10.3390/ijgi5100193
  38. Y.C. Lu, F. Chen, Y. Wang, C.T. Lu, “Discovering Anomalies on Mixed-Type Data Using a Generalized Student-t Based Approach,” IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 28, No.  10, pp. 2582-2595, Oct. 2016. DOI: http://doi.ieeecomputersociety.org/10.1109/TKDE.2016.2583429
  39. L. Zhao, T. Hua, C.T. Lu, I.R. Chen, “A Topic-Focused Trust Model for Twitter,” Computer Communications, the International Journal for the Computer and Telecommunications Industry, Elsevier.Vol. 76, Issue C, pp. 1-11, February, 2016. DOI:10.1016/j.comcom.2015.08.001
  40. R. Dos Santos, A. Boedihardjo, S. Shah, F. Chen, C.T. Lu, N. Ramakrishnan, “The Big Data of Violent Events: Algorithms for Association Analysis Using Spatio-Temporal Storytelling,” GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Springer, Vol. 20, No. 4, pp. 879-921, October 2016. DOI: 10.1007/s10707-016-0247-0
  41. R. Dos Santos, S. Shah, F. Chen, A. Boedihardjo, C.T. Lu, P. Butler, N. Ramakrishnan, “A Framework of Intelligence Analysis Using Spatio-temporal Storytelling,” GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Springer, Vol. 20, No. 2, pp. 285-326, April 2016. http://dx.doi.org/10.1007/s10707-015-0236-8
  42. Y.J. Wu, F. Chen, C.T. Lu, S. Yang, “Urban Traffic Flow Prediction Using a Spatio-Temporal Random Effects Model,” Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Vol. 20, Issue 3, pp. 282-293, 2016. DOI: 10.1080/15472450.2015.1072050
  43. N. Ramakrishnan, C.T. Lu, et al., “Model-Based Forecasting of Significant Societal Events,” IEEE Intelligent Systems, Volume 30, Issue 5, pp. 86-90, Sept.-Oct. 2015. DOI:10.1109/MIS.2015.74 (inaugural article, Predictive Analytics)
  44. A. Boedihardjo, C.T. Lu, F. Chen, “Fast Adaptive Kernel Density Estimator for Data Streams,” Knowledge and Information Systems An International Journal (KAIS), Springer, Volume 42, Issue 2, pp. 285-317, Feb. 2015. DOI 10.1007/s10115-013-0712-0
  45. L. Zhao, F. Chen, J. Dai, T. Hua, C.T. Lu, N. Ramakrishnan, “Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling,” PLoS ONE 9(10): e110206., Oct. 28, 2014. DOI:10.1371/journal.pone.0110206
  46. A. Doyle, G. Katz, K. Summers, C. Ackermann, I. Zavorin, Z. Lim, S. Muthiah, P. Butler, N. Self, L. Zhao, C.T. Lu, R.P. Khandpur, Y. Fayed, N. Ramakrishnan, “Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System,” Big Data, Vol. 2, No. 4., pp. 185-195, Dec. 2014. DOI: 10.1089/big.2014.0046
  47. F. Jin, W. Wang, L. Zhao, E. Dougherty, Y. Cao, C.T. Lu, N. Ramakrishnan, “Misinformation Propagation in the Age of Twitter” IEEE Computer, vol. 47, no. 12, pp. 90-94, Dec. 2014. DOI: 10.1109/MC.2014.361
  48. Q. Yan, M. Li, F. Chen, T. Jiang, Student Member, W. Lou, T. Hou, C.T. Lu, “SpecMonitor: Toward Efficient Passive Traffic Monitoring for Cognitive Radio Networks,” IEEE Transaction on Wireless Communications, Vol. 13, No. 10, pp. 5893-5905, Oct. 2014. DOI: 10.1109/TWC.2014.2339218
  49. X. Liu, F. Chen, C.T. Lu, “On Detecting Spatial Categorical Outliers,” GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Springer, Volume 18, Issue 3, pp. 501-536, July 2014. DOI 10.1007/s10707-013-0188-9 On detecting spatial categorical outliers | SpringerLink
  50. A. Boedihardjo, C.T. Lu, B. Wang, “A Framework for Exploiting Local Information to Enhance Density Estimation of Data Streams,” ACM Transactions on Knowledge Discovery from Data, Volume 9, Issue 1, Article No. 2, August 2014. DOI: http://dx.doi.org/10.1145/2629618
  51. T. Hua, C.T. Lu, N. Ramakrishnan, F. Chen, J. Arredondo, D. Mares, K. Summers, “Analyzing Civil Unrest through Social Media,” IEEE Computer, vol. 46, no. 12, pp. 80-84, Dec. 19, 2013. DOI:10.1109/MC.2013.442. (Article selected and featured by the IEEE Special Technical Community (STC) on Social Networking, January, 2014)
  52. Qi Li, C.T. Lu, “A Two-layer Framework for Appearance based Recognition using Spatial and Discriminant Influences,” Neurocomputing, Elsevier, Volume 119, pp. 425-433, Nov. 7, 2013. http://dx.doi.org/10.1016/j.neucom.2013.03.015
  53. C.T. Lu, R. F. Dos Santos, X. Liu, Y. Kou,“A Graph-based Approach to Detect Abnormal Spatial Points and Regions,” International Journal on Artificial Intelligence Tools, Volume 20, No. 4, pp. 721-751, 2011. (PDF)
  54. C.T. Lu, J. Dai, Y. Jin, J. Mathuria, “GLIP: A Concurrency Control Protocol for Clipping Indexing,” IEEE Transactions on Knowledge and Data Engineering, Volume 21, No. 5, pp. 714-728, May 2009.(PDF)
  55. D. Chang, C.T. Lu, Y. Kou, F. Chen, “On Detecting Spatial Outliers,” GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Springer, Volume 12,  Issue 4, pp. 455- 475, December 2008. (PDF)
  56. C. Steel, C.T. Lu, “Impersonator Identification through Dynamic Fingerprinting,” Digital Investigation, the International Journal of Digital Forensics & Incident Response, Elsevier, Volume 5, Issues 1-2, pp. 60-70, September 2008.(PDF)
  57. C.T. Lu, Y. Kou, J. Zhao, L. Chen, “Detecting and Tracking Region Outliers in Meteorological Data,” Information Sciences Journal, Informatics and Computer Science Intelligent Systems Applications, An International Journal, Elsevier, Volume 177, Issue 7, pp. 1609-1632, April 2007. (PDF, PDF-P)
  58. Chang-Tien Lu, Raimundo F. Dos Santos Jr, Lakshmi N. Sripada, Yufeng Kou, "Advances in GML for Geospatial Applications," GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Springer, Volume 11, Number 1, pp. 131-157, March 2007.(PDF, PDF-P).
  59. C.T. Lu, L. Sripada, S. Shekhar, R. Liu, “Transportation Data Visualization and Mining for Emergency Management,” International Journal of Critical Infrastructures, Inderscience, Vol.1. Nos. 2/3, pp. 170-194, 2005. (PDF, PDF-P)
  60. Y. Kou, C.T. Lu A. Godrej, T. Grizzard, H. Post, “A Web-based Data Visualization and Analysis System for Watershed Management,” Journal of Geographic Information Science Special Issue on Distributed GIS, Vol. 11, No.1, pp. 40-49, June 2005. (PDF)
  61. C.T. Lu, D. Chen, Y. Kou, “Multivariate Spatial Outlier Detection,” International Journal on Artificial Intelligence Tools, Vol. 13, No. 4, pp. 801-812, December, 2004. (PDF) (Link)
  62. S. Shekhar, C.T. Lu, P. Zhang, "A Unified Approach to Spatial Outliers Detection," GeoInformatica, An International Journal on Advances of Computer Science for Geographic Information System, Vol. 7, No.2, pp. 139-166, June 2003. (PDF-P)
  63. S. Shekhar, C.T. Lu, S. Chawla, S. Ravada, "Efficient Join Index Based Join Processing: A Clustering Approach," IEEE Transactions on Knowledge and Data Engineering, Vol. 14, No. 6 (Nov/Dec 2002), pp. 1400-1421 ( PostScript (8M), PDF (4M), Detail , PDF-P)
  64. S. Shekhar, C.T. Lu, P. Zhang, "Detecting Graph-based Spatial Outliers," International Journal of Intelligent Data Analysis (IDA), Vol. 6, No 5. pp. 451-468, 2002 (PDF , PDF-P)
  65. S. Shekhar, S. Chawla, S. Ravada, A. Fetterer, X. Liu, C.T. Lu, "Spatial Databases - Accomplishments and Research Needs," IEEE Transactions on Knowledge and Data Engineering, Vol. 11, No 1 (Jan/Feb 1999), pp. 45-55 (PostScript , PDF)

Book Chapter

  1. 1. Shang, R., Chen, S., Chen, Z., & Lu, C. -T. (2024). GraphNILM: A Graph Neural Network for Energy Disaggregation. In D. N. Yang, X. Xie, V. S. Tseng, J. Pei, J. W. Huang, & J. C. W. Lin (Eds.), Advances in Knowledge Discovery and Data Mining, Vol. 14646, pp. 431-443, Springer Nature Singapore. DOI:10.1007/978-981-97-2253-2_34
  2. O. Zulfiqar, Y.C. Chang, P.H. Chen, K. Fu, C.T. Lu, D. Solnick, Y. Li, “RISECURE: Metro Transit Disruptions Detection Using Social Media Mining and Graph Convolution,” Social Media Analysis for Event Detection, T. Ozyer (Editor), Springer Lecture Notes on Social Networks Series (LNSN), pp. 111-131, Springer, 2022.
  3. M. Shukla, A. Fong, R. Dos Santos, C.T. Lu, “Event Categorization and Key Prospect Identification from Storylines,” In: Grueau C., Laurini R., Rocha J. (eds), Geographical Information Systems Theory, Applications and Management (GISTAM), Communications in Computer and Information Science, Vol. 741, pp. 62-88, Springer, 2017.
  4. Y. Jin*, J. Dai*, C.T. Lu, “Efficient Range Query Using Multiple Hilbert Curves,” chapter in RFID/Book 1, Chap. 19, InTech - Open Access Publisher, July 20, 2011, ISBN 978-953-307-356-9. DOI: 10.5772/22413
  5. C.T. Lu, A. Boedihardjo*, S. Shekhar, “Analysis of Spatial Data with Map Cubes: Highway Traffic Data,” chapter in Geographic Data Mining and Knowledge Discovery (2nd edition), Harvey J. Miller and Jiawei Han (eds.), pp. 69-97, Taylor and Francis, ISBN 978-1-4200-7397-3, 2009.
  6. J. Dai*, C.T. Lu, “Concurrency Control for Spatial Access Method,” Encyclopedia of Geographical Information Science, Shashi Shekhar and Hui Xiong (eds.), pp. 124-128, Springer, ISBN 978-0-387-30858-6, 2008.
  7. R. DosSantos*, C.T. Lu, “Geography Markup Language,” Encyclopedia of Geographical Information Science, Shashi Shekhar and Hui Xiong (eds.), pp. 364-368 ,Springer, ISBN 978-0-387-30858-6, 2008.
  8. F. Chen*, C.T. Lu, “Nearest Nearby Query,” Encyclopedia of Geographical Information Science, Shashi Shekhar and Hui Xiong (eds.), pp. 776-782, Springer, ISBN 978-0-387-30858-6, 2008.
  9. Y. Kou*, C.T. Lu, “Spatial Outlier Detection,” Encyclopedia of Geographical Information Science, Shashi Shekhar and Hui Xiong (eds.), pp. 832-838 ,Springer, ISBN 978-0-387-30858-6, 2008.
  10. S. Nambiar*, C.T. Lu, “M-Payment Solutions and M-Commerce Fraud Management,” Chapter 9 in Advances in Banking Technology and Management: Impacts of ICT and CRM. Vadlamani Ravi (eds.), pp. 139-157, Idea Group Publishing, ISBN 9781599046754, 2008.
  11. S. Nambiar*, C.T. Lu, “M-Payment Solutions and M-Commerce Fraud Management,” chapter in Advances in Security and Payment Methods for Mobile Commerce. Wen-Chen Hu, Chung-wei Lee, and Weidong Kou (eds.), pp. 192-213, Idea Group Publishing, ISBN 159140346-4, 2005. (PDF, PDF-P)
  12. S. Shekhar, C.T. Lu, X. Tan, S. Chawla,"Map Cube: A Visualization Tool for Spatial Data Warehouses," chapter in Geographic Data Mining and Knowledge Discovery, Harvey J. Miller and Jiawei Han (eds.) (2001), Taylor and Francis. (Detail , GKD book)
  13. S. Shekhar, Y. Huang, W. Wu, C.T. Lu, "What's Spatial about Spatial Data Mining: Three case studies," chapter in Data Mining for Scientific and Engineering Applications, V. Kumar, R. Grossman, C. Kamath, R. Namburu (eds.) (2001) (PostScript , PDF)

Demonstration

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Summary

Talks