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Biografia

Cong Liu é doutorado pela Eindhoven University of Technology, nos Países Baixos (2019), onde integrou o Process Mining Group. A sua investigação foca-se nas áreas de process mining, gestão de processos de negócio e inteligência artificial. É autor de mais de 100 publicações em revistas e conferências de referência, como IEEE Transactions on Services Computing, IEEE Transactions on Systems, Man, and Cybernetics, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Big Data, IEEE Transactions on Cloud Computing, IEEE/CAA Journal of Automatica Sinica, Information Sciences, Information Fusion, ICWS, ICPC e EuroVIS, entre outras. O seu trabalho conta com mais de 3.500 citações e um índice h de 29, de acordo com o Google Scholar.

Publicações Cientificas

Li, H., Liu, C., Du, Q., Zeng, Q., Liu, H., Wang, Q., & Cheng, L. (2026)

Optimizing resource allocation for wind turbine maintenance through process and fault data fusion. Information Fusion, 126, 103678. https://doi.org/10.1016/j.inffus.2025.103678

Lu, F., Liu, Y., Lin, Z., Han, X., & Liu, C. (2026)

SiamWT-CRNet: A Siamese Wavelet Network with Cross-Domain Feature Fusion for Dynamic Coal-Rock Recognition in Top-Coal Caving Systems. Applied Soft Computing, 186, Part A, Article 113984. https://doi.org/10.1016/j.asoc.2025.113984

Chen, Q., Zhang, Z., Zhang, Z., Zhang, K., Li, D., Wang, W., Zhang, J., & Liu, C. (2025)

Distilled large language model-driven dynamic sparse expert activation mechanism. Applied Soft Computing, 185, Part B, Article 114037. https://doi.org/10.1016/j.asoc.2025.114037

Guo, N., Liu, C., Mo, Q., Cao, J., Ouyang, C., Lu, X., & Zeng, Q. (2025)

Business Process Remaining Time Prediction Based on Incremental Event Logs. IEEE Transactions on Services Computing, 18(3), 1308–1320. https://doi.org/10.1109/TSC.2025.3562338

He, Y., Ren, Y., Yue, M., Zhang, L., Liu, C., & Li, C. (2025)

Indoor Dark Light Video Positioning Algorithm Based on Backbone Structure From Motion. IEEE Sensors Journal, 25(15), 29509–29523. https://doi.org/10.1109/JSEN.2025.3581284

Li, H., Liu, C., Du, Q., Zeng, Q., Zhang, J., Theodoropoulo, G., & Cheng, L. (2025)

Sampling-Based Next-Event Prediction for Wind-Turbine Maintenance Processes. Energies, 18(16), 4238. https://doi.org/10.3390/en18164238

Li, S., Bao, Y., Lu, F., Yu, C., & Liu, C. (2025)

A use-after-free vulnerability detection method for multi-threaded programs based on an improved Petri net and value flow graph. IEEE Access, 13, 177994-178005. https://doi.org/10.1109/ACCESS.2025.3620811

Liu, C., Liu, W., Guo, N., Song, R., Gu, Y., Cheng, L., & Zeng, Q. (2025)

Comparative evaluation of encoding techniques for workflow process remaining time prediction for cloud applications. Journal of Cloud Computing, 14, Article 36. https://doi.org/10.1186/s13677-025-00763-8

Wang, Q., Zhang, L., Cao, R., Guo, N., Zhang, H., & Liu, C. (2025)

A Process Tree-Based Incomplete Event Log Repair Approach. Information, 16(5), 390. https://doi.org/10.3390/info16050390

Wen, M., Liu, X., Ning, X., Liu, C., Chen, X., Nian, J., & Cheng, L. (2025)

Deep Reinforcement Learning for Energy-Efficient Workflow Scheduling in Edge Computing. Computer Networks, Article 111790. https://doi.org/10.1016/j.comnet.2025.111790

Xiang, Z., Cheng, J., Liu, C., Mao, Q., Yuan, G., & Gao, S. (2025)

Privacy-Preserving Autonomous Vehicle Group Formation in a Collusive Attack Scenario. IEEE Internet of Things Journal, 12(13), 25576–25586. https://doi.org/10.1109/JIOT.2025.3559151

Xiong, M., Zhang, Q., Li, D., Wang, W., Zhang, Z., Zhang, K., Liu, C., Chen, D., & Zhang, J. (2025)

Fine-tuning feature interaction for unsupervised domain adaptive low-light object detection. Neurocomputing, 131717. https://doi.org/10.1016/j.neucom.2025.131717

Zou, M., Zeng, Q., Liu, C., Cao, R., Chen, S., & Zhao, Z. (2025)

Prediction of Remaining Execution Time of Business Processes With Multiperson Collaboration in Assembly Line Production. IEEE Transactions on Computational Social Systems, 12(3), 1279–1295. https://doi.org/10.1109/TCSS.2024.3455418

Su, X., Liu, C., Lu, F., Cheng, L., Zeng, Q., & Zhang, S. (2025)

EdgeIM: An Efficient Edge-Based Process Model Discovery Technique. In R. N. Chang, C. K. Chang, J. Yang, N. Atukorala, D. Chen, S. Helal, S. Tarkoma, Q. He, T. Kosar, C. A. Ardagna, A. Beheshti, B. Cheng, & W. Gaaloul (Eds.), 2025 IEEE International Conference on Web Services: IEEE ICWS 2025 (pp. 404-410). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICWS67624.2025.00057

Su, X., Liu, C., Lu, F., Cheng, L., Zeng, Q., & Zhou, J. (2025)

Enhancing Healthcare Process Model Discovery Through Duplicate Task Identification. In R. N. Chang, C. K. Chang, J. Yang, N. Atukorala, D. Chen, S. Helal, S. Tarkoma, Q. He, T. Kosar, C. A. Ardagna, A. Beheshti, B. Cheng, & W. Gaaloul (Eds.), 2025 IEEE International Conference on Web Services: IEEE ICWS 2025 (pp. 477-483). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICWS67624.2025.00067

Yan, J., Liu, C., Cheng, L., Cheng, J., & Zeng, Q. (2025)

Enhancing Manufacturing Process Discovery Through Sub-Process Optimization. In R. N. Chang, C. K. Chang, J. Yang, N. Atukorala, D. Chen, S. Helal, S. Tarkoma, Q. He, T. Kosar, C. A. Ardagna, A. Beheshti, B. Cheng, & W. Gaaloul (Eds.), 2025 IEEE International Conference on Web Services: IEEE ICWS 2025 (pp. 428-434). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICWS67624.2025.00061

Wu, Y., Dong, Z., Liu, J., Li, Y., Liu, C., Wen, L., & Wu, X. (2025)

OER-Miner: One-off episode rule mining for process event logs. IEEE Transactions on Emerging Topics in Computing, 1–13. https://doi.org/10.1109/TETC.2025.3607892