大数据智能科学、桥梁健康状况监测、电池全生命周期智能化管理。以第一作者/共同第一作者发表论文 十余篇, SCI二区以上 6 篇,  IEEE Trans文章 3 篇, 累计IF>44，已授权专利2项。

1. 以第一作者/共同第一作者发表的论文：

• M. Chen, L. Tao, J. Lou and X. Luo, "Latent-Factorization-of-Tensors-Incorporated Battery Cycle Life Prediction," accepted by IEEE/CAA Journal of Automatica Sinica, vol. 12, no. 3, pp. 633-635, March 2025. （SCI, 中科院一区Top, JCR Q1，影响因子：15.3） 

• M. Chen, G. Ma, W. Liu, N. Zeng, and X. Luo, “An overview of data-driven battery health estimation technology for battery management system,” accepted by Neurocomputing, Vol. 532, pp: 152-169, 1 May 2023. （SCI, 中科院二区Top, JCR Q1，影响因子：5.3） 

• M. Chen, C. He, X. Luo, “MNL: A Highly-Efficient Model for Large-scale Dynamic Weighted Directed Network Representation,” accepted by IEEE Transactions on Big Data, vol. 9, no. 3, pp. 889-903, Jun. 2023（SCI, 中科院二区, JCR Q1，影响因子：7.5） 

• M. Chen, R. Wang and X. Luo, “A Generalized Nesterov’s Accelerated Gradient-Incorporated Non-negative Latent-factorization-of-tensors Model for Efficient Representation to Dynamic QoS Data,” accepted by IEEE Transactions on Emerging Topics in Computational Intelligence. vol. 8, no. 3, pp. 2386-2400, June 2024. （SCI, 中科院二区, JCR Q1，影响因子：5.3） 

• X. Luo*, M. Chen, H. Wu, Z. Liu, H. Yuan and M. Zhou, “Adjusting Learning Depth in Nonnegative Latent Factorization of Tensors for Accurately Modeling Temporal Patterns in Dynamic QoS Data,” accepted by IEEE Transactions on Automation Science and Engineering, vol. 18, no. 4, pp. 2142-2155, Oct.2021. （与导师共同一作，SCI, 中科院二区, JCR Q1，影响因子：5.9） 

• Q. Wang, M. Chen, M. Shang, X. Luo. “A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction,” accepted by Neurocomputing, 2019, 367: 299-307. (与导师共同一作，SCI, 中科院二区Top, JCR Q1，影响因子：5.3） 

• M. Chen, C.H, H. Wu, S.Chen. Momentum-incorporated Latent Factorization of Tensors for Extracting Temporal Patterns from QoS Data [C].2019 IEEE International Conference on Systems,  Man and Cybernetics (SMC), Bari, Italy, 2019, pp. 1757-1762. CCF C类会议

• M. Chen, Xin Luo*,“Efficient Representation to Dynamic QoS Data via Generalized Nesterov’s Accelerated Gradient-incorporated Biased Non-negative Latent Factorization of Tensors,” 2021 IEEE International Conference on Systems, Man and Cybernetics (SMC), Melbourne, Australia, 2021, pp. 576-581, doi: 10.1109/SMC52423.2021.9658852. CCF-C类会议

• M. Chen and H. Wu, “A Breif Review on Data-driven Battery Health Estimation Methods for Energy Storage Systems,” 2022 IEEE International Conference on Networking, Sensing and Control (ICNSC), Shanghai, China, 2022, pp. 1-6, doi: 10.1109/ICNSC55942.2022.10004051.

• M. Chen and H. Wu, “Efficient Representation to Dynamic QoS Data via Momentum-incorporated Biased Nonnegative and Adaptive Latent Factorization of Tensor,” 2021 International Conference on Cyber-physical Social Intelligence. Beijing, China, 2021, pp. 1-6, doi: 10.1109/ICCSI53130.2021.9736227.

2. 已授权专利：

• 罗辛，吴昊，陈敏治，尚明生，刘志刚，钟裕荣.“一种基于偏置张量分解的云服务响应时间预测方法和装置,” 授权号：   CN110113180B, 授权日：2021.11.26

• 吴昊，夏艳，陈敏治，陈野."一种电动汽车充电桩充电时长预测方法和装置," 授权号: CN116957167B, 授权日：20240319