一、 基本信息
出生年月：1986年2月
职称：教授
最高学位：博士
主要研究方向：机器学习、模式识别
导师类别：博导、学硕、专硕
工作单位：武汉理工大学人工智能学院
邮箱：chenglian@whut.edu.cn
个人简介：廉城，武汉理工大学人工智能学院自动化系，教授、博士生导师，武汉理工大学15551青年拔尖人才，IEEE Senior Member，中国自动化学会会员，中国人工智能学会会员，湖北省自动化学会理事。长期从事面向时序数据的机器学习算法及应用研究，具体包括：面向时序数据的预测、分类、异常检测、填补、自监督学习、多模态/多视图学习、多示例学习、大模型等，并应用于医疗、电力、交通、工业、地质等多场景，相关成果发表于IEEE TNNLS、IEEE TIP、IEEE TSG、IEEE TII、IEEE TNSRE、IEEE TASE、IEEE TR、IEEE TETCI、IEEE TIM、PR、NN等SCI期刊。
招生专业：交通信息工程及控制（学博）、电子信息（专博）、控制科学与工程（学硕）、电子信息（专硕）
二、 教育及工作经历
2026-至今，武汉理工大学，人工智能学院，教授
2022-2026，武汉理工学，自动化学院，教授
2017-2022，武汉理工大学，自动化学院，副教授
2016-2017，武汉理工大学，自动化学院，讲师
2014-2016，华中科技大学，电子信息与通信学院，博士后
2011-2014，华中科技大学，控制科学与工程，博士
2008-2011，武汉理工大学，控制科学与工程，硕士
2004-2008，武汉理工大学，电气工程及其自动化，学士
三、 近期主持的科研项目
1.2022-2025，国家自然科学基金面上项目，面向心音心电时序信号的智能分析方法及应用，主持
2. 2019-2022，国家自然科学基金面上项目，基于多源地学时空数据分层学习的滑坡易发性动态区划，主持
3.2016-2018，国家自然科学基金青年项目，基于多场信息数据驱动的滑坡演化多模式切换概率预测和控制研究，主持
4. 2025-2026，国家级JG科技项目，人工智能XXX研究，课题负责人
5. 2024-2025，湖北省智慧水电技术创新中心开放研究基金项目，基于跨域学习的滑坡演化阶段识别及位移变形区间预测，主持
6.2022-2024，山西省重点研发计划项目，面向多模态心音心电信号的心脏健康智能诊断系统研究，课题负责人
7.2017-2018，湖北省自然科学基金面上项目，基于人工神经网络多维时空数据挖掘的崩滑流灾害链预测，主持
8.2015-2016，中国博士后科学基金面上项目，基于随机权值神经网络的滑坡位移区间预测研究，主持
9. 2020，横向项目，心音数据分割与降噪，主持
10. 2022，横向项目，国网江西电科院配电网低电压试验平台改造项目技术服务，主持
四、 近期代表性学术成果
1. Honggang Yang, Cheng Lian*, Bingrong Xu, Ruijin Ding, and Zhigang Zeng, “PowerDiffuser: Collaborative Contrastive-Reconstruction Self-Supervised Learning for Robust Power Load Signal Representation,” IEEE Transactions on Industrial Informatics, vol. 22, no. 2, pp. 1461-1472, 2026（SCI）
2. Honggang Yang, Cheng Lian*, Bingrong Xu, Yilin Chen, Pengbo Zhao and Zhigang Zeng, “Decoupled self-supervised deep multi-task learning framework for subscriber portrait in smart meter,” Pattern Recognition, vol. 172, 112633, 2026.（SCI）
3. Qianjiang Chen, Cheng Lian*, Bingrong Xu, Quan Zhou, Yixin Su and Zhigang Zeng, “Large Language Model-assisted multi-scale hierarchical classification of ECG signals,” Knowledge-Based Systems, vol. 324, 113807, 2025.（SCI）
4. Xuhuang Du, Cheng Lian*, Youping Li, Zhiyong Qi, Zhengyang Tang, Jin Yuan, Bo Xu, Hui Zeng, “Adaptive classification of landslide displacement evolution states through multi-landslide data transfer learning,” Natural Hazards, vol. 121, pp. 11915-11930, 2025.（SCI）
5. Honggang Yang, Cheng Lian*, Bingrong Xu, Ruijin Ding, Pengbo Zhao and Zhigang Zeng, “Self-Supervised Latent Feature-Guided Multi-Step Diffusion Model for Electricity Theft Detection with Imbalanced and Missing Data,” IEEE Transactions on Smart Grid, vol. 16, no. 3, pp. 2439-2450, 2025.（SCI）
6. Yufeng Wei, Cheng Lian*, Bingrong Xu, Pengbo Zhao, Honggang Yang, Zhigang Zeng, “Bimodal Masked Autoencoders with internal representation connections for electrocardiogram classification,” Pattern Recognition, vol. 161, 111311, 2025.（SCI）
7. Pengbo Zhao, Cheng Lian*, Bingrong Xu, Zhigang Zeng, “Multiscale Global Prompt Transformer for EEG-Based Driver Fatigue Recognition,” IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 2700-2711, 2025.（SCI）
8. Bingrong Xu, Zhigang Zeng*, Cheng Lian, Zhengming Ding, “Generative Mixup Networks for Zero-Shot Learning,” IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 3, pp. 4054-4065, 2025.（SCI）
9. Haozhan Han, Cheng Lian*, Bingrong Xu, Zhigang Zeng, Adi Alhudhaif, Kemal Polat, “A MIL-based framework via contrastive instance learning and multimodal learning for long-term ECG classification,” Applied Soft Computing, vol. 167, 112372, 2024.（SCI）
10. Yuqing Wang, Danhong Zhang*, Yixin Su, Cheng Lian, Kunxiang Deng, “A Parallel Nonlinear Factor Recovery Method for VIO Based on a Factor Graph,” IEEE Transactions on Instrumentation & Measurement, vol. 73, no. 7508215, pp. 1-15, 2024.（SCI）
11. Tian Zhang, Cheng Lian*, Bingrong Xu, Yixin Su and Zhigang Zeng, “Cardiac signals classification via optional multimodal multiscale receptive fields CNN-enhanced Transformer,” Knowledge-Based Systems, vol. 300, 112175, 2024.（SCI）
12. Pengbo Zhao, Cheng Lian*, Bingrong Xu, Yixin Su and Zhigang Zeng, “Driving Cognitive Alertness Detecting Using Evoked Multimodal Physiological Signals Based on Uncertain Self-Supervised Learning,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 32, pp. 2165-2176, 2024.（SCI）
13. Weishan Yang, Yixin Su*, Yuepeng Chen and Cheng Lian, “Integrated Spatial Kinematics–Dynamics Model Predictive Control for Collision-Free Autonomous Vehicle Tracking,” Actuators, vol. 13, no. 4, 153, 2024.（SCI）
14. Bingrong Xu, Jianhua Yin, Cheng Lian, Yixin Su and Zhigang Zeng*, “Low-Rank Optimal Transport for Robust Domain Adaptation,” IEEE/CAA Journal of Automatica Sinica, vol. 11, no. 7, pp. 1667-1680, 2024.（SCI）
15. Siyuan Zhang, Cheng Lian*, Bingrong Xu, Yixin Su, Adi Alhudhaif, “12-Lead ECG Signal Classification for Detecting ECG Arrhythmia via An Information Bottleneck-Based Multi-Scale Network,” Information Sciences, vol. 662, 120239, 2024.（SCI）
16. Shunxiang Yang, Cheng Lian*, Zhigang Zeng, Bingrong Xu, Yixin Su, Chenyang Xue, “Masked Self-Supervised ECG Representation Learning via Multiview Information Bottleneck,” Neural Computing and Applications, vol. 36, pp. 7625–7637, 2024.（SCI）
17. Depeng Li, Tianqi Wang, Junwei Chen, Kenji Kawaguchi, Cheng Lian, Zhigang Zeng*, “Multi-View Class Incremental Learning,” Information Fusion, vol. 102, 102021, 2024.（SCI）
18. Siyuan Zhang, Cheng Lian*, Bingrong Xu, Junbin Zang, Zhigang Zeng, “A Token Selection-Based Multi-Scale Dual-Branch CNN-Transformer Network for 12-Lead ECG Signal Classification,” Knowledge-Based Systems, vol. 280, 111006, 2023.（SCI）
19. Long Chen, Cheng Lian*, Zhigang Zeng, Bingrong Xu, Yixin Su, “Cross-modal multiscale multi-instance learning for long-term ECG classification,” Information Sciences, vol. 643, 119230, 2023.（SCI）
20. Junbin Zang, Cheng Lian*, Bingrong Xu, Zhidong Zhang, Yixin Su, Chenyang Xue, “AmtNet: Attentional multi-scale temporal network for phonocardiogram signal classification,” Biomedical Signal Processing and Control, vol. 85, 104934, 2023.（SCI）
21. Haozhan Han, Cheng Lian*, Zhigang Zeng, Bingrong Xu, Junbin Zang, Chenyang Xue, “Multimodal multi-instance learning for long-term ECG classification,” Knowledge-Based Systems, vol. 270, 110555, 2023.（SCI）
22. Shunxiang Yang, Cheng Lian*, Zhigang Zeng, Bingrong Xu, Junbin Zang, Zhidong Zhang, “A Multi-View Multi-Scale Neural Network for Multi-Label ECG Classification,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 7, no. 3, pp. 648-660, 2023.（SCI）
23. Yupeng Wu, Cheng Lian*, Zhigang Zeng, Bingrong Xu, Yixin Su,“An Aggregated Convolutional Transformer Based on Slices and Channels for Multivariate Time Series Classification,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 7, no. 3, pp. 768-779, 2023.（SCI）
24. Guangyang Tian, Cheng Lian*, Bingrong Xu, Junbin Zang, Zhidong Zhang, Chenyang Xue, “Classification of Phonocardiogram Based on Multi-view Deep Network,” Neural Processing Letters, vol. 55, pp. 3655-3670, 2023.（SCI）
25. Wei Yao, Cheng Lian*, Lorenzo Bruzzone, “A CNN Ensemble Based on a Spectral Feature Refining Module for Hyperspectral Image Classification,” Remote Sensing, vol. 14, no. 10, 4982, 2022.（SCI）
26. Guangyang Tian, Cheng Lian*, Zhigang Zeng, Bingrong Xu, Yixin Su, Junbin Zang, Zhidong Zhang, Chenyang Xue, “Imbalanced heart sound signal classification based on two-stage trained DsaNet,” Cognitive Computation, vol. 14, pp. 1378-1391, 2022.（SCI）
27. Binghua Shi, Yixin Su*, Cheng Lian, Chang Xiong, Yang Long, Chenglong Gong, “Obstacle type recognition in visual images via dilated convolutional neural network for unmanned surface vehicles,” Journal of Navigation, vol. 75, no. 2, pp. 437-454, 2022.（SCI）
28. Xiaoyang Yu, Cheng Lian*, Yixin Su, Bingrong Xu, Xiaoping Wang, Wei Yao, Huiming Tang, “Selective ensemble deep bidirectional RVFLN for landslide displacement prediction,” Natural Hazards, vol. 112, pp. 725-745, 2022.（SCI）
29. Bingrong Xu, Zhigang Zeng*, Cheng Lian, Zhengming Ding, “Few-shot Domain Adaptation via Mixup Optimal Transport,” IEEE Transactions on Image Processing, vol. 31, pp. 2518-2528, 2022.（SCI）
30. Shu Sun, Xiaoping Wang*, Junnan Li, Cheng Lian, “Landslide evolution state prediction and down-level control based on multi-task learning,” Knowledge-Based Systems, vol. 238, 107884, 2022.（SCI）
31. Wei Zhou, Cheng Lian*, Zhigang Zeng, Bingrong Xu, Yixin Su, “Improve Semi-supervised Learning with Metric Learning Clusters and Auxiliary Fake Samples,” Neural Processing Letters, vol. 53, pp. 3427-3443, 2021.（SCI）
32. Wei Yao*, Cheng Lian, Lorenzo Bruzzone, “ClusterCNN: Clustering based feature learning for hyperspectral image classification,” IEEE Geoscience and Remote Sensing Letters, vol. 18, no. 11, pp. 1991-1995, 2021.（SCI）
33. Bingrong Xu, Zhigang Zeng*, Cheng Lian, Zhengming Ding, “Semi-Supervised Low-Rank Semantics Grouping for Zero-Shot Learning,” IEEE Transactions on Image Processing, vol. 30, pp. 2207-2219, 2021.（SCI）
34. Cheng Lian, Zhigang Zeng*, Xiaoping Wang, Wei Yao, Yixin Su, Huiming Tang, “Landslide displacement interval prediction using lower upper bound estimation method with pre-trained random vector functional link network initialization,” Neural Networks, vol.130, pp.286-296, 2020.（SCI）
35. Wei Zhou, Cheng Lian*, Zhigang Zeng, Yixin Su, “Mutual improvement between temporal ensembling and virtual adversarial training,” Neural Processing Letters, vol. 51, pp. 1111-1124, 2020.（SCI）
36. Lingzi Zhu, Cheng Lian*, Zhigang Zeng, Yixin Su, “A broad learning system with ensemble and classification methods for multi-step-ahead wind speed prediction,” Cognitive Computation, vol. 12, pp. 654-666, 2020.（SCI）
37. Zhihao Liu, Zhigang Zeng*, Cheng Lian, “Multidomain features fusion for zero-shot learning,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 4, no. 6, pp. 764-773, 2020.（SCI）
38. Cheng Lian, Lingzi Zhu, Zhigang Zeng*, Yixin Su, Wei Yao, Huiming Tang, “Constructing prediction intervals for landslide displacement using bootstrapping random vector functional link networks selective ensemble with neural networks switched,” Neurocomputing, vol. 291, pp. 1-10, 2018.（SCI）
39. Wei Yao, Zhigang Zeng*, Cheng Lian, Huiming Tang, “Pixel-wise regression using U-Net and its application on pansharpening,” Neurocomputing, vol.312, pp.364-371, 2018.（SCI）
40. Wei Yao, Zhigang Zeng*, Cheng Lian, “Generating probabilistic predictions using mean-variance estimation and echo state network,” Neurocomputing, vol.219, pp.536-547,2017.（SCI）
41. Cheng Lian, Zhigang Zeng*, Wei Yao, Huiming Tang, C. L. Philip Chen, “Landslide displacement prediction with uncertainty based on neural networks with random hidden weights,” IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 12, pp. 2683-2695, 2016.（SCI）
42. Cheng Lian*, C. L. Philip Chen, Zhigang Zeng, Wei Yao, Huiming Tang, “Prediction intervals for landslide displacement based on switched neural networks,” IEEE Transactions on Reliability, vol. 65, no. 3, pp. 1483-1495, 2016.（SCI）
43. Cheng Lian, Zhigang Zeng*, Wei Yao, Huiming Tang, “Multiple neural networks switched prediction for landslide displacement,” Engineering Geology, vol. 186, pp. 91-99, 2015.（SCI）
44. Wei Yao, Zhigang Zeng*, Cheng Lian, Huiming Tang, “Training enhanced reservoir computing predictor for landslide displacement,” Engineering Geology, vol. 188, pp. 101-109, 2015.（SCI）
45. Cheng Lian, Zhigang Zeng*, Wei Yao, Huiming Tang, “Extreme learning machine for the displacement prediction of landslide under rainfall and reservoir level,” Stochastic Environmental Research and Risk Assessment, vol.28, no.8, pp.1957-1972, 2014.（SCI）
46. Cheng Lian*, Zhigang Zeng, Wei Yao, Huiming Tang, “Ensemble of extreme learning machine for landslide displacement prediction based on time series analysis,” Neural Computing and Applications, vol.24, no.1, pp.99-107, 2014.（SCI）
47. Cheng Lian, Zhigang Zeng*, Wei Yao, Huiming Tang, “Displacement prediction model of landslide based on a modified ensemble empirical mode decomposition and extreme learning machine,” Natural Hazards, vol. 66, no. 2, pp.759-771, 2013.（SCI）