朱理，博士、副教授。本科毕业于大连理工大学控制科学与工程学院，于浙江大学获工学博士学位，曾在瑞典隆德大学自动控制系进行博士后研究工作。

承担国家自然科学基金项目、国家高技术研究发展计划、国家重点研发计划、辽宁省自然基金资助计划以及企业横向项目等20余项。在高水平期刊与顶级会议上发表学术论文60余篇，授权国家发明专利10项，登记软件著作权6项。曾任国际标准化组织ISO TC184/SC5专家组成员。主要研究方向包括：工业数据挖掘与人工智能、智能感知与推理决策、异常检测与故障诊断、工业大模型与多智能体协同等。

欢迎有意向从事相关研究工作的同学加入课题组！

zhuli@dlut.edu.cn

[1][Papers]Zhu, Li.Li, Zhe,Chen, Junghui.Evaluating and Predicting Energy Efficiency Using Slow Feature Partial Least Squares Method for Large-scale Chemical Plants[J],Energy,2021,230:1-14

[2][Papers]Zhu, Li.Chen, Junghui.Energy efficiency evaluation and prediction of large-scale chemical plants using partial least squares analysis integrated with Gaussian process models[J],ENERGY CONVERSION AND MANAGEMENT,2019,195:690-700

[3][Papers]Zhu, Li.Chen, Junghui.Development of energy efficiency principal component analysis model for factor extraction and efficiency evaluation in large-scale chemical processes[J],INTERNATIONAL JOURNAL OF ENERGY RESEARCH,2019,43(2):814-828

[4][Papers]Zhu, Li.Chen, Junghui.A dynamic approach to energy efficiency estimation in the large-scale chemical plant[J],JOURNAL OF CLEANER PRODUCTION,2019,212:1072-1085

[5][Papers]Zhu, Li.Chen, JH (reprint author), Chung Yuan Christian Univ, Dept Chem Engn, Taoyuan 32023, Taiwan..Chen, Junghui.Prognostics of PEM fuel cells based on Gaussian process state space models[J],ENERGY,2018,149:63-73

[6][Papers]Zhu, Li.Chen, Chun-I,Chen, Junghui.Prognostics of tool failing behavior based on auto-associative Gaussian process regression for semiconductor manufacturing[A],2020:316-321

[7][Papers]Zhu Li.Li Zhe,Chen Junghui.An Industrial Process Monitoring Scheme with Moving Window Slow Feature Analysis[A],2021

[8][Papers]Zhu, Li.Schiraldi, Massimiliano,Johnsson, Charlotta,Mejvik, Jacob,Varisco, Martina.Key performance indicators for manufacturing operations management in the process industry[A],2017,2017-December:969-973

[9][Papers]Zhu, Li.Pettersson, Hakan,Varisco, Martina,Schiraldi, Massimiliano M.,Mejvik, Jacob,Johnsson, Charlotta,Bengtsson, Kristofer.Key Performance Indicators in Manufacturing Operations Management: A case study of the IS022400-standard applied at Volvo Cars[A],2018,2018-September:1149-1152

[10][Papers]Li, Zhe.朱理,Chen, Junghui.Adaptive two-dimensional subspace identification for monitoring batch processes with limited batch data[J],ISA TRANSACTIONS,2024,152:408-426

[11][Papers].Yang, Xin.朱理,Xu Xirong,魏小鹏,Yang Xin.ICAD: Rethinking the Role of Inference and Cues for the Anomaly Detection of Time Series in IIoT[J],IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2026,38(8):5187-5201

[12][Papers]朱理.Yu, Meng-Qin,Chen, Junghui.A Cyber-Physical monitoring and diagnosis scheme of energy consumption in Plant-Wide chemical processes[J],ENERGY CONVERSION AND MANAGEMENT,2023,289

[13][Papers]朱理.Chen, Junghui,Chen, Chun-, I.Prognostics for Semiconductor Sustainability: Tool Failure Behavior Prediction in Fabrication Processes[J],IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2024

[14][Papers]Duan, Chenming.朱理,Xu Xirong,Zhu, Jianmin,Wei, Ziqi,Yang Xin,武志超.武志超.DSTN: Dynamic Spatio-Temporal Network for Early Fault Warning in Chemical Processes[J],KNOWLEDGE-BASED SYSTEMS,2024,296

[15][Papers]朱理.Chen, Junghui.Lian, Jie.Attention-gated stacked information-separation target-supervised variational autoencoder for soft sensing[J],ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,2026,182

[16][Papers]朱理.Chen, Junghui.Chen, Chun-, I.Prognostics for Semiconductor Sustainability: Tool Failure Behavior Prediction in Fabrication Processes[J],IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2024,54(6):3450-3460

[17][Papers]Zhu, Li.Johnsson, Charlotta,Varisco, Martina,Schiraldi, Massimiliano M..Key performance indicators for manufacturing operations management - gap analysis between process industrial needs and ISO 22400 standard[A],2018,25:82-88

[18][Papers]朱理.Chen, Junghui.Liu, Ching-Lien.Enhancing industrial fault diagnosis via A Meta-learning: Zero-shot identification with constraint conditional variational autoencoder[J],ADVANCED ENGINEERING INFORMATICS,2026,71