Dr. Xin Peng currently serves as a distinguished research fellow/ professor at the National Key Laboratory of Industrial Control Technology of East China University of Science and Technology. His research interests include intelligent modeling, control and optimization of industrial processes; AI for science/engineering; computer vision and its industrial applications. His academic achievements won the second prize of Shanghai Science and Technology Awards—Natural Science Award in 2022, and the second prize of Scientific and Technological Progress Award of China Instrument and Control Society in 2023. He was respectively awarded the funding sponsored by Shanghai Pujiang Scholar Talent Program in 2021, and Shanghai Sailing Program in 2018.

He has presided over 1 National Key R&D Program of China funded by Ministry of Science and Technology, 1 General Program funded by National Natural Science Foundation of China, 1 program supported by National Natural Science Foundation of China Young Scientists Fund, and 3 programs supported by provincial and ministerial funds. As a backbone member, he has participated in a number of scientific research and engineering application projects, including a Major Program funded by National Natural Science Foundation of China, a National Key R&D Program of China, and 3 R&D programs cooperated with enterprises. He has published more than 90 peer-reviewed papers on journals including IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Industrial Electronics, Applied Energy, Journal of Cleaner Production, etc.

He served as youth editor of SCI Journal of Central South University and Information and Control (Chinese edition). Currently, the applicant serves as an associate editor of IEEE Transactions on Industrial Informatics and is a reviewer for 91 papers in the journal. He simultaneously serves as invited reviewer of other IEEE journals, including IEEE Transactions on Industrial Electronics, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Instrumentation and Measurement, Applied Energy, Chemical Engineering Science, etc. He has 49 published national invention patents, of which 16 have been authorized, and has 12 registered software copyrights.

He serves as an IEEE Senior Member, CAA Senior Member, a member of the CAA Technical Committee on Fault Diagnosis and Safety of Processes, a member of the CAA Technical Committee on Environmental Perception and Protection Automation, a director of the Shanghai Association of Automation, a member of the CAAI Technical Committee on Intelligent Diagnosis and Health Management of the Chinese Association for Artificial Intelligence, and a director of the East China University of Science and Technology branch of the Western Returned Scholars Association (Overseas-educated Scholars Association of China).

1.        High-Precision Modeling of the Full Process in Multi-Stage Mineral Processing, National Key R&D Program of China, Ministry of Science and Technology, 2022YFB3304701, 2022-2025, 2,800,000 RMB, Principal Investigator

2.       Research on Load Optimization and Operational Condition Evaluation Methods for Wastewater Systems in Chemical Parks, National Natural Science Foundation of China (General Program), 62173145, 2021-2024, 570,000 RMB, Principal Investigator

3.       Research on Base Feature Recognition Methods for RNA Single-Molecule Detection Signals, National Natural Science Foundation of China Young Scientists Fund, 61803157, 2018-2021, 250,000 RMB, Principal Investigator

4.       Research on Load Optimization and Operational Condition Evaluation Methods for Wastewater Systems in Industrial Parks, Shanghai Pujiang Scholar Talent Program, 21PJ1402200, 2021-2022, 300,000 RMB, Principal Investigator

5.       Research on Distributed Feature Extraction and Anomaly Detection Methods for Refining Processes Based on Large-Scale Multi-Source Heterogeneous Data, Sponsored by Shanghai Sailing Program, 18YF1405200, 2018-2020, 200,000 RMB, Principal Investigator

6.       Risk Assessment and Early Warning Technology for Hazardous Chemicals Based on Dynamic Risk Cloud Maps, Sub-project of National Key R&D Program of China, Ministry of Science and Technology, 2018YFC0809304, 2019-2021, 450,000 RMB, Sub-project Leader

7.       International Postdoctoral Exchange Fellowship Program Scholarship (300,000 RMB from the Chinese side + 300,000 RMB from the German side), China Postdoctoral Science Foundation, Ministry of Human Resources and Social Security, 20170096, 2017-2019, 600,000 RMB, Principal Investigator

8.       Distributed Feature Extraction and Anomaly Detection for Multi-Source Data in Refining Processes, Supported by “the Fundamental Research Funds for the Central Universities”, 222201814041, 2018-2020, 150,000 RMB, Principal Investigator

9.       Intelligent Characterization and Process Condition Optimization of New Green Porous Catalytic Materials, Project of State Key Laboratory of Chemical Engineering, SKL-ChE-23C03, 2023-2023, 200,000 RMB, Principal Investigator

10.    Intelligent Characterization Analysis and Process Condition Optimization of Green Chemical Catalytic Materials, the Project of Key Laboratory of Intelligent Computing & Signal Processing（Anhui University）, Ministry of Education, 2022A006A, 2023-2023, 50,000 RMB, Principal Investigator

11.     High-Throughput Characterization Analysis and Process Optimization of Molecular Sieve Catalysts, Sponsored by Joint International Research Laboratory of Smart and Optimal Manufacturing for Petrochemical Industry, East China University of Science and Technology, 2022-2022, 800,000 RMB, Principal Investigator

12.     High-Throughput Intelligent Characterization Analysis and Rational Optimization of Preparation Conditions for Green Chemical Catalytic Materials, Independent Project of State Key Laboratory of Industrial Control Technology, ICT2024A23, 2024-2025, 200,000 RMB, Principal Investigator

13.     Intelligent Characterization Analysis and Process Condition Optimization of Green Chemical Catalytic Materials,Outstanding Young Talent Cultivation Program, East China University of Science and Technology, 2022-2022, 60,000 RMB, Principal Investigator

14.     Interpretable Operational Performance Evaluation and Load Optimization of Wastewater Systems in Industrial Parks, Outstanding Young Talent Cultivation Program, East China University of Science and Technology, 2023-2023, 80,000 RMB, Principal Investigator

15.     Anomaly Condition Early Warning and Self-Healing Control in Urban Wastewater Treatment Processes, National Natural Science Foundation of China (Major Program), 61890933, 2019-2023, Project Participant

16.     Chemical Process Modeling and Operational Optimization, National Science Fund for Distinguished Young Scholars, 61925305, 2019-2023, Project Participant

17.     Risk Early Warning and Intelligent Decision-Making in Refinery Production Based on Human-Machine Collaborative Learning, National Natural Science Foundation of China (Emergency Management Program), 61751305, 2018-2020, Project Participant

18.    Research on Key Technologies for Intelligent Control and Operational Optimization of Heavy-Duty Gas Turbines,Shanghai United Innovation Collaboration Program in the Field of Heavy-Duty Gas Turbines,Shanghai Municipal Education Commission、China United Heavy Duty Gas Turbine Technology Co., Ltd, 2023-2025, Technical Leader

19.     Research on Data Mining Techniques for High-Throughput Molecular Sieve Synthesis Systems, China Petroleum & Chemical Corporation, 421055, (Transversal Project, 9,500,000 RMB), 2021-2023, Technical Leader

20.    Research on Machine Learning Optimization Methods for Molecular Sieve Synthesis and System Development, China Petroleum & Chemical Corporation, 223025, (Transversal Project, 1,600,000 RMB, Total Project Funding, 16,200,000 RMB), 2023-2025, Technical Leader

21.     Data Mining and Applications of High-Throughput Molecular Sieve Systems, Sinopec Shanghai Research Institute of Petrochemical TechnologyCo., Ltd,33750000-19-ZC0607-001（Transversal Project, 500,000 RMB）, 2018-2020, Technical Leader

[1]          Tan D, Su Y, Peng X*, Chen H, et al. Large-Scale Data-Driven Optimization in Deep Modeling With an Intelligent Decision-Making Mechanism[J]. IEEE Transactions on Cybernetics, 2024, 54 (5): 2798-2810.

[2]          Jiang H, Zhang S, Yang W, Peng X*, et al. Integration of Encoding and Temporal Forecasting: Toward End-to-End NOx Prediction for Industrial Chemical Process[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35 (3): 2984-2996.

[3]          Tan D, Huang Z, Peng X*, Zhong W, et al. Deep Adaptive Fuzzy Clustering for Evolutionary Unsupervised Representation Learning[J]. IEEE Trans Neural Netw Learn Syst, 2024, 35 (5): 6103-6117.

[4]          Peng X, Pan R G, Li X, Zhong W M, et al. Molecular descriptor-assisted interpretable machine learning: A scheme for guiding the synthesis of zeolites with target structures[J]. Chemical Engineering Science, 2025, 308: 121378.

[5]          Zhang T, Shen F, Li Z, Peng X*, et al. Synergizing low-carbon planning and operation for sustainable integrated refinery-petrochemical processes under arrival time uncertainty: A large-scale hierarchical energy-efficiency optimization perspective[J]. Applied Energy, 2025, 377: 124497.

[6]          Jiang H, Zhang S C, Liu J R, Peng X*, et al. Model-free adjustment of reducing agent for SCR device under label deficiency: Regulation-oriented stage-wise reward deep Q-learning with transfer-learned state[J]. Process Safety and Environmental Protection, 2025, 195: 106745.

[7]          Zhang T, Zhong W, Liu Y, Lu R, Peng X*, et al. Incorporating large-scale economic-environmental-energy coupling assessment and collaborative optimization into sustainable product footprint management: A graph-assisted life cycle energy efficiency enhancement approach[J]. Energy Conversion and Management, 2025, 329: 119616.

[8]          彭鑫,沈菲菲, 张庭伟, 堵威, 钟伟民，钱锋. 大型炼化一体化过程全流程低碳运行分析与决策优化综述[J]. 中国科学基金, 2024, 38 (4): 571-582.

[9]          Peng X, Chen Z, Zhang J, Li Z, et al. A truncated Gaussian distribution based multi-scale segment-wise fusion transformer model for multi-step commodity price forecasting[J]. Engineering Applications of Artificial Intelligence, 2024, 133: 108434.

[10]       Kong M, Shen F, Li Z, Peng X*, Zhong W*, et al. Finite-Time Performance Mask Function-Based Distributed Privacy-Preserving Consensus: Case Study on Optimal Dispatch of Energy System[J]. IEEE Transactions on Signal and Information Processing over Networks, 2024, 10: 776-787.

[11]       Zhang T, Shen F, Li Z, Peng X*, et al. Synergizing low-carbon planning and operation for sustainable integrated refinery-petrochemical processes under arrival time uncertainty: A large-scale hierarchical energy-efficiency optimization perspective[J]. Applied Energy, 2025, 377: 124497.

[12]       Gao F, Zhong W, Jiang Q, Peng X*, Zhi Li, OWFD-UCPM: An open-world fault diagnosis scheme based on uncertainty calibration and prototype management[J]. Knowledge-Based Systems, 2024, 111403.

[13]       Jiang C, Peng X*, Huang B, Zhong W. Switching probabilistic slow feature extraction for semisupervised industrial inferential modeling[J]. Journal of Process Control, 2024, 141:1-1.

[14]       Du P, Zhong W*, Peng X*, Li L. Mode Substitution and Constraint Implementation in Complex Dynamic Process Regulation: A Solution for Performance Self-Recovery[J]. IEEE Transactions on Automation Science and Engineering, 2024: 1-13.

[15]       Huang H, Peng X*, Du W, Zhong W, Robust Sparse Gaussian Process Regression for Soft Sensing in Industrial Big Data under the Outlier Condition[J], IEEE Transactions on Instrumentation and Measurement, 2024, PP: 1-12.

[16]       Yang D, Peng X*, Jiang C, Wu X, Zhong W, et al. Transferable Deep Slow Feature Network with Target Feature Attention for Few-shot Time Series Prediction[J]. IEEE Transactions on Industrial Informatics, 2024, PP: 1-12.

[17]       Huang H, Peng X*, Du W, Zhong W. Robust Sparse Gaussian Process Regression for Soft Sensing in Industrial Big Data under the Outlier Condition[J]. IEEE Transactions on Instrumentation and Measurement, 2024: 1-1.

[18]       Chen S, Shen F, Zhong W, Peng X*, Du W. Synchronous adjustment framework for the integrated hydrogen network and production system: a concurrent optimization strategy of the system based on multi-model ensemble method[J]. Applied Energy, 2024, 360: 122636.

[19]       Kong M, Shen F, Du P, Peng X*, et al. Distributed Secure Consensus for Multiagent systems Based on Removing Intra-Cluster Coupling Restrictions and Its Application to Energy Systems [J]. Information Sciences, 2024, 653: 119579.

[20]       Shi Y, Zhong W, Peng X*, Yang M, et al. Interpretable reconstruction of naphtha components using property-based extreme gradient boosting and compositional-weighted Shapley additive explanation values[J]. Chemical Engineering Science, 2024, 284: 119462.

[21]       Li L, Zhang H, Ding S X, Qiao L, Peng X*, et al. Unified Solutions to Optimal Fuzzy Observer-Based Fault Detection for Discrete-Time Nonlinear Systems[J]. IEEE Transactions on Fuzzy Systems, 2024: 1-13.

[22]       Wang Q, Ji S, Wang X, Peng X*, et al. Distributed quantized secure bipartite consensus of linear multi‐agent systems with switching topologies and sequential scaling attacks[J]. IET Control Theory & Applications, 2024:1-1

[23]       Zhang T, Shen F, Peng X*, Li Z, et al. Carbon-efficient production planning for long-chain integrated refinery-petrochemical processes: A material-energy-carbon optimization perspective[J]. Journal of Cleaner Production, 2023: 138916.

[24]       Yang D, Peng X*, Su C, Li L, et al. Regularized Wasserstein distance-based joint distribution adaptation approach for fault detection under variable working conditions[J]. IEEE Transactions on Instrumentation and Measurement, 2024, 73: 1-11.

[25]       Xu L, Peng X*, Xi Z, Yuan Z, et al. Predicting organic structures directing agents for zeolites with conditional deep learning generative model[J]. Chemical Engineering Science, 2023: 119188.

[26]       Du P, Zhong W, Peng X*, Li Z, et al. Fault Effect Identification-Based Adaptive Performance Self-Recovery Control Strategy for Wastewater Treatment Process[J]. IEEE Transactions on Industrial Informatics, 2023: 1-12.

[27]       Gao F, Peng X*, Yang D, Su C, et al. A Novel Distributed Fault Diagnosis Scheme Toward Open-Set Scenarios Based on Extreme Value Theory[J]. IEEE Transactions on Industrial Informatics, 2023, 19 (10): 10454-10466.

[28]       Du P, Zhong W, Peng X*, Li L, et al. Self-Healing Control for Wastewater Treatment Process Based on Variable-Gain State Observer[J]. IEEE Transactions on Industrial Informatics, 2023, 19 (10): 10412-10424.

[29]       Huang H, Peng X*, Du W, Ding S, Zhong W.*, et al. Nitrogen Oxides Concentration Estimation of Diesel Engines Based on a Sparse Nonstationary Trigonometric Gaussian Process Regression with Maximizing the Composite Likelihood[J]. IEEE Transactions on Industrial Electronics, 2023, 70 (11): 11744-11753.

[30]       P.H. Du, W.M. Zhong, X. Peng*, L.L. Li, X.L. Wu, et al. Residual-triggered threshold decision and performance self-healing control for wastewater treatment process, [J]. Information Sciences, 2023, 640: 118822.

[31]       Li L, Ding S, Peng X*. Optimal Observer-based Fault Detection and Estimation Approaches for T-S Fuzzy Systems[J]. IEEE Transactions on Fuzzy Systems, 2022, 30 (2): 579-590.

[32]       Lu Y, Yang D, Li Z, Peng X*, & Zhong W. Neural Network Based on Windowed Convolutional Transformation to Extract Features in Time Domain and Its Application on Soft Sensing[J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 1-13.

[33]       Lu Y, Yang D, Li Z, Peng X*, et al. Neural networks with upper and lower bound constraints and its application on industrial soft sensing modeling with missing values[J]. Knowledge-Based Systems, 2022, 243: 108510.

[34]       Lu Y, Jiang C, Yang D, Peng X*, et al. Quality-relevant feature extraction method based on teacher-student uncertainty autoencoder and its application to soft sensors[J]. Information Sciences, 2022, 592: 320-339.

[35]       Du P, Peng X*, Li Z, Li L, et al. Performance-guaranteed adaptive self-healing control for wastewater treatment processes[J]. Journal of Process Control, 2022, 116: 147-158.

[36]       Yang D, Peng X*, Lu Y, Huang H, et al. Teacher-student uncertainty autoencoder for the process-relevant and quality-relevant fault detection in the industrial process[J]. IEEE Transactions on Artificial Intelligence, 2022: 1-11.

[37]       Xin J D, Wei Z P, Yang M L, Peng X*, et al. Merged-Sampling Mask R-CNN With Random Proposal Expansion for Particle Measurement of SEM Images of Molecular Sieve Catalysts[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-13.

[38]       Yang D, Peng X*, Ye Z, Lu Y, et al. Domain adaptation network with uncertainty modeling and its application to the online energy consumption prediction of ethylene distillation processes[J]. Applied Energy, 2021, 303: 117610.

[39]       Huang H, Li Z, Peng X*, Ding S X, et al. Gaussian Process Regression with Maximizing the Composite Conditional Likelihood[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-11.

[40]       Lu Y, Peng X*, Yang D, Jiang C, et al. The probabilistic discriminative time-series model with latent variables and its application to industrial chemical process modeling[J]. Chemical Engineering Journal, 2021, 423: 130298.

[41]       Huang H, Song Y, Peng X*, Ding S, et al. A Sparse Nonstationary Trigonometric Gaussian Process Regression and its Application on Nitrogen Oxides Prediction of the Diesel Engine[J]. IEEE Transactions on Industrial Informatics, 2021, 17 (12): 8367-8377.

[42]       Lu Y, Peng X*, Yang D, Yang M, et al. Model-Agnostic Meta-Learning with Optimal Alternative Scaling Value and Its Application to Industrial Soft Sensing[J]. IEEE Transactions on Industrial Informatics, 2021, 17 (12): 8003-8013.

[43]       Peng X, Ding S X, Du W L, Zhong W M, et al. Distributed process monitoring based on canonical correlation analysis with partly-connected topology[J]. Control Engineering Practice, 2020, 101: 104500.

[44]       Peng X, Li Z, Zhong W M, Qian F, et al. Concurrent Quality-Relevant Canonical Correlation Analysis for Nonlinear Continuous Process Decomposition and Monitoring[J]. Industrial & Engineering Chemistry Research, 2020, 59 (18): 8757-8768.

[45]       Li L, Ding S X, Peng X*. Distributed data-driven optimal fault detection for large-scale systems[J]. Journal of Process Control, 2020, 96: 94-103.

[46]       Peng X, Tang Y, Du W L, Qian F. Multimode Process Monitoring and Fault Detection: A Sparse Modeling and Dictionary Learning Method[J]. IEEE Transactions on Industrial Electronics, 2017, 64 (6): 4866-4875.

[47]       Peng X, Tang Y, Du W L, Qian F. Online Performance Monitoring and Modeling Paradigm Based on Just-in-Time Learning and Extreme Learning Machine for a Non-Gaussian Chemical Process[J]. Industrial & Engineering Chemistry Research, 2017, 56 (23): 6671-6684.

[48]       Peng X, Tang Y, Du W L, Qian F. Performance monitoring of non-gaussian chemical processes with modes-switching using globality-locality preserving projection[J]. Frontiers of Chemical Science and Engineering, 2017, 11 (3): 429-439.

[49]       Peng X, Tang Y, He W, Du W, et al. A Just-in-Time Learning Based Monitoring and Classification Method for Hyper/Hypocalcemia Diagnosis[J]. IEEE/ACM Trans Comput Biol Bioinform, 2018, 15 (3): 788-801.

[50]       Hong H F, Jiang C, Peng X*, Zhong W M*. Concurrent Monitoring Strategy for Static and Dynamic Deviations Based on Selective Ensemble Learning Using Slow Feature Analysis[J]. Industrial & Engineering Chemistry Research, 2020, 59 (10): 4620-4635.

[51]       Huang H J, Peng X, Jiang C, Li Z,Peng X*, Zhong W M*. Variable-Scale Probabilistic Just-in-Time Learning for Soft Sensor Development with Missing Data[J]. Industrial & Engineering Chemistry Research, 2020, 59 (11): 5010-5021.