Leaderboards/Fault Detection and Control Systems

Fault Detection and Control Systems

Last updated July 7, 2026

Rising Stars

New and hot

Rising Stars Researchers

1
Jakob Gawlikowski
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
2
Fujin Wang
Kunming University of Science and Technology
3
Lukas Brunke
Technical University of Munich
4
Junxiong Chen
University of Science and Technology of China
5
Anthony Brohan
Google (United States)
6
Lucas Costa Brito
Universidade Federal de Uberlândia
7
Man Zhang
China Agricultural University
8
Husnain Ali
Punjab Medical College
9
Yiyao An
Chongqing University of Posts and Telecommunications
10
ZY Chen
Unknown

Rising Stars Papers

1
Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis
Nature Communications|2024
607 cit.
2
Semi-Supervised DAS VSP Data Denoising Using Signal and Noise Distribution Difference
IEEE Transactions on Geoscience and Remote Sensing|2024
455 cit.
3
Robust statistical industrial fault monitoring: A machine learning-based distributed CCA and low frequency control charts
Chemical Engineering Science|2024
45 cit.
4
Intelligent machine learning-based multi-model fusion monitoring: application to industrial physio-chemical systems
Control Engineering Practice|2025
44 cit.
5
Advance industrial monitoring of physio-chemical processes using novel integrated machine learning approach
Journal of Industrial Information Integration|2024
42 cit.
6
Fault detection using machine learning based dynamic ICA-distributed CCA: Application to industrial chemical process
Digital Chemical Engineering|2024
41 cit.
7
Physical knowledge guided state of health estimation of lithium-ion battery with limited segment data
Reliability Engineering & System Safety|2024
39 cit.
8
A novel dynamic machine learning-based explainable fusion monitoring: application to industrial and chemical processes
Machine Learning Science and Technology|2024
38 cit.
9
Hybrid Fusion Paradigm in Advanced Process Monitoring: A Panoramic Review and Future Perspectives
Industrial & Engineering Chemistry Research|2025
25 cit.
10
Few-Shot Learning-Based Fault Diagnosis Using Prototypical Contrastive-Based Domain Adaptation Under Variable Working Conditions
IEEE Sensors Journal|2024
18 cit.

Emerging Leaders

Gaining momentum

Emerging Leaders Researchers

1
Yuyan Zhang
Lanzhou University
2
Symone Gomes Soares Alcalá
Universidade Federal de Goiás
3
Olga Fink
International Institute for Management Development
4
Quanqing Yu
Harbin Institute of Technology
5
Haidong Shao
South China University of Technology
6
Zitong Zhou
Nanjing University of Posts and Telecommunications
7
Qiao Zhu
Southwest Jiaotong University
8
Aapo Nummenmaa
Harvard University
9
Guijun Ma
Huazhong University of Science and Technology
10
Xin Hu
Ludong University

Emerging Leaders Papers

1
Fusing physics-based and deep learning models for prognostics
Repository for Publications and Research Data (ETH Zurich)|2022
349 cit.
2
SOC estimation for lithium-ion battery using the LSTM-RNN with extended input and constrained output
Energy|2022
323 cit.
3
Real-time personalized health status prediction of lithium-ion batteries using deep transfer learning
Energy & Environmental Science|2022
247 cit.
4
Challenges and outlook for lithium-ion battery fault diagnosis methods from the laboratory to real world applications
eTransportation|2023
222 cit.
5
OCV-SOC-Temperature Relationship Construction and State of Charge Estimation for a Series– Parallel Lithium-Ion Battery Pack
IEEE Transactions on Intelligent Transportation Systems|2023
200 cit.
6
A novel conditional weighting transfer Wasserstein auto-encoder for rolling bearing fault diagnosis with multi-source domains
Knowledge-Based Systems|2022
154 cit.
7
Current sensor fault diagnosis method based on an improved equivalent circuit battery model
Applied Energy|2022
151 cit.
8
A Transfer Learning-Based Method for Personalized State of Health Estimation of Lithium-Ion Batteries
IEEE Transactions on Neural Networks and Learning Systems|2022
149 cit.
9
Prior Knowledge-Augmented Self-Supervised Feature Learning for Few-Shot Intelligent Fault Diagnosis of Machines
IEEE Transactions on Industrial Electronics|2022
125 cit.
10
State of charge estimation for lithium-ion batteries using gated recurrent unit recurrent neural network and adaptive Kalman filter
Journal of Energy Storage|2022
119 cit.

Current Senior Leaders

Established & currently active

Current Senior Leaders Researchers

1
Michio Sugeno
Tokyo Institute of Technology
2
Manfred Morari
ETH Zurich
3
Biao Huang
University of Alberta
4
John F. MacGregor
McMaster University
5
S. Joe Qin
Lingnan University
6
Steven X. Ding
University of Duisburg-Essen
7
Guang‐Hong Yang
State Key Laboratory of Synthetical Automation for Process Industries
8
Ross L. Prentice
Fred Hutch Cancer Center
9
Feng Ding
Nanjing Institute of Vegetable Science
10
Frank Allgöwer
University of Stuttgart

Current Senior Leaders Papers

1
Fuzzy identification of systems and its applications to modeling and control
IEEE Transactions on Systems Man and Cybernetics|1985
19.4k cit.
2
The Statistical Analysis of Failure Time Data.
Biometrics|1981
10k cit.
3
Model predictive control: Theory and practice—A survey
Automatica|1989
5.3k cit.
4
A survey of industrial model predictive control technology
Control Engineering Practice|2003
5k cit.
5
Control of systems integrating logic, dynamics, and constraints
Automatica|1999
3.1k cit.
6
A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches
IEEE Transactions on Industrial Electronics|2015
3k cit.
7
Structure identification of fuzzy model
Fuzzy Sets and Systems|1988
2.7k cit.
8
Robust constrained model predictive control using linear matrix inequalities
Automatica|1996
2.5k cit.
9
A fuzzy-logic-based approach to qualitative modeling
IEEE Transactions on Fuzzy Systems|1993
2.4k cit.
10
Model predictive control: past, present and future
Computers & Chemical Engineering|1999
2.3k cit.

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