H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering H-index 64 Citations 12,566 331 World Ranking 429 National Ranking 24

Research.com Recognitions

Awards & Achievements

2018 - IEEE Fellow For contributions to and application of Bayesian soft-sensing for control performance monitoring

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Control theory
  • Artificial intelligence

Biao Huang spends much of his time researching Control theory, Mathematical optimization, Data mining, Control system and Nonlinear system. His work carried out in the field of Control theory brings together such families of science as Matrix, Model predictive control and Benchmark. His study looks at the relationship between Model predictive control and fields such as Control theory, as well as how they intersect with chemical problems.

His research in Mathematical optimization tackles topics such as Robust control which are related to areas like Adaptive control and Exponential stability. The various areas that Biao Huang examines in his Data mining study include Probabilistic logic, Bayesian probability and Soft sensor. Biao Huang combines subjects such as Stability, Particle filter and Expectation–maximization algorithm with his study of Nonlinear system.

His most cited work include:

  • A new method for stabilization of networked control systems with random delays (752 citations)
  • Data Mining and Analytics in the Process Industry: The Role of Machine Learning (325 citations)
  • Performance Assessment of Control Loops (272 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Control theory, Mathematical optimization, Algorithm, Nonlinear system and Control engineering. His Control theory research includes themes of Model predictive control and Minimum-variance unbiased estimator. His research in Mathematical optimization intersects with topics in Bayesian probability, Particle filter, Estimation theory and Constraint.

His Bayesian probability research is multidisciplinary, incorporating perspectives in Machine learning and Probabilistic logic. His work investigates the relationship between Algorithm and topics such as Expectation–maximization algorithm that intersect with problems in Identification. His work deals with themes such as Control and Benchmark, which intersect with Control engineering.

He most often published in these fields:

  • Control theory (41.26%)
  • Mathematical optimization (19.21%)
  • Algorithm (18.74%)

What were the highlights of his more recent work (between 2018-2021)?

  • Algorithm (18.74%)
  • Nonlinear system (16.54%)
  • Control theory (41.26%)

In recent papers he was focusing on the following fields of study:

Algorithm, Nonlinear system, Control theory, Artificial intelligence and Iterative learning control are his primary areas of study. Biao Huang interconnects Fault detection and isolation, Probability density function, Bayesian inference and Expectation–maximization algorithm in the investigation of issues within Algorithm. His Nonlinear system study combines topics from a wide range of disciplines, such as Mathematical optimization, Data model and Robustness.

The concepts of his Control theory study are interwoven with issues in Estimation theory and Control. His biological study spans a wide range of topics, including Machine learning and Pattern recognition. He has researched Iterative learning control in several fields, including Data-driven, Multi-agent system, Lyapunov function and Trajectory.

Between 2018 and 2021, his most popular works were:

  • Review and Perspectives of Data-Driven Distributed Monitoring for Industrial Plant-Wide Processes (62 citations)
  • Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy (55 citations)
  • An Improved Data-Driven Point-to-Point ILC Using Additional On-Line Control Inputs With Experimental Verification (26 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Machine learning

His primary areas of investigation include Algorithm, Nonlinear system, Artificial intelligence, Data-driven and Feature extraction. The Algorithm study combines topics in areas such as Distribution, Probability density function, Outlier and Expectation–maximization algorithm. Nonlinear system is a subfield of Control theory that Biao Huang explores.

His Control theory research is mostly focused on the topic State observer. His research investigates the connection with Artificial intelligence and areas like Pattern recognition which intersect with concerns in Autoencoder and Probabilistic logic. The study incorporates disciplines such as Principal component analysis and Data mining in addition to Feature extraction.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

A new method for stabilization of networked control systems with random delays

Liqian Zhang;Yang Shi;Tongwen Chen;Biao Huang.
IEEE Transactions on Automatic Control (2005)

995 Citations

Performance Assessment of Control Loops: Theory and Applications

Biao Huang;S. L. Shah;M. A. Johnson;M. J. Grimble.
(1999)

664 Citations

Data Mining and Analytics in the Process Industry: The Role of Machine Learning

Zhiqiang Ge;Zhihuan Song;Steven X. Ding;Biao Huang.
IEEE Access (2017)

493 Citations

Performance Assessment of Control Loops

Biao Huang;Sirish L. Shah.
(1999)

416 Citations

Good, bad or optimal? Performance assessment of multivariable processes

B. Huang;S. L. Shah;E. K. Kwok.
Automatica (1997)

332 Citations

Dynamic Modeling, Predictive Control and Performance Monitoring: A Data-driven Subspace Approach

Biao Huang;Ramesh Kadali.
(2008)

330 Citations

Detection of multiple oscillations in control loops

N.F Thornhill;B Huang;H Zhang.
Journal of Process Control (2003)

309 Citations

Subspace method aided data-driven design of fault detection and isolation systems

S.X. Ding;P. Zhang;A. Naik;E.L. Ding.
Journal of Process Control (2009)

289 Citations

Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE

Xiaofeng Yuan;Biao Huang;Yalin Wang;Chunhua Yang.
IEEE Transactions on Industrial Informatics (2018)

237 Citations

Performance-Driven Distributed PCA Process Monitoring Based on Fault-Relevant Variable Selection and Bayesian Inference

Qingchao Jiang;Xuefeng Yan;Biao Huang.
IEEE Transactions on Industrial Electronics (2016)

231 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Top Scientists Citing Biao Huang

Feng Ding

Feng Ding

Jiangnan University

Publications: 118

Zidong Wang

Zidong Wang

Brunel University London

Publications: 82

Zhiqiang Ge

Zhiqiang Ge

Zhejiang University

Publications: 76

Steven X. Ding

Steven X. Ding

University of Duisburg-Essen

Publications: 70

Huijun Gao

Huijun Gao

Harbin Institute of Technology

Publications: 68

Sirish L. Shah

Sirish L. Shah

University of Alberta

Publications: 64

Zhihuan Song

Zhihuan Song

Zhejiang University

Publications: 60

Peng Shi

Peng Shi

University of Adelaide

Publications: 56

Tongwen Chen

Tongwen Chen

University of Alberta

Publications: 54

Shen Yin

Shen Yin

Norwegian University of Science and Technology

Publications: 53

Yang Shi

Yang Shi

University of Victoria

Publications: 42

Guang-Hong Yang

Guang-Hong Yang

Northeastern University

Publications: 41

Fei Liu

Fei Liu

Xi'an Jiaotong University

Publications: 40

Nina F. Thornhill

Nina F. Thornhill

Imperial College London

Publications: 39

Donghua Zhou

Donghua Zhou

Shandong University of Science and Technology

Publications: 38

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