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.
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