Leo H. Chiang

According to our database, Leo H. Chiang authored at least 15 papers between 2004 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Contamination classification for pellet quality inspection using deep learning.

You Peng, Birgit Braun, Casey McAlpin, Michael Broadway, Brenda Colegrove, Leo H. Chiang

Comput. Chem. Eng., 2022

Continuous assessment of data sources quality for improving the resilience of multisource fusion platforms.

Eugeniu Strelet, Zhenyu Wang, You Peng, Ivan Castillo, Ricardo R. Rendall, Birgit Braun, Leo H. Chiang, Marco S. Reis

Proceedings of the American Control Conference, 2022

2021

Recent trends on hybrid modeling for Industry 4.0.

Joel Sansana, Mark N. Joswiak, Ivan Castillo, Zhenyu Wang, Ricardo R. Rendall, Leo H. Chiang, Marco S. Reis

Comput. Chem. Eng., 2021

Integration of process knowledge and statistical learning for the Dow data challenge problem.

Si-Zhao Joe Qin, Siyi Guo, Zheyu Li, Leo H. Chiang, Ivan Castillo, Birgit Braun, Zhenyu Wang

Comput. Chem. Eng., 2021

Reinforcement Learning-Based Fed-Batch Optimization with Reaction Surrogate Model.

Yan Ma, Zhenyu Wang, Ivan Castillo, Ricardo R. Rendall, Rahul Bindlish, Brian Ashcraft, David Bentley, Michael G. Benton, José A. Romagnoli, Leo H. Chiang

Proceedings of the 2021 American Control Conference, 2021

2020

Data-driven plant-model mismatch quantification for MIMO MPC systems with feedforward control path.

Xiaodong Xu, Jodie M. Simkoff, Michael Baldea, Leo H. Chiang, Ivan Castillo, Rahul Bindlish, Brian Ashcraft

Proceedings of the 2020 American Control Conference, 2020

2019

Wide spectrum feature selection (WiSe) for regression model building.

Ricardo R. Rendall, Ivan Castillo, Alix Schmidt, Swee-Teng Chin, Leo H. Chiang, Marco S. Reis

Comput. Chem. Eng., 2019

Data-driven methods for batch data analysis - A critical overview and mapping on the complexity scale.

Ricardo R. Rendall, Leo H. Chiang, Marco S. Reis

Comput. Chem. Eng., 2019

Advances and opportunities in machine learning for process data analytics.

Si-Zhao Joe Qin, Leo H. Chiang

Comput. Chem. Eng., 2019

2017

Autocovariance-based plant-model mismatch estimation for linear model predictive control.

Siyun Wang, Jodie M. Simkoff, Michael Baldea, Leo H. Chiang, Ivan Castillo, Rahul Bindlish, David B. Stanley

Syst. Control. Lett., 2017

Plant-model mismatch evaluation for unconstrained MPC with state estimation.

Jodie M. Simkoff, Siyun Wang, Michael Baldea, Leo H. Chiang, Ivan Castillo, Rahul Bindlish, David B. Stanley

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

Plant-model mismatch estimation in unconstrained state-space MPC.

Jodie M. Simkoff, Siyun Wang, Michael Baldea, Leo H. Chiang, Ivan Castillo, Rahul Bindlish, David B. Stanley

Proceedings of the 2017 American Control Conference, 2017

2006

Empirical Models with Self-Assessment Capabilities for On-Line Industrial Applications.

Arthur K. Kordon, Guido Smits, Elsa M. Jordaan, Alex N. Kalos, Flor A. Castillo, Leo H. Chiang

Proceedings of the IEEE International Conference on Evolutionary Computation, 2006

2004

Fault diagnosis based on Fisher discriminant analysis and support vector machines.

Leo H. Chiang, Mark E. Kotanchek, Arthur K. Kordon

Comput. Chem. Eng., 2004

Robust Inferential Sensors Based on Ensemble of Predictors Generated by Genetic Programming.

Elsa M. Jordaan, Arthur K. Kordon, Leo H. Chiang, Guido Smits

Proceedings of the Parallel Problem Solving from Nature, 2004