ProfessorSalvador Garcia Munoz
Visiting Professor
Department of Chemical Engineering - Faculty of Engineering
Orcid identifier0000-0003-0067-9773 (opens in a new tab)
- Visiting ProfessorDepartment of Chemical Engineering - Faculty of Engineering
- ACE Extension, South Kensington Campus, United Kingdom
RESEARCH
RESEARCH INTERESTS
Multivariate Latent Variable Methods (LVM)
Theory, algorithms and parameter estimation solutions for reduced rank projection and regression methods (PLS,PCA)
Application of multi-block and multi-path methods to complex data structures.
Optimization solutions with embedded latent variable models for assisted process operations.
Monitoring, troubleshooting, fault-detection control and optimization of process systems with LVM.
algorithms and methods for process analytical technology
Lean development and low cost of ownership methods for PAT (EIOT).
Self-sustaining methodologies (structured adaptive techniques).
Data fusion.
Integration of PAT metrics into state estimation, reconciliation and non-linear control solutions
statistics and fundamental modeling
Model Based Experimental Design for non-linear differential algebraic systems. i) Model Discrimination, ii) Model Parametrization, iii) Model Exploration.
Uncertainty handling and analysis for indirect measurements (PAT) incorporated into fundamental models.
hybrid modeling systems
Process monitoring, state-estimation and fault detection using fundamentally derived and empirically derived models.
OPTIMIZATION
Application of optimization methods to all of the above.
pyPhi - A Python package for Multivariate Analysis
pyphi is a python based package for multivariate analysis.
Version 1.0 includes: Principal Components Analysis, Projection to Latent Structures, LWPLS, Savitzy-Golay derivative transform, Standard Normal Variate transform. PCA and PLS routines support to missing data.
pyphi_plots is a package with a variety of plotting tools for models created with pyphi
==========================================
Dependencies: numpy, scipy, pandas, datetime, bokeh , matplotlib
The packages can be downloaded from:
Multivariate Latent Variable Methods (LVM)
Theory, algorithms and parameter estimation solutions for reduced rank projection and regression methods (PLS,PCA)
Application of multi-block and multi-path methods to complex data structures.
Optimization solutions with embedded latent variable models for assisted process operations.
Monitoring, troubleshooting, fault-detection control and optimization of process systems with LVM.
algorithms and methods for process analytical technology
Lean development and low cost of ownership methods for PAT (EIOT).
Self-sustaining methodologies (structured adaptive techniques).
Data fusion.
Integration of PAT metrics into state estimation, reconciliation and non-linear control solutions
statistics and fundamental modeling
Model Based Experimental Design for non-linear differential algebraic systems. i) Model Discrimination, ii) Model Parametrization, iii) Model Exploration.
Uncertainty handling and analysis for indirect measurements (PAT) incorporated into fundamental models.
hybrid modeling systems
Process monitoring, state-estimation and fault detection using fundamentally derived and empirically derived models.
OPTIMIZATION
Application of optimization methods to all of the above.
pyPhi - A Python package for Multivariate Analysis
pyphi is a python based package for multivariate analysis.
Version 1.0 includes: Principal Components Analysis, Projection to Latent Structures, LWPLS, Savitzy-Golay derivative transform, Standard Normal Variate transform. PCA and PLS routines support to missing data.
pyphi_plots is a package with a variety of plotting tools for models created with pyphi
==========================================
Dependencies: numpy, scipy, pandas, datetime, bokeh , matplotlib
The packages can be downloaded from: