Imperial College London

Dr. Salvador García Muñoz

Faculty of EngineeringDepartment of Chemical Engineering

Visiting Professor







ACE ExtensionSouth Kensington Campus





PhD. Chemical Engineering (McMaster University, Canada).
MS. Chemical Engineering (Monterrey Tech, Mexico)
BS. Chemical and Computer Systems Engineering ( Monterrey Tech, Mexico)

NEW - Process Analytics using multivariate methods - May 20 to May 23 2024

Description of the course:

The participants will be introduced to modern day multivariate data analytics methods through lectures and hands-on workshops. The syllabus is geared towards general concepts on Multivariate Data Analysis (MVDA) using methods like PCA and PLS. The agenda includes theory and applications on a variety of  scenarios (e.g. continuous and batch processes, chemometrics). MVDA is a data-driven modeling technique particularly useful to understand systems where acquired data is: abundant, complex, correlated and noisy. Basic knowledge of statistics, linear algebra and geometry are helpful to fully understand the concepts of this course.

The course includes various hands-on workshops using data from real applications, using Python tools.

2024 Course offerings 

"Introduction to Process Analytics using Multivariate Methods " -  May 20 and 21 2024

Day 1: Principal Components Analysis Fundamentals and common applications

  • Geometric and statistical introduction to PCA
  • Algorithms and objective functions
  • Global diagnostics and contributions
  • Outlier Detection
  • Multivariate process monitoring
  • Establishing multivariate specifications for materials
  • Unsupervised clustering and classification

Day 2: Partial Least Squares fundamentals and common applications

  • Objective function and reduced rank regression
  • Algorithms
  • Parametric interpretation and model diagnostics
  • Chemometrics  and soft sensors
  • Multi-block methods

"Advanced Applications of Process Analytics using Multivariate Methods" - MAY 22 - 23  2024

Day 3 – Batch analysis and optimization based solutions

  • Batch process analysis and monitoring
  • Introduction to optimization using PYOMO 
  • Process and product design using PLS with optimization tools
  • In-silico formulation of new formulated products (blending optimization)

Day 4

  • Optimization Based Chemometrics 
  • NEW ! - Handling of missing samples
  • Adaptive and localized modeling
  • NEW! - Building hybrid models with PLS

Registration Fee applies (discounts available for CPSE Consortium companies, students and researchers ) 

For inquiries regarding the detailed agenda or to register please email:



Odgers J, Kappatou C, Misener R, et al., 2023, Probabilistic predictions for partial least squares using bootstrap, Aiche Journal, Vol:69, ISSN:0001-1541, Pages:1-16

Wehbe M, Haslam AJ, Garcia-Munoz S, et al., 2023, Thermodynamic modelling of the nature of speciation and phase behaviour of binary and ternary mixtures of formaldehyde, water and methanol, Molecular Physics, ISSN:0026-8976

Nascu I, Diangelakis NA, Munoz SG, et al., 2023, Advanced model predictive control strategies for evaporation processes in the pharmaceutical industries, Computers & Chemical Engineering, Vol:173, ISSN:0098-1354

Kappatou C, Odgers J, García-Muñoz S, et al., 2023, An optimization approach coupling pre-processing with model regression for enhanced chemometrics, Industrial and Engineering Chemistry Research, Vol:62, ISSN:0888-5885, Pages:6196-6213

Zhao F, Ochoa MP, Grossmann IE, et al., 2022, Novel formulations of flexibility index and design centering for design space definition, Computers & Chemical Engineering, Vol:166, ISSN:0098-1354

More Publications