Prince picture
Prince Addo

PhD student, Process Control

Chemical and Materials Eng Dept
University of Alberta
Edmonton AB


Donadeo Innovation Centre For Engineering
9211-116 St, Edmonton AB
T6G 2H5


Phone: +1 (587) 991-6872

I am currently a PhD student at the  Chemical and Materials Engineering Department of the University of Alberta. My research interests are in process control (mainly statistical), machine learning, and modelling and simulation of chemical processes. I am also interested in software, application and web development. 

Previously, I completed my masters at the Process Engineering Department of Stellenbosch University. My research interests are in process control (mainly statistical), machine learning, and modelling and simulation of chemical processes. I am also interested in software and web development. 

My master's work was on adaptive process monitoring with data-driven approaches, in which a novel monitoring approach that caters for slow and sudden process changes was developed. The work was funded by Sasol and The Center for Artificial Intelligence Research, South Africa, with notable contributions by the people listed below.  

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Dr. Lidia Auret

Data Science and Process Manager 

Stone Three Digital

South Africa

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Dr. Steve Kroon

Senior Lecturer 

Department of Computer Science

Stellenbosch University

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Dr. Roelof Coetzer

Senior Manager

Industrial Statistics 

Sasol Group Technology

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Dr. John McCoy

Data Scientist 

Stone Three Digital

South Africa

Sports Data Analytics Toolbox   

An App for sports data analytics for different subjects running in different shoes and on different surfaces. Database for all the shoes, surfaces, and the subjects is kept as well. ** UNLESS UNDER SPECIAL CIRCUMSTANCES, THIS APP IS NOT AVAILABLE FOR DOWNLOAD **    



Non-Isothermal Continuous Stirred Tank Reactor (CSTR) Simulator   

This work builds a Simulink model and a MATLAB program that uses graphical user interfaces (GUI) for simulating the Non-isothermal CSTR which was first developed by Yoon and MacGregor (2001) in fault detection. The model incorporates different works of the non-isothermal CSTR into a combined model that simulates a unimodal/multimodal operation data and different process faults as well as closed/open loop operation.   



Process Monitoring Toolbox

This work builds a toolbox that employs principal component analysis (PCA), adaptive PCA (APCA) as well as Gaussian mixture models (GMM) and adaptive GMM techniques. Moving window PCA (MWPCA) and recursive PCA (RePCA) are the APCA techniques available. The toolbox supports model training, validation, and testing for various data types and faults. The unique approaches available are PCA, MWPCA, RePCA, GMM, and adaptive GMM. Dynamic PCA can also be achieved by lagging the data when performing PCA. For the GMM methods, the decision on the data type (whether scores, normalized or raw) is only available after selecting either approach. 

MEng Defense, January 2019

Machine Learning Summer School, January 2019

Postgraduate conference, June 2018

Bayesian summer school, January 2018

Mineral research showcase, August 2017



10811 83 Ave NW, Edmonton, AB| +1-587-99172 ||Personal webpage:





Having a background in the following areas: modelling, machine learning, and graphical user interface with application to monitoring and control of chemical and mining processes; and website, software and application development, Prince seeks to develop further expertise through positions in website and application development, and process improvement and control. Special interests include fault detection and diagnostics, data analytics, graphical user interface development, and full-stack website development.


PhD, Process Control                                                                                                                     09/2020 – Present

Soft sensor development for Alberta oil sands.

University of Alberta, Canada                                                                  

Master of Engineering, Extractive Metallurgy–Full Research                                              01/2017 – 03/2019 

Thesis title: Adaptive process monitoring using principal component analysis and Gaussian mixture models.

Grade: Pass

Stellenbosch University, South Africa


Bachelor of Science, Petrochemical Engineering                                                                    09/2012 – 05/2016

Class: First Class Honours 

Class Rank: 1 of 67

Kwame Nkrumah University of Science and Technology (KNUST), Ghana



Addo P., Auret L., Kroon S., & McCoy J.T. (2018, October). Adaptive process monitoring using principal component analysis and Gaussian mixture models. Presentation at the Control Systems Day of the South African Council for Automation and Control, Stellenbosch, SA.   

Addo P., Wakefield B., Auret L., Kroon S., & McCoy J.T. (2017, August). Adaptive process monitoring using principal component analysis, a milling circuit focus. Presentation and poster presented at the Minerals Research Showcase of the Southern African Institute of Mining and Metallurgy, Cape Town, SA.   






                Masters work                                                                                                    01/2017 – 03/2019

Adaptive process monitoring using principal component analysis and Gaussian mixture models.

Worked on improving process monitoring performance in process industries (mainly chemical and mining), by developing process monitoring models which incorporate process changes and update the model parameters in real time.


               Undergraduate Honours Research Thesis                                                    09/2015 – 05/2016 

Plant design for styrene production 

Served as a project leader in the design of a plant to produce styrene in Ghana, carrying out the required feasibility studies, economic and environmental impact assessments. The final thesis was assessed in through a thesis defence.


              Engineering in Society Project                                                                         05/2013 – 09/2013

Pyrolysis of plastic waste into fuel oil 

Investigated the feasibility of converting locally produced plastic waste (generated in communities) into a mixture of synthetic crude oil. The result of this study was used in the development of a  pilot programme for a first-year project to help students identify the application of engineering to everyday challenges– and was presented to the College of Engineering, KNUST.  


              Chemical Engineer Intern, Genser Energy, Ghana.                                       06/2014 – 08/2014

Projects undertaken:

             Assessment of binders for coal briquettes                                                                                                   

             Investigated the performance of local binders for the production of coal briquettes in power production for GP Chirano Plant,  a 30.0MW Steam Turbine Plant.                   


            Assessment of biomass for coal co-firing                                                                                                   

            Investigated the performance of different biomasses to be combined with coal for power production.  





Genser Energy, Accra, Ghana private power producer in Africa 

Chemical engineer intern:                                                                                                   6/2014 – 8/2014