Talks and presentations

AIChE Spring Meeting - Advanced Tools for Process Data Analytics

March 31, 2019

Short course, American Institute of Chemical Engineers (AIChE) 2019 Spring Meeting, New Orleans, US

Process industries have been using data analytics in various forms for more than three decades. In particular, statistical techniques such as principal component analysis (PCA), partial least squares (PLS) and canonical variate analysis (CVA) have been used widely. This workshop introduces the essential machine learning algorithms and software tools for graduate students, experienced researchers and engineers working in the industry. In particular, several known and emerging applications of these algorithms in soft sensing, state and parameter estimation, process monitoring, fault detection and diagnosis, and control will be presented.

ADCHEM 2018 Shenyang - Advanced Tools for Data Analytics

July 24, 2018

Workshop, 10th IFAC International Symposium on Advanced Control of Chemical Processes, Shenyang, Liaoning, China

As an organizer for this workshop myself and a fellow graduate student were responsible for developing and delivering the majority of the workshop material including presentation slides and interactive case studies delivered as Jupyter notebooks. Material that I was responsible for developing and presenting included classification algorithms, regression techniques, dimensionality manipulation methods and advanced learning algorithms.

bcdata - Polynomial regression and the kernel trick

August 14, 2017

Talk, bcdata Data Science Workshop, Vancouver, British Columbia

As a co-organizer of the 2017 bcdata Data Science Workshop part of my duties included providing a presentation (a Jupyter notebook) in the first week of the workshop on least-squares, ridge, polynomial and kernel regression methods. Another duty involved moderating the career panel discussion. Finally, the second week of the workshop involved group projects where we ultimately presented on data insights from vehicle time series messages, a project supported by