Our proposed research objective is to develop a data-centric control framework that applies scalable machine learning techniques on multilevel heterogeneous process data in order to extract knowledge for improved process operation. Specifically, the objective is to successfully detect and diagnose process conditions of interest (i.e., disturbances or process upsets) and to subsequently control for or against such conditions. Ultimately, we wish to enlighten the way the process analytics community perceives value in data, in order to achieve some of the many benefits other industries are experiencing.
What was the best surprise about UBC or life in Vancouver?
The variety of outdoor activities in Vancouver is great. So is the sushi.
Why did you decide to study at UBC?
My choice to continue studies at UBC was based primarily on the intriguing research vision of my supervisor Bhushan Gopaluni.
What is it specifically, that your program offers, that attracted you?
The ability to collaborate closely with industry on important industrially relevant problems.
What do you like to do for fun or relaxation?
Skiing, hiking and playing hockey.
What advice do you have for new graduate students?
Start drafting your thesis early and stay organized throughout your studies.