Welcome to the UBC DAIS Lab
Prof. Bhushan Gopaluni leads research activities at the UBC DAIS Lab. He is a Professor in the Department of Chemical and Biological Engineering and Associate Dean, Education and Professional Development in the Faculty of Applied Science at the University of British Columbia (UBC). Read More.
DAIS Lab Research
Our research lies at the intersection of industrial process control, data analytics and machine learning.
Recent representative publications in these areas:
Machine Learning
Towards Self-Driving Processes: A Deep Reinforcement Learning Approach to Control
AIChE Journal. 2019 [PDF]
Data Analytics
Data-Driven Dynamic Modeling and Online Monitoring for Multiphase and Multimode Batch Processes with Uneven Batch Durations
Industrial & Engineering Chemistry Research. 2019 [PDF]
Alarm Analytics
Univariate model-based deadband alarm design for nonlinear processes
Industrial & Engineering Chemistry Research. 2019 [PDF]
Process Control
Machine Direction Adaptive Control on a Paper Machine
Industrial & Engineering Chemistry Research. 2019 [PDF]
Research Themes
We are at a unique historical moment with conditions ripe for a new industrial revolution that is going to take us to a level of automation that had never been seen before. This revolution is driven by a serendipitous confluence of ubiquitous cyber-physical systems or internet of things, gargantuan computing power, inexpensive memory and major algorithmic developments in machine learning and artificial intelligence.
It is happening all around us in the form of self-driving cars to human-like robots.
The process industries are in possession of treasure troves of heterogenous data that are gravely under utilized. These incredible volumes of data that industries already possess are poised to provide a level of insight and information never realized before, and thus alleviate economic and competitive pressures.
We often collaborate with industry partners and other academic researchers for problem-solving in specific domains. For a list of our projects and collaborators, please visit our Research page, check out our Publications and see our Team members:
DAIS Lab Recruitment
Please see our publications list for more information on our research on process control, machine learning and data analytics. Our team members and some examples of current and past projects are also available on our team page. We upload our presentations and workshops to the resources page.
Our group is recruiting year-round for postdocs, MASc and PhD students, visiting students and undergraduate students. Please see our Opportunities page for more information.
DAIS Lab Highlights
Recruiting graduate students for industry-academic collaborative projects with Burnaby Refinery
Link6 papers were accepted for the IFAC World Congress 2023 in Yokohama, Japan. Congratulations!
LinkLee's lime kiln monitoring research commercialized by BlueMarvel AI. Congratulations!
LinkDAIS Lab News
6 papers from the UBC DAIS Lab has been accepted to the IFAC World Congress 2023.
The UBC DAIS Lab and the Burnaby Refinery are recruiting graduate students to work on industry-academia collaborative projects.
HeatSeeker is a lime kiln monitoring solution developed by BlueMarvel AI to help industry save energy
DAIS lab member Kene Ene receives 2022 APSC student star award
Ibrahim Yousef receives 2022 DYCOPS Young Author award.
New paper on machine learning approaches for energy systems published in Renewable Energy.
Daniel and Seoun successfully defended their MASc thesis and MEng project respectively