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
Daniel and Nathan's paper on meta-reinforcement learning has been selected as a Keynote at ADCHEM 2021. Congratulations!
LinkDAIS Lab News
New papers from the DAIS lab accepted in Control Engineering Practice and Biofuels, Bioproducts and Biorefining.
New papers from Lee, Yiting and Ryan have been accepted
Lee wins Best Student Paper award at the PACWEST Technical Conference 2021.
Daniel McClement receives NSERC CGS M scholarship
Representation Learning and Predictive Classification - Application with an Electric Arc Furnace
1 - A Meta-Reinforcement Learning Approach to Process Control and 2 - Learning Physics Based Models of Lithium-ion Batteries
Lu et al. (2021) - 'Model-Plant Mismatch Detection for Cross-directional Processes' published in ISA Transactions