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 Vice-Provost and Associate Vice-President, Faculty Planning in the Office of the Provost and Vice-President Academic, UBC Vancouver. From 2017 to 2022, he was the Associate Dean for Education and Professional Development in the UBC Faculty of Applied Science. 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.
We recruit year-round for postdocs, MASc and PhD students, visiting students and undergraduate students. Please see our Opportunities page for more information.
DAIS Lab Highlights
DAIS Lab News
Liang Cao wins award at the 2024 IEEE/CAA JAS Conference on Automation for Industry 5.0.
UBC-Rogers partnership creates opportunities for AI-enabled research to redefine emergency room patient care
Faye wins EDI.I Excellence Award at the BioProducts Institute Research Day
DAIS Lab updates for March 2024.
DAIS Lab publishes its 100th journal article in Automatica.
Iman Jalilvand wins Silver Award at 2023 HCI International Student Design Competition.
6 papers from the UBC DAIS Lab has been accepted to the IFAC World Congress 2023.