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 at UBC Vancouver. 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:
Paper
Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior
Automatica. 2024 [PDF] [Code] [arXiv]
Paper
Paper
Paper
From automated to autonomous process operations
Computers & Chemical Engineering. 2025
Paper
Research Themes
Recent advances in machine learning, large-scale optimization, and computational infrastructure have created unprecedented opportunities for transforming industrial processes. These developments enable us to extract actionable insights from complex, high-dimensional data and deploy intelligent systems that can adapt and learn in real-time.
The process industries generate vast amounts of heterogeneous data from sensors, control systems, and operational records. Our research focuses on developing principled approaches to leverage this data for improved decision-making, predictive maintenance, fault detection, and autonomous control.
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
New paper on ML-driven CO2 capture materials discovery published in npj Computational Materials!
LinkNew perspective paper on autonomous process operations published in Computers & Chemical Engineering!
LinkDAIS Lab News
DAIS Lab celebrates the graduation of two PhD students.
Ahmed Abdalla wins 2nd place in the CHBE 3-Minute Thesis Competition
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.