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The UBC DAIS Lab conducts research at the intersection of process control, data analytics and machine learning. We develop novel algorithms and computational tools to bring a new level of automation to the process industry.
Data-Driven Dynamic Modeling and Online Monitoring for Multiphase and Multimode Batch Processes with Uneven Batch Durations
Machine Direction Adaptive Control on a Paper Machine
Towards Self-Driving Processes: A Deep Reinforcement Learning Approach to Control
Univariate model-based deadband alarm design for nonlinear processes
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Please see our [publications list]({{ site.baseurl }}/publications/) 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]({{ site.baseurl }}/people/). We upload our presentations and workshops to the [resources page]({{ site.baseurl }}/resources/).