Recruitment
We recruit year-round for postdocs, MASc and PhD students, visiting students and undergraduate students. Please see our Opportunities page for more information.
Lee Rippon
Lee Rippon is a PhD student studying Chemical and Biologial Engineering (CHBE) at UBC. He also holds BASc and MASc degrees from UBC in CHBE where his research experience includes applications of compressive sensing, adaptive control, system identification and process monitoring on sheet and film processes. His current research interests include applying process analytics and machine learning techniques to historical process data to perform fault detection, isolation, and diagnosis in a kraft pulping process.
📚 Program/Degree
GROUP ALUMNI (2022) |
PhD
| Started 2017
📝 Research
Process Analytics and Machine Learning Techniques for the Kraft Pulping Process
👥 Also supervised by
💻 GitHub
🔗 Website
DAIS Lab Publications
-
Conference Proceedings
Cross-directional controller performance monitoring for paper machines
In proceedings of American Control Conference, Chicago, USA.
pp. 4970 – 4975. 2015 -
Conference Proceedings
Noncausal modeling and closed-loop optimal input design for cross-directional processes of paper machines
American Control Conference.
pp. 2837-2842. 2017 [PDF] [Slides] -
Conference Proceedings
Invited Paper
Pattern and Knowledge Extraction using Process Data Analytics: A Tutorial
In Proceedings of the 10th ADCHEM Conference, Shengyang, China.
pp. 13-18. 2018 [Code] -
Journal Paper
Data-Driven Dynamic Modeling and Online Monitoring for Multiphase and Multimode Batch Processes with Uneven Batch Durations
Industrial & Engineering Chemistry Research. 2019 [PDF] -
Journal Paper
Machine Direction Adaptive Control on a Paper Machine
Industrial & Engineering Chemistry Research. 2019 [PDF] -
Conference Proceedings
Process Analytics And Machine Learning to Predict Arc Loss In An Electric Arc Furnace
In proceedings of the 59th Conference of Metallurgists. 2020 [PDF] [Video] -
Journal Paper
Representation Learning and Predictive Classification: Application with an Electric Arc Furnace
Computers & Chemical Engineering. 2021 [PDF] -
Journal Paper
Visualization of Multiscale Ring Formation in a Rotary Kiln
Nordic Pulp and Paper Research Journal. 2021 [PDF] [Code] -
Conference Proceedings
Data Quality Over Quantity: Pitfalls and Guidelines for Process Analytics
In Proceedings of the 22nd IFAC World Congress. 2023 [PDF] [Slides] [Video] [arXiv] -
Journal Paper
The Arc Loss Challenge: A Novel Industrial Benchmark for Process Analytics and Machine Learning
Journal of Process Control. 2023 [PDF] -
Patent
Closed-loop model parameter identification techniques for industrial model-based process controllers
U.S. Patent No. 10,761,522. 2020
DAIS Lab Member? Submit a pull request or join the @daisubc organization on GitHub to update your profile - Lee Rippon.md.