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Lee Rippon

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
Philip Loewen (Math)
📨 Contact
💻 GitHub
https://github.com/LeeRippon
Linkedin
https://www.linkedin.com/in/leerippon
🔗 Website
https://leerippon.com/

DAIS Lab Publications

  1. Conference Proceedings
    Cross-directional controller performance monitoring for paper machines
    , , , , , , ,
    In proceedings of American Control Conference, Chicago, USA.
    pp. 4970 – 4975. 2015
  2. 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]
  3. Patent
    Closed-loop model parameter identification techniques for industrial model-based process controllers
    , , , , , ,
    US Patent App. 15. 2018
  4. 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]
  5. 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]
  6. Journal Paper
    Machine Direction Adaptive Control on a Paper Machine
    , , , , ,
    Industrial & Engineering Chemistry Research. 2019 [PDF]
  7. 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]
  8. Journal Paper
    Representation Learning and Predictive Classification: Application with an Electric Arc Furnace
    , , , , , , , ,
    Computers & Chemical Engineering. 2021 [PDF]
  9. Journal Paper
    Visualization of Multiscale Ring Formation in a Rotary Kiln
    , , , , ,
    Nordic Pulp and Paper Research Journal. 2021 [PDF] [Code]
  10. 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]
  11. Journal Paper
    The Arc Loss Challenge: A Novel Industrial Benchmark for Process Analytics and Machine Learning
    , , , ,
    Journal of Process Control. 2023 [PDF]

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Highlights - 21 January 2024

DAIS Lab publishes its 100th journal article in Automatica!

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