Liang Cao

Liang Cao

Liang Cao is a Ph.D. student studying Chemical and Biological Engineering (CHBE) at UBC. He received his BASc and MASc in Automation/Control Engineering from Beijing University of Chemical and Technology in China. He also is a joint master student at the University of Duisburg-Essen (Germany) and a research assistant at Tsinghua University (China). His current Ph.D. research interests focus on applying machine learning techniques to historical refinery process data to build inferential sensors, extract causality, and mine sequence patterns.

πŸ“š Program/Degree
PhD | Started 2019
πŸ“ Research
Soft Sensor Design and Causality Extraction in Industrial Processes
πŸ‘₯ Also supervised by
πŸ“¨ Contact

DAIS Lab Publications

  1. Journal Paper
    Data-driven Dynamic Inferential Sensors Based on Causality Analysis
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    Control Engineering Practice. 2020 [PDF]
  2. Journal Paper
    A Novel Approach to Alarm Causality Analysis Using Active Dynamic Transfer Entropy
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    Industrial & Engineering Chemistry Research. 2020 [PDF]
  3. Journal Paper
    Determining the amount of 'green' coke generated when co-processing lipids commercially by fluid catalytic cracking (FCC)
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    Biofuels, Bioproducts and Biorefining. 2021 [PDF]
  4. Conference Proceedings
    Online Capacity Estimation of Lithium-ion Batteries by Partial Incremental Capacity Curve
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    Proceedings of the 19th IEEE Vehicle Power and Propulsion Conference (To Appear). 2022 [PDF]
  5. Conference Proceedings
    Soft Sensor Change Point Detection and Root Cause Analysis
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    Society of Instrument and Control Engineers (SICE) Annual Conference, Kumamoto, Japan (To Appear). 2022 [PDF] [Slides]
  6. Journal Paper
    Causal Discovery based on Observational Data and Process Knowledge in Industrial Processes
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    Industrial & Engineering Chemistry Research. 2022 [PDF]
  7. Journal Paper
    Tracking the green coke production when co-processing lipids at a commercial fluid catalytic cracker (FCC): combining isotope 14C and causal discovery analysis
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    Sustainable Energy & Fuels. 2022 [PDF]
  8. Conference Proceedings
    Interpretable Soft Sensors using Extremely Randomized Trees and SHAP
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    In Proceedings of the 22nd IFAC World Congress (To Appear). 2023 [PDF] [Slides] [Video]
  9. Conference Proceedings
    Frequent Event Pattern Extraction of Drilling Time Series Using Change Point Detection and Event Sequence Generation (I)
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    In Proceedings of the 22nd IFAC World Congress (To Appear). 2023 [PDF] [Slides] [Video]
  10. Journal Paper
    False alarm reduction in drilling process monitoring using virtual sample generation and qualitative trend analysis
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    Control Engineering Practice. 2023 [PDF]
  11. Journal Paper
    Adaptive Online Optimization of Alarm Thresholds using Multilayer Bayesian Networks and Active Transfer Entropy
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    Control Engineering Practice. 2023 [PDF]
  12. Journal Paper
    Long Short-Term Memory Network with Transfer Learning for Lithium-ion Battery Capacity Fade and Cycle Life Prediction
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    Applied Energy. 2023 [PDF]

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