Siang Lim

Siang Lim

Siang graduated from UBC with distinction in chemical engineering and was selected as a 2017 Faculty of Applied Science Rising Star. He completed an NSERC USRA term with the DAIS Lab and is currently pursuing a MSc in Computer Science (OMSCS) at Georgia Tech while working on process control and data science at the Burnaby Refinery.



📚 Program/Degree
GROUP ALUMNI (2017) | Undergraduate | Started 2017
📝 Research
Machine Learning and Process Control
📨 Contact

DAIS Lab Publications

  1. Conference Proceedings Invited Paper
    Pattern and Knowledge Extraction using Process Data Analytics: A Tutorial
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    In Proceedings of the 10th ADCHEM Conference, Shengyang, China.
    pp. 13-18. 2018
    [Code]
  2. Journal Paper
    A Comparison of Clustering and Prediction Methods for Identifying Key Chemical–Biological Features Affecting Bioreactor Performance
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    Processes. 2019 [PDF] [Code]
  3. Journal Paper
    Interactive Visualization for Diagnosis of Industrial Model Predictive Controllers with Steady-State Optimizers
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    Control Engineering Practice. 2021 [PDF] [Thesis] [Video]
  4. 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]
  5. Journal Paper
    Causal Discovery based on Observational Data and Process Knowledge in Industrial Processes
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    Industrial & Engineering Chemistry Research. 2022 [PDF]
  6. 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]
  7. Conference Proceedings
    Interpretable Soft Sensors using Extremely Randomized Trees and SHAP
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    In Proceedings of the 22nd IFAC World Congress. 2023 [PDF] [Slides] [Video]
  8. Conference Proceedings
    Data Quality Over Quantity: Pitfalls and Guidelines for Process Analytics
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    In Proceedings of the 22nd IFAC World Congress. 2023 [PDF] [Slides] [Video] [arXiv]
  9. Journal Paper
    Real-Time Tracking of Renewable Carbon Content with AI-aided Approaches During Co-Processing of Biofeedstocks
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    Applied Energy. 2024 [PDF]

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