Daniel McClement

Daniel McClement

Originally from Calgary, Daniel moved to Vancouver to pursue a bachelor's degree in engineering at the University of British Columbia. After being allured by the scenic hikes and beaches around the city as well as the interesting research being done by the DAIS Lab, he chose to stay for his master's degree. He is now studying reinforcement learning for use in control systems. Outside of his studies, Daniel enjoys skiing at Cypress Mountain in the winter and hiking around Vancouver in the summer.

📚 Program/Degree
GROUP ALUMNI (2022) | MASc | Started 2020
📝 Research
Deep Reinforcement Learning Algorithms for Maintenance-free Control
👥 Also supervised by
📨 Contact

DAIS Lab Publications

  1. Conference Proceedings Keynote Presentation
    A Meta-Reinforcement Learning Approach to Process Control
    , , , ,
    In Proceedings of IFAC International Symposium on Advanced Control of Chemical Processes (ADCHEM, To Appear). 2021 [PDF] [Slides] [Video] [arXiv]
  2. Journal Paper
    Deep Reinforcement Learning with Shallow Controllers: An Experimental Application to PID Tuning
    , , , , ,
    Control Engineering Practice. 2021 [PDF]
  3. Conference Proceedings
    Meta-Reinforcement Learning for Adaptive Control of Second Order Systems
    , , , , ,
    In Proceedings of the 7th International Symposium on Advanced Control of Industrial Processes (AdCONIP). 2022 [PDF] [Video]
  4. Journal Paper
    Meta-Reinforcement Learning for the Tuning of PI Controllers: An Offline Approach
    , , , , ,
    Journal of Process Control. 2022 [PDF]

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