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Jiayang Ren

A PhD student working on optimzation, interpretable machine learning, and control at University of British Columbia.

About Me

I am graduating in Spring 2026 πŸŽ‰πŸŽ‰πŸŽ‰ and am actively seeking a Post-Doctoral position in Process Modeling and Control.


I’m currently a PhD candidate working with Prof. Yankai Cao at the Department of Chemical and Biological Engineering, University of British Columbia, Canada. I obtained my Bachelor’s and Master’s degrees in Control Science from Zhejiang University in 2018 and 2021 under the supervision of Prof. Dong Ni.

My research addresses the critical need for both high performance and clear interpretability in systems used for chemical process, energy, and healthcare. I tackle the common trade-off between accuracy and transparency by developing advanced optimization algorithms for interpretable machine learning models. I applied these interpretable models to various real-world problems, such as learning interpretable model predictive control laws via oblique decision trees.


πŸ”₯ News

πŸ† 2025-11 Honored to enter the Finalists of CAST Director’s Student Presentation Award, presenting my work on interpretable machine learning for process control.
πŸ† 2025-08 Honored to receive the Wall Research Award .
πŸ“° 2025-07 Our paper about "Exact Learning of Linear Model Predictive Control Laws using Oblique Decision Trees with Linear Predictions" is accepted by 64th IEEE Conference on Decision and Control (CDC).
πŸ“° 2025-02 Our paper about "A Global Optimization Algorithm for K-Center Clustering of One Billion Samples" is accepted by Management Science.
πŸ“° 2024-12 Our paper about "Hierarchical model predictive control for energy consumption regulation of industrial-scale circulation counter-flow paddy drying process" is accepted by Energy.
πŸ“° 2024-04 Our paper about "Deep Learning-Based Approximation of Model Predictive Control Laws Using Mixture Networks" is accepted by IEEE Transactions on Automation Science and Engineering.
πŸ“° 2022-09 Two papers about global optimization of large-scale K-Medoids Clustering and Decision Tree are accepted by NeurIPS 2022. Thanks to my co-authors Dr. Kaixun Hua and Prof. Yankai Cao.

πŸ“¬ Contact Me

  • rjy12307@outlook.com
  • Chemical & Biological Enigneering
    2360 East Mall
    Vancouver, BC Canada V6T 1Z3


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