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Jiayang Ren

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

Publications

A full publication list is available on Google Scholar.
Here, 📜 - Conference, 📖 - Journal, * - Co-First Author

1️⃣ Advanced Optimization for Interpretable AI

  • 📖 [Management Science]: Ren, J., Hua, K. and Cao, Y. (2025). A Global Optimization Algorithm for K-Center Clustering of One Billion Samples.
  • 📖 [Informs Journal on Computing]: Ren, J. and Cao, Y. (2025). GO-Clustering.JI: A Julia Package for Global Optimal Centroid-Based Clustering. In Preparation.
  • 📖 [Informs Journal on Computing]: Ren, J., Valentín, O. and Cao, Y. (2025). A GPU-Accelerated Moving-Horizon Algorithm for Training Deep Classification Trees on Large Datasets. Under Review.
  • 📜 [NeurIPS]: Mao, Q., Ren, J., Wang, Y., Zou, C., Zheng, J., Cao, Y. (2025). Differentiable Decision Tree via “ReLU+Argmin” Reformulation. Under Review.
  • 📜 [NeurIPS]: Zou, C, Ren, J., Mao, Q., Liu, J., Lai, M., Cao, Y. (2025). A Moving-Horizon Approximate Branch-and-Reduce Method for Deep Classification Trees. Under Review.
  • 📜 [NeurIPS]: Ren, J., Hua, K. and Cao, Y. (2022). Global Optimal K-Medoids Clustering of One Million Samples.
  • 📜 [NeurIPS]: Hua, K., Ren, J. and Cao, Y. (2022). A Scalable Deterministic Global Optimization Algorithm for Training Optimal Decision Tree.
  • 📜 [ICML]: Shi, M., Hua, K., Ren, J., and Cao, Y. (2022). Global Optimization of K-Center Clustering.

2️⃣ Interpretable AI for Process Modeling and Control

  • 📖 [Automatica]: Ren, J., Mao, Q., Zhao, T., and Cao, Y. (2025). Learning Model Predictive Control Laws using Interpretable Oblique Decision Trees with robust considerations. Submitted.
  • 📖 [Energy]: Li*, C., Ren*, J., Chen, Y., Zhang, X., Fang, Z. and Cao, Y. (2025). Hierarchical model predictive control for energy consumption regulation of industrial-scale circulation counter-flow paddy drying process.
  • 📖 [IEEE Transactions on Automation Science and Engineering]: Okamoto, M., Ren, J., Mao, Q., Liu, J., and Cao, Y. (2024). Deep Learning-Based Approximation of Model Predictive Control Laws Using Mixture Networks.
  • 📖 [Industrial & Engineering Chemistry Research]: Li, Y., Wang, Y., Chen, Y., Lu, Y., Hua, K., Ren, J.,… and Cao, Y. (2022). Deep-Learning-Based Predictive Control of Battery Management for Frequency Regulation.
  • 📜 [ICML]: Liu, P., Hao, Z., Ren, X., Yuan, H., Ren, J., & Ni, D. (2024). PAPM: A Physics-aware Proxy Model for Process Systems.
  • 📜 [CDC]: Ren, J., Mao, Q., Zhao, T., and Cao, Y. (2025). Exact Learning of Model Predictive Control Laws using Oblique Decision Trees with Linear Predictions.
  • 📜 [ADCHEM]: Wang, Y., Kumar, A., Ren, J., You, P., Seth, A., Gopaluni, R.B. and Cao, Y. (2024). Interpretable Data-Driven Capacity Estimation of Lithium-ion Batteries.
  • 📜 [ESCAPE]: Ren, J., Hua, K., Trajano, H., and Cao, Y. (2023). Global Optimal Explainable Models for Biorefining.

3️⃣ Data-driven Fault Detection Algorithms for Batch Processes

  • 📖 [IEEE Transactions on Semiconductor Manufacturing]: Ren, J., and Ni, D. (2021). A Real-Time Monitoring Framework for Wafer Fabrication Processes With Run-to-Run Variations.
  • 📖 [Chemical Engineering Research and Design]: Ren, J., and Ni, D. (2020). A batch-wise LSTM-encoder decoder network for batch process monitoring.
  • 📜 [PATENT]: Ni, D., Zhu, F. and Ren, J. (2018). Plasma components spatial distribution method for real-time measurement and its device based on light spectrum image-forming.
  • 📜 [Chinese Automation Congress (CAC)]: Ren, J., and Ni, D. (2019). Real-time Fault Detection System for Multiphase Plasma Etching Process using OES, Two-Step Division and Change Stage Alignment Method.