CV(web)

Zhongyu Zhang

PhD candidate working on uncertainty-aware modeling, optimization, and process systems engineering.

Links

Google Scholar / webzhongyu.com / zhongyu4@ualberta.ca / GitHub

Education

University of Alberta

PhD candidate, Process Control. Supervised by Prof. Zukui Li and Prof. Biao Huang.

2023.01 - present / Edmonton, Alberta, Canada

University of Alberta

MSc Degree, Process Control. GPA: 3.8/4.0. Supervised by Prof. Zukui Li.

2020.09 - 2022.12 / Edmonton, Alberta, Canada

Shandong University

BEng Degree, Automation. GPA: 4.17/5.

2016.09 - 2020.06 / Jinan, Shandong, China

Skills

Research & Modeling

  • Optimization with uncertainty
  • Flexibility analysis
  • Control theory

Machine Learning & Data

  • Physics-informed neural networks
  • Time-series forecasting
  • Classification and regression

Optimization & Applications

  • LP
  • NLP
  • MILP
  • MINLP
  • Smelting process optimization
  • Process fault diagnosis
  • Biomedical treatment planning
  • Petroleum molecular composition inference

Programming & Tools

  • Python
  • PyTorch
  • NumPy
  • SciPy
  • scikit-learn
  • OpenCV
  • Pyomo
  • GAMS
  • MATLAB
  • Git
  • Databricks

Web & Visualization

  • React
  • Gatsby
  • JavaScript
  • HTML/CSS
  • Node.js
  • Express
  • MySQL

Projects

KIVCET Furnace Feed Optimization (2025-2026)

Teck Metals Canada

  • Built a cloud-based pipeline to generate optimization recommendations for KIVCET furnace feed moisture and element-ratio control.
  • Implemented a constrained blending optimization model reflecting real operating bounds, and validated performance via multi-day simulation comparisons against manual operation results.
  • Automated KPI tracking and reporting to support daily decision-making and continuous model refinement with operations stakeholders.

Industrial Application of Model-Plant-Mismatch Detection (2024-2025)

Teck Metals Canada

  • Applied the Model-Plant-Mismatch Detection toolbox to identify potential mismatches in production systems, improving operational insights.
  • Migrated local detection code to a cloud platform, streamlining processes and enhancing daily reports with automated mismatch detection results.

Publications

  1. S. Li, Z. Li, Z. Zhang, et al. Database-driven and property-constrained inference of molecular composition of petroleum fractions from routine experimental data[J]. Chemical Engineering Journal, 2026: 176448.
  2. Z. Zhang, B. Huang, Z. Li. Simultaneous Outlier-Exclusion and Distributionally Robust Learning through Partial Optimal Transport. Computers & Chemical Engineering (2025): 109408.
  3. S. Li, Z. Zhang, Z. Li, G. Cai, L. Zhang, Q. Shi. Molecular composition reconstruction of naphtha fractions through data-driven modeling and interpretable optimization. Chemical Engineering Science (2025): 122655.
  4. Z. Zhang, B. Huang, Z. Li. Dynamic Process Flexibility Analysis Using Neural Networks and a Volumetric Flexibility Index. Industrial & Engineering Chemistry Research. 2025, 64, 7452-7465.
  5. Z. Zhang, S. Yang, B. Huang, Z. Li. Novel Feasible Set Learning and Process Flexibility Analysis Method Using Deep Neural Networks. Industrial & Engineering Chemistry Research. 2024, 63, 11516-11529.
  6. Z. Zhang, and Z. Li. Model Predictive Control for Renal Anemia Treatment through Physics-informed Neural Network. IFAC-PapersOnLine 58.14 (2024): 307-312.
  7. Z. Zhang, Z. Li. Haemoglobin Response Modelling under Erythropoietin Treatment: Physiological Model-Informed Machine Learning Method. The Canadian Journal of Chemical Engineering. 2023, 101, 4307-4319.
  8. Z. Zhang, B. Huang, Z. Li. Distributionally robust optimization for Gaussian mixture model ambiguity under moment variations. Computers & Chemical Engineering (Under Review).
  9. Z. Zhang, B. Huang, Z. Li. The Two Faces of Outliers in Robust Learning: Exclusion and Emphasis via Partial Optimal Transport. (Under Preparation).

Presentations

Distributionally Robust Optimization for Gaussian Mixture Model Ambiguity Under Moment Variations

Oral presentation in American Institute of Chemical Engineers (AIChE) Annual Meeting on November 3, 2025, Boston, Massachusetts, U.S.

Decision-focused Learning Considering Solution Robustness under Data Uncertainty

Oral presentation in Canadian Chemical Engineering Conference (CSChE 2025) on October 7, 2025, Montreal, Quebec, Canada.

Dynamic Process Operational Flexibility Analysis Using Neural Networks

Poster presentation in Canadian Chemical Engineering Conference (CSChE 2024) on October 6-9, 2024, Toronto, Ontario, Canada.

Model Predictive Control for Renal Anemia Treatment through Physics-Informed Neural Network

Poster presentation in 12th IFAC International Symposium on Advanced Control of Chemical Processes (ADCHEM) on July 14-17, 2024, Toronto, Ontario, Canada.

A Novel Volumetric Flexibility Index Calculation Method Using Physics-Informed Neural Networks

Oral presentation in American Institute of Chemical Engineers (AIChE) Annual Meeting on November 9, 2023, Orlando, Florida, U.S.

Awards

  • Graduate Students' Association Academic Travel Grant (2025)
  • Captain Thomas Farrell Greenhalgh Memorial Graduate Scholarship (2023)
  • Graduate Students' Association Academic Travel Grant (2023)

Teaching Assistant Experience

  • CHE 574 Process Optimization (Winter 2026)
  • CHE 358 Process Data Analytics and Machine Learning (Spring/Summer 2024)

Zhongyu Zhang