Zukui Li, PhD

Professor, Faculty of Engineering - Chemical and Materials Engineering Dept

Contact

Professor, Faculty of Engineering - Chemical and Materials Engineering Dept
Email
zukui@ualberta.ca
Phone
(780) 492-1107
Address
13-271 Donadeo Innovation Centre For Engineering
9211 116 St
Edmonton AB
T6G 2H5

Overview

Area of Study / Keywords

Process Systems Engineering Mathematical Optimization Process Control Oil Sands Energy Data Analytics Machine Learning


About

Dr. Li holds a Bachelor's degree (2002) in Automatic Control and a Master's degree (2005) in Control Theory and Control Engineering from the University of Science and Technology of China. Dr. Li received his Ph.D. in Chemical Engineering from Rutgers University in 2010. Dr. Li was a postdoctoral research associate in Princeton University from June 2010 to December 2012. He joined the University of Alberta as an Assistant Professor in January 2013. 

https://sites.ualberta.ca/~zukui/


Research

Dr. Li's research interests include: 

  1. Process operations involving scheduling, planning and supply chain management, as well as process design and process control with a focus on energy systems applications; 
  2. Nonlinear and mixed integer optimization, with a focus on addressing uncertainty through robust optimization, stochastic programming and parametric programming techniques;
  3. Systems engineering in biomedical and biotechnology applications including anemia management and biomarker discovery.

Keywords: Process Systems Engineering, Mathematical Optimization, Process Control, Computational Biology

Courses

CH E 358A - Process Data Analysis

Statistical analysis of process data from chemical process plants and course laboratory experiments. Topics covered include least squares regression, analysis of variance, propagation of error, and design of experiments. Prerequisites: CH E 351 and STAT 235. Corequisites: CH E 314 and 345.


CH E 358B - Process Data Analysis

Statistical analysis of process data from chemical process plants and course laboratory experiments. Topics covered include least squares regression, analysis of variance, propagation of error, and design of experiments. Prerequisites: CH E 351 and STAT 235. Corequisites: CH E 314 and 345.


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