Jinfeng Liu, PhD

Associate Professor, Faculty of Engineering - Chemical and Materials Engineering Dept

Contact

Associate Professor, Faculty of Engineering - Chemical and Materials Engineering Dept
Email
jinfeng@ualberta.ca
Phone
(780) 492-1317
Address
13-269 Donadeo Innovation Centre For Engineering
9211-116 St
Edmonton AB
T6G 2H5

Overview

Area of Study / Keywords

Process Systems Engineering Mathematical and Molecular Modeling Energy Artificial Intelligence


About

Dr. Liu received the BS and MS degrees in Control Science and Engineering from Zhejiang University in 2003 and 2006, respectively. He received the PhD degree in Chemical Engineering from the University of California, Los Angeles in 2011. Before joining the University of Alberta in April, 2012, Dr. Liu was a postdoctoral researcher at the University of California, Los Angeles. 


Research

Dr. Liu's research interests are in the general areas of process control theory and practice with emphasis on model predictive control, networked control systems, process monitoring, and optimal control of chemical processes, energy systems, wastewater treatment plants, agriculture irrigation systems and biomedical systems. The long-term goal is to develop techniques enabling sustainable smart plant operations, in which physical processes, computations, and communication are integrated to address plant-wide safety and environmental and economic considerations.

Keywords: Process Control, Model Predictive Control, Networked Control Systems, Moving Horizon Estimation, Optimization, Energy Systems, Wastewater Treatment Plants, Precision Irrigation, Biomedical

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.

Spring Term 2021
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.

Summer Term 2021

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