Vinay Prasad, PhD
Contact
Professor, Faculty of Engineering - Chemical and Materials Engineering Dept
- vprasad@ualberta.ca
- Phone
- (780) 248-1595
- Address
-
12-293 Donadeo Innovation Centre For Engineering
9211 116 StEdmonton ABT6G 2H5
Overview
Area of Study / Keywords
Process Systems Engineering Mathematical and Molecular Modeling Energy Reaction Engineering and Catalysis Artificial Intelligence/Machine Learning Mineral Processing
About
My degrees are in chemical engineering and my research training is primarily in process control and systems engineering. I have academic experience in India, the USA and Canada and industrial experience in India and the USA.
Research
My research focuses on process systems engineering, including multiscale modeling, process estimation and monitoring, advanced control and optimization. The analysis of complex systems based on machine learning, data mining and graph/network-based approaches is of particular interest. The application areas of the research include chemoinformatics, real-time monitoring of complex reacting mixtures, reservoir engineering, froth flotation, biomass conversion, heterogeneous catalysis, CO2 capture and microalgal processes.
Keywords: Process Control, Process Systems Engineering, Machine learning, Data analytics, Big data, Reaction engineering, Chemoinformatics, Reservoir engineering, Froth flotation, CO2 capture
Courses
CH E 446 - Process Dynamics and Control
Introduction to process modeling and transient response analysis; design and analysis of feedback systems; stability analysis; process control applications; process control using digital computers. Prerequisites: CME 265, MATH 201 and 209. Corequisite: CH E 312.
CME 265 - Process Analysis
Basic process principles; material and energy balances, transient processes, introduction to computer-aided balance calculations. Prerequisites: ENCMP 100, MATH 102 and CHEM 105. Corequisites: CH E 243 and MATH 209 or equivalent. Credit may not be obtained in this course if previous credit has been obtained for CH E 265.
CME 660 - Advanced Process Data Analytics
Multivariate statistics. Process systems engineering objectives: modeling, estimation, monitoring, control, optimization, and their relationship to data analytics. Feature extraction and dimension reduction, clustering, classification, regression. Nonlinear techniques and analysis of dynamic data. Applications of advanced data analytics in chemical process engineering.