CHEG 4147: Process Dynamics & Control
- Upcoming: Spring 2025
- Previously offered: Spring 2022, Spring 2023, Spring 2024
- Recommended Book:
- Process Dynamics and Control, 4th Edition by Dale E. Seborg, Thomas F. Edgar, Duncan A. Mellichamp, Francis J. Doyle III
Chemical process modeling, dynamics, and analysis. Measurement and control of process variables, design, and computer simulation of simple processes and control systems.
Prerequisites: CHEG 3112; CHEG 3124; MATH 2110Q; MATH 2410Q; open only to School of Engineering students.
CHEG 5330: Applied Machine Learning in Chemical Engineering
- Upcoming: Fall 2025
- Previously offered: Fall 2022, Fall 2023
- Recommended Material:
- An Introduction to Statistical Learning with Applications in R, Second Edition by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
- Python for Everybody by Charles R. Severance
- Data Science Using Python and R by Chantal D. Larose, Daniel T. Larose
This course is an applied machine learning algorithms course tailored for the chemical/process engineers. The focus of this course from is on case studies and real-world examples seen by chemical engineers. The course will include exposure to machine learning, data science & analytics, and big data in a chemical engineering context. Students are taught to identify descriptors and predict and optimize system properties using a machine learning approach.
Prerequisites: Instructor consent.
CHEG 5336: Optimization
- Upcoming: TBA
- Previously offered: Fall 2024
- Recommended Material:
- Floudas C.A., “Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications” Oxford University Press, 1995. ISBN 9780195100563. https://academic.oup.com/book/40799
- Williams H.P., “Model Building in Mathematical Programming” 5th Edition. Wiley. ISBN 978-1-118-44333-0
- Bazaraa M.S., Jarvis J.J., Sherali H.D. “Linear Programming and Network Flows” 4th Edition. Wiley. ISBN 978-0-470-46272-0
- Cornell University Computational Optimization Open Textbook. Access here: https://optimization.cbe.cornell.edu/index.php?title=Main_Page
Advanced topics in optimization such as linear and nonlinear programming, mixed-integer linear and nonlinear programming, deterministic and stochastic global optimization, and interval global optimization. Example applications drawn from engineering.
Prerequisites: None.