Master of Intelligent Process Control


Master of Intelligent Process Control


The master’s degree in Intelligent process control will bring together students from several engineering backgrounds and enable them to take advantage of the comprehensive variety of available course contents and experienced faculty in the topics related to digitalized of process automation in general. Students will learn about process modeling and simulation, instrumentation and control, optimization, process data collection and manipulation to extract intelligent information necessary for decision making including the use of digital twin in enhancing operation and control.

This master program will provide students with in-depth theoretical knowledge along with practical experience in the development of intelligent process control, which represents an interdisciplinary field that involves chemical engineering, electrical engineering, instrumentation and control engineering, mechanical engineering, math and computing, as well as business management.

The Master program consists of 8 core courses from different disciplines that cover four domains: Modeling and simulation, control and intelligent instrumentation networks, advanced controller design techniques, Data analyses, AI/Machine learning in decision making. In addition, the student must finish a final project during the last two semesters. The final project will be completed under the program affiliated faculty supervision and will integrate the skills acquired from the core courses to work on intelligent process control related subjects.

Program Requirement:

The applicant should have an accredited bachelor’s degree or its equivalent degree in Mechanical Engineering, Electrical/Electronic Engineering, Control and Instrumentation System Engineering, Chemical Engineering, Petroleum Engineering, or discipline relevant to the program content.

Degree Plan:

First Semester

  • Introduction to Intelligent Process Control
  • Simulation of Chemical Processes
  • Instrumentation and Control Network
  • Intelligent Decision Support Systems (IDSSs) for Process Control

Second Semester

  • Optimal and Learning-based Process Control Design
  • Soft Computing for Identification
  • Cybersecurity of Industrial Control Systems
  • Project


  • Applied AI in Process Control
  • Project (Contd.)