Teaching

ES 1050 Foundations of Engineering Practice (Laboratory Instructor)

This course introduces the principles and practices of professional engineering. Team-based design projects provide context for developing research, critical thinking, and problem-solving skills along with professional behavior. This course includes elements of need recognition, conceptualization, prototyping, and engineering design to satisfy commercial specifications. It emphasizes creativity, teamwork, time management, communication, and engineering skills necessary to practice in any engineering discipline. At the end of this course, students will be able to model professional engineering behavior and work in teams to execute all parts of a systematic design process, including seeking and critically examining information identifying and addressing knowledge gaps and communicating effectively with clients and other stakeholders.

CBE 2291 Computational Methods for Engineers

This course introduces model formulation for various chemical, biochemical and environmental processes, numerical techniques in solving the associated equations, and basic concepts of Artificial Intelligence (AI). A variety of numerical methods will be introduced with their application to the solution of problems in the chemical engineering field. These problems include linear and nonlinear algebraic equations, root problems, numerical optimization, finite difference methods, interpolation, linear and nonlinear regression analysis, differentiation and integration, and ordinary differential equations (initial value and boundary value problems). MATLAB will be introduced and extensively used as a computing tool to solve all the problems mentioned above. Students will learn both the object-oriented programming and command line modes of MATLAB and apply them to the solution of a variety of problems involving optimization and dynamic simulation of engineering processes. This course will also provide students with a foundational overview of AI, bridging the gap between traditional computational methods and modern AI approaches in chemical engineering. This brief overview aims to acquaint students with the potential of AI as a tool in engineering problem-solving, setting the stage for more advanced studies in the field.

CBE 4413 Artificial Intelligence in Chemical and Biochemical Engineering

In chemical and biochemical engineering, practitioners frequently encounter complex challenges that demand problem-solving and decision-making skills in various areas, including process and product design, fault diagnosis and control, optimization, and process operations and safety. Traditionally, chemical and biochemical engineers have been adopting modeling concepts and techniques from diverse fields such as applied mathematics and operations research. Over the last three decades, the integration of Artificial Intelligence (AI) methods into these approaches has become increasingly prevalent. The necessity for incorporating AI-based techniques into the skillset of well-trained chemical and biochemical engineers has now been evident. This course seeks to address this crucial need.