Department of Industrial and Systems Engineering ushers in AI Integration
The Â鶹ÊÓƵ Department of Industrial and Systems Engineering has integrated Artificial Intelligence (AI) as a fundamental technology taught to solve problems in robotics, quality control, reliability, safety, and supply chain management. 
The department has added new graduate coursework in User Experience with Artificial Intelligence and Artificial Intelligence for Industrial Engineering. These classes allow students to learn and explore rapidly evolving AI techniques (LLM, Transfer Learning, Image Processing). The department has also added AI to existing courses on machine learning and applied programming courses. Students in the department have the option to enroll in AI, software development, and machine courses offered by the Computer Science Department and the College of Business.
For the first time this fall, associate professor of Industrial and Systems engineering Dr. Yueqing Li taught User Experience with AI. The course teaches the theory and practice of the design, implementation, and evaluation of software user experience with emphases on interaction with artificial intelligence models. The course has a group project that develops a user interface. The students have come up with a range of AI-related project ideas such as scheduling assistants, text summarization, sign language translator, and shopping bots. The students developing these ideas within a UX framework with steps including project ideas, project proposal, storyboards, low-fidelity prototype, user testing, and high-fidelity working prototypes.
“Artificial intelligence is impacting how we interact with the world dramatically day to day. Including artificial intelligence in the curriculum will prepare our students for their future career,” Dr. Li said.
In the Spring of 2024, Dr. Alberto Marquez, associate professor of Industrial and Systems Engineering, will be teaching AI for Industrial Engineering for the first time. The course is a series of projects where students identify AI solutions for common industrial engineering tasks including software development, quality control, data cleaning, data analysis, reviewing text records, automating business processes, and writing reports. Students will explore the important question of how much AI can automate tasks today. The teams will present their work to each other to develop best practices for current technology, and share creative solutions.
Recent doctoral students have used AI to predict equipment failure, analyze free response survey data, and identify the use of PPE. Master’s students have explored document generation and natural language processing of text data.
"As the models become less expensive to develop and run due to transfer learning, better computer hardware and better software development frameworks, a wide range of use cases will become cost effective,” Dr. James Curry, Chair of Industrial Engineering said. “As with all math modeling, the critical skill is to identify if the problems require a model-based solution as opposed to a simpler low risk solution."
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