REU Site: Research on Perspective Analytics for AI-enabled Operations Engineering
Overview
In recent years, the adoption of prescriptive analytics, an integration of machine learning and operations research methods, has enabled data-driven planning and decision-making in the three main sectors of the economy: services, manufacturing, and agriculture. Therefore, it is viewed as a promising approach for alleviating key challenges of these industries, such as high expenditure, supply-demand mismatch, and operational uncertainties. Our goal is to develop a new REU site to fill the gap in student knowledge on prescriptive analytics that is nascent in the current engineering curriculum. This REU program will not only equip students with the required knowledge but provide them with the skill set to conduct research on delivering intelligent/scalable prescriptive analytics solutions to real-world problems.
While predictive analytics has been widely explored by researchers, the research methods and applications of prescriptive analytics are increasingly gaining attention in recent years. Moreover, with the recent digital transformation and evolution of Service 4.0, Manufacturing 4.0, and Agriculture 4.0, several industry organizations are revolutionizing their systems to improve operational efficiencies.
The objective of this REU site is to train students to conduct research on state-of-the-art prescriptive analytics and develop AI-enabled solutions for real-world applications in Service 4.0, Manufacturing 4.0, and Agriculture 4.0.
The summer program will cultivate student interest in developing several creative and novel research works. Sample projects include:
real-time scheduling models to optimize the planning and control of an unmanned ground vehicle (UGV) - transfer robots
creating a Blockchain system for healthcare process improvement
designing decomposition-based iterative optimization algorithms for dynamically dispatching and routing unmanned aerial vehicles (UAVs), i.e., drones and air taxis
understanding genotype, environment and management interaction using deep learning
The student projects in our REU Site will build upon the transformative research conducted by faculty mentors in prescriptive analytic methods across different sectors. The student projects will be aligned with faculty mentors’ ongoing research and will be designed for students with diverse backgrounds and abilities. They will also be tailored appropriately during the program, depending on the student's preparation levels. This emerging artificial intelligence (AI)-enabled operations engineering area is multidisciplinary and has gained much significance in recent years due to the advances in Information and Communication Technologies (ICT), such as Industrial Internet of Things (IIoT), Cyber Physical Production Systems (CPPS), smart wireless in-field sensor network, and edge and cloud computing systems.