UNIVERSITY PARK, Pa. — As Penn State embarks on a multi-year AI transformation initiative to expand its enterprise artificial intelligence (AI) tools, provide AI upskilling for faculty, and teach critical AI literacy skills to students, faculty are exploring innovative ways to give students hands-on opportunities with AI and machine learning. Over a two-week period in May, Hongtao Sun, assistant professor in the Harold and Inge Marcus Department of Industrial Manufacturing Engineering, hosted 13 students for a two-week summer research experience (REU) for undergraduates focused on research using AI. The program was managed through Sun’s research lab, AI-driven materials design and manufacturing.
“I founded this program to create an opportunity for a wide range of undergraduate students from different backgrounds and levels of expertise to learn together about hands-on research in machine learning,” said Sun.
Machine learning, a branch of artificial intelligence that allows computers to identify patterns and make predictions from data, has powerful applications across multiple fields and provides skills that will be useful not only for the future of science and technology, but also for students, Sun said.
The program grew out of Sun’s previous experience supervising undergraduate students in the lab. Among them is Steven Traczik, an industrial engineering undergraduate who first enrolled in one of Sun’s courses before joining the lab. Although Traczik had no experience in machine learning research, he contributed to a project that used artificial intelligence to predict the mechanical behavior of advanced 3D printed materials. This study supports future applications in smart manufacturing, digital twins, structural monitoring, and soft robotics by predicting how deformation patterns evolve under mechanical loading. Traczik is also a co-author of a peer-reviewed paper published in May in ACS Applied Engineering Materials. Sun said this experience proved that undergraduate students from a variety of fields can make meaningful contributions to AI-powered scientific research if provided with the right guidance and hands-on research opportunities.
“Many people think that machine learning research is only available to students with strong backgrounds in computer science, but our experience shows that this is not the case,” Sun said. “Students from a variety of disciplines can successfully learn and apply machine learning tools. Our research integrates artificial intelligence with practical experimental science and engineering, allowing students to collect their own data, develop machine learning models, and directly explore how AI can help analyze complex science and engineering problems.”
The first cohort included 13 Penn State undergraduates across multiple engineering majors, including industrial, mechanical, and aerospace engineering. The two-week program combines hands-on exposure to engineering research with basic training in artificial intelligence. During the first week, students participated in a series of lab visits and hands-on activities focused on energy storage and 4D printing. The second week featured a series of lectures covering machine learning fundamentals, neural networks, and data-driven research.
Aryan Ingle, a senior in aerospace engineering, said she was attracted to Sun’s program because of its focus on innovation and interdisciplinary collaboration, and said she appreciated Sun’s enthusiasm during initial discussions.
“Dr. Sun was passionate about training students in the basic mathematics, programming, and conceptual understanding of AI,” Ingle said. “I learned the basic programming and mathematics behind common classification and predictive models, neural networks, and generative AI systems. This AI implementation is massive in my field of research as a new space race begins.”
Sun also used the program to introduce students to Penn State’s extensive network of resources, including the Roar supercomputer housed in the Computational and Data Science Institute.
“We introduced the students to a basic working environment for AI-related research, including leveraging Penn State resources such as the Roar supercomputer,” Sun said. “We introduced them to Linux-based computing environments and showed them how these resources support modern AI and data-driven research.”
The program is closely aligned with broader efforts within the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering to prepare students for an increasingly AI-driven workforce. Lynn Rothrockinterim chair of the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering.
“Artificial intelligence is becoming an essential tool across engineering and manufacturing,” said Rothrock. “We are committed to providing opportunities for students to develop AI literacy and practical skills through hands-on experience. Programs like this help students understand how AI can be applied to real-world challenges and prepare for careers in engineering, advanced manufacturing, and emerging technology fields.”
Sun said he hopes to continue the program and expand opportunities for undergraduate students to participate in AI-powered research projects. He also plans to help students pursue individual research experiences within their own labs or in collaboration with supervisors in their respective fields.
“For the next REU program, we hope to recruit students from a broader range of majors, including fields other than engineering,” Sun said. “Machine learning is becoming an important tool in almost every field, and we hope this program will help students gain the skills and confidence to apply AI to advance research in their areas of interest.”
