The College of Engineering (CENG) initiated a Summer Undergraduate Research Program (SURP) in 2017. The purpose of the program is to provide research experiences for our undergraduate students working alongside our faculty during the summer. This program also supports the scholarly efforts of our faculty through engagement with undergraduate students. Projects lead to student-faculty authored publications in venues appropriate to the area of research conducted during the summer. Further, the program invites industrial and other external sponsors to provide university-industry collaborative research and project activities.

This program supports Cal Poly’s educational mission as both faculty members and students are provided a significant opportunity for their professional growth. SURP students gain valuable training in research methods and practices, professional experience, have opportunities to apply classroom knowledge and theories in a research setting, and work in a team environment. Through collaboration with faculty members and external sponsors, SURP students gain “Learn by Doing” research experience that will support their growth as a student and set a foundation to build on as they pursue their career goals. Depending on the project, students may have tangible products such as data sets, hardware prototypes, software code, other forms of intellectual property, abstracts and/or research posters, and co-authored publications. SURP faculty participants are able to implement the teacher-scholar model while making progress in their area of research. Partnerships with industrial and external sponsors through SURP support the California State University’s mission of preparing significant numbers of educated and responsible people to contribute to California’s economy, culture, and future. Industrial and external SURP project sponsors gain a head start in cultivating professional relationships with talented and motivated SURP students.

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Submissions from 2023

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Machine Learning Prediction of HEA Properties, Nicholas J. Beaver, Nathaniel Melisso, and Travis Murphy

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Improving Semantic Document Classification Accuracy by Integrating Human-Crafted Knowledge, Zachary Weinfeld and Lubomir Stanchev