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Faculty Highlight: Integration of Research and Education in Civil Engineering


By Dr. Hamid Mansouri Rad, Senior Proposal Development Specialist, RAS
NMSU Office of Research, Creativity and Strategic Initiatives

We value the scholarly activities of all NMSU faculty and staff, in particular those who contribute to the research mission of the university. Such contributions are regularly recognized when faculty submit large proposals or garner external awards; however, monitory value is not the only measure of research excellence. NMSU faculty regularly develop innovative approaches that often lead to strengthening our research capabilities, or contribute to research scholarships, efforts that we wish to highlight in the Research Digest.

An NMSU faculty whose scholarly innovations need to be recognized is Assistant Professor Doeun Choe, an early career faculty in the Department of Civil Engineering. Choe’s research interests include artificial intelligence (AI) and deep learning, which is an extension of her main expert area of probabilistic modeling in civil engineering. As she explains, her long-term research goal is to advance knowledge on uncertainty, risk, and reliability within human-built environments and to enhance the resilience of our structures such as buildings, bridges and other facilities that support the human’s basic and critical needs.

“AI is another tool just like mathematics for engineers. It will contribute to improving knowledge within many engineering fields, especially those we couldn’t solve with our traditional tool, mathematics.” She states. “However, it is also very important that we understand and use this new tool, AI, properly.”

Teaching various topics in her area, Choe has recognized that there are gaps between students’ coursework and their research experiences. Her vision is to address this gap in the courses she offers, namely a two-semester course series that she teaches in her department, AI for Civil Engineers I: Machine Learning (CE 498/596 Undergraduate & Graduate Special Topics) and AI for Civil Engineers II: Deep Learning (CE 596: Graduate Special Topics). In fall 2022, she offered AI for Civil Engineers I: Machine Learning (ML) and is currently continuing Deep Learning (AIDL) in spring 2023. The AIML course aims to introduce broad civil engineering problems in various areas such as structures, materials, environmental engineering and geotechnical engineering. Choe’s goal for this semester was for each student to apply artificial intelligence learned during the course to their own scientific interest areas.

To achieve this goal, she dedicated three quarters of the course to lectures helping students learn ML tools/skills, while devoting one quarter of the course to application of ML to students’ own areas that allows students to conduct their individual research projects using the course material, which she compares to a design studio course. This course has so far resulted in 10 high-quality student research posters that were exhibited last month in January in Hernandez Hall.

As Choe reports, the outcome of these activities include:

  • Being able to identify appropriate data analysis methods for various civil engineering problems,
  • being able to perform various ML analyses using Matlab/Python to solve civil engineering problems, and
  • being able to find an appropriate ML method and apply them for the research problems within the students’ domain.

For more information, please contact Choe at