Internship Highlight: Cameron Sierra, Westinghouse

The internship experience felt somewhat familiar this year for Cameron Sierra, as he returned to Westinghouse Electric Company for the second consecutive summer. After his positive experience as an eVinci Product Engineer, he was eager to build upon the skills he developed, including gaining valuable scanning electron microscopy (SEM) experience and contributing to the testing phase of Westinghouse’s nuclear-specific AI, bertha™. 

This summer, as their Materials Science and Engineering Intern, Cameron worked on projects related to improving Westinghouse's efficiency and effectiveness in materials characterization processes in order to better support their fleet of operating nuclear power plants. Using the software platform Dragonfly 3D World, Cameron was able to automate image analysis processes that were previously performed manually. Prior to beginning his internship, Cameron had never used this particular software, but he embraced the opportunity to develop a new skill set as he explored its capabilities and applied what he learned to make a meaningful contribution to the company.  

“I enjoy both learning and problem-solving, so being able to develop new skills while tackling real engineering challenges has been extremely rewarding,” he said.

While expanding his knowledge of image analysis, Python programming, software development, and deep learning, Cameron also applied his existing knowledge base, built through the coursework and lab experiences from the materials science and engineering program at Carnegie Mellon. Concepts from materials characterization courses helped him to understand and interpret microscopy images, and his programming experience gained from Materials Engineering Essentials and Engineering Statistics courses aided him in code development. Laboratory classes proved to be useful as he incorporated experimental design, technical writing, and documentation skills throughout his projects.

The analytical thinking and problem-solving developed through challenging engineering coursework have prepared me to tackle unfamiliar problems

Cameron Sierra, BS Student, Materials Science and Engineering Department

“Beyond specific technical skills, the analytical thinking and problem-solving developed through challenging engineering coursework have prepared me to tackle unfamiliar problems, learn new technologies quickly, and develop practical solutions for real engineering applications,” Cameron said. 

By developing custom code and training deep learning models, Cameron created automated workflows that reduced image analysis time from hours of manual work to just minutes. In preliminary testing, these automated workflows have accurately analyzed dozens of images in a fraction of the time previously required for manual analysis. This dramatic increase in analysis efficiency will allow engineers to evaluate substantially more materials data and extract more information from each analysis, enabling more informed engineering decisions and helping facilitate the safe and reliable operation of nuclear power plants.

As his experience came to a close, Cameron noted the progress made in both his technical skills and his confidence as an engineer and the reinforcement of the importance of combining a strong understanding of materials science with modern computational tools to solve real-world engineering problems.

“I have learned how to independently manage projects, identify opportunities for improvement, and teach myself unfamiliar technologies as new challenges arise. This experience has given me skills that I will apply in future coursework, undergraduate research, and my career as a materials engineer.”