Interns Explore Use Cases for AI, Other Emerging TechnologiesCompany NewsBy Tria Federal

A successful intern program benefits both students and the company they intern for. By those standards, Tria Federal’s summer intern program, wrapping up this month, was a rousing success.

Our five college interns were sponges for knowledge, gaining in-depth exposure to government contracting and contributing to real-world projects for our chief technology officer and our advisory business unit.

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Five young adults standing on a rooftop with a cityscape and cloudy sky in the background.

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The interns’ research advanced Tria’s work in generative artificial intelligence (AI) and robotic process automation (RPA), and they worked side-by-side with our staff to contribute to customer projects.

They took on much of the learning and training themselves, with support from Tria colleagues. They participated in intern seminars and expanded their professional networks. And they had fun too, helping to take Tria’s beach volleyball team to a league championship.

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Three young men in navy shirts standing on grass near beach volleyball courts, one holding a yellow and black Wilson volleyball.

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The sign of a strong internship experience is getting to “not just theoretically learn something but apply it,” Tria CEO Tim Borchert told the interns during their final presentations.

“You were able to learn some new skills, you were able to learn some new technology, and most importantly you can see how it gets put into place at a company like ours,” Borchert said. “Each of you were tasked with a lot of different challenges, and you rose to the occasion.”

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Here is some of what our summer 2024 interns worked on:

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Exploring how machine learning models can help prevent fraud, waste and abuse. Their work provides a foundation for Tria to develop a deep learning algorithm that analyzes incoming data, identifies patterns, and flags deviations from normal patterns.

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Updating and refining Tria’s corporate generative AI policy to align with the company’s leadership in promoting responsible use of this emerging technology.

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Investigating possible uses of generative AI for education and training in government contracting, including personalized learning, real-time feedback and gamification.

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Using real-world data to create a code to generate a risk score indicating who should be tested for diabetes. Their work supports the development of a predictive health model that could identify and predict possible health problems given people’s medical history and lifestyle factors.

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