Congratulations to College of Engineering students who have recently earned prestigious honors:
Caleb Kowalski, a sophomore in mechanical and materials engineering, was one of four University of Nebraska-Lincoln students chosen to be part of the inaugural class of Innovation Fellows.
Kowalski and the other Innovation Fellows – Alison Cloet, a junior in fashion design; Dana Hoppe, a sophomore in computer science and art; and Mickey Tran, a sophomore in computer science – were introduced by Chancellor Ronnie Green on Feb. 12 during a celebration at Nebraska Innovation Studio.
As fellows, the undergraduates will build their portfolios and resumes while also impacting children across the state by working on a design team with leading educational professionals from Beyond School Bells. As a team they’ll develop Think, Make, Create Labs – mobile trailers used for expanded learning opportunities – that encourage problem-solving, creativity and exploration in a hands-on learning environment. The fellowship runs through December, and the fellows earn a $5,000 stipend.
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Jenny Wynn, a junior in agricultural engineering, is part of a four-student team that won the Start Something 48-Hour Challenge, hosted by the Center for Entrepreneurship and the College of Business.
The event featured more than 50 students working over a weekend – Jan. 26-28 – to develop business ideas, pitch the ideas and voting on the best ideas. After voting eliminated all but eight ideas, teams organically formed and the new teams began fleshing out ideas, including creating prototypes, talking with potential clients and doing market research. The competition concluded Sunday night with presentations in front of a panel of judges, who chose the winner.
Wynn’s team – which also included Trevor Fellbaum, a sophomore in computer science; Joshua Jones, a junior in economics and computer science; and Jonathan Pynes, an undeclared junior – was selected as the winner for developing novocAI, which is an artificial intelligence-assisted cancer diagnostic software. The proposed software would use an image classification system from a database of thousands of images to identify the type of cancer and diagnose patients more quickly and accurately than standard methods currently in use.