Summer Research: Nolan Eichorn '26 trains machine learning models
Eichorn, a mathematics major, is participating in the National Science Foundation Research Experience (REU) program at the University of Florida.
Thursday, June 26th, 2025, 11:24am
Nolan Aichon '26
Over 70 Muhlenberg students are conducting the survey this summer. About 60 people on campus, about 10 more, and only a handful of others through other institutions.
Research challenges students to apply what they learn in the classroom, hone their discipline-specific skills and influence their field. Learn more about Muhlenberg's Transforming Summer Research Program.
Nolan Aichon '26
Hometown: Warminster, Pennsylvania
Selected subjects: Mathematics (teacher)
Describe your summer research.
I am changing my machine learning model to test the evolutionary hypothesis of butterflies. Artificial intelligence can be used to analyze butterfly images obtained from the Natural History Museum and use these photos to train your models. After training, test the model to see how well you can predict the species and subspecies of butterfly images you've never seen before. This allows us to change data that previously only qualified as quantifiable data that would help biologists classify butterflies more accurately.
Why are you interested in research in general and in this project, especially through the University of Florida?
This research will allow you to learn how artificial intelligence works and how to build and train machine learning models. I took part in this study in hopes of applying these models in a broader context and learning how to use machine learning in other fields. From number theory to disease control and material science, I applied for a wide range of REU programs this summer. When I was accepted into the University of Florida program, I was with EC! It was one of the only programs I had little experience with, but it was something I was very hoping to get in, so I had the opportunity to learn new things that I really were interested in.
“When I was accepted into the University of Florida program, I was with ec! It was one of the only programs I had little experience with, but it was something I was very hoping to have the opportunity to learn new things that I really were interested in.”
What is the most challenging and rewarding part of your research?
The most difficult part of my research is to fully understand the code behind AI. I often get unexpected errors and results, so I can parse my code to find out what's wrong, but it can often be challenging and frustrating. However, the satisfaction level achieved after correcting the error or getting the expected output is extremely rewarding. Learning how these models are built is very difficult due to their complexity, but it's a good feeling to add new parts and push the models to allow them to train and learn more efficiently.
How does this experience shape your understanding of what you want to do in the future?
I aim to go to dental school after graduation, and I would like to use this experience as a stepping stone to do similar research in dental schools. Research like myself is being done in the mandibular bone, and I think machine learning can be used in a larger context in the future, both in patients and doctors. AI is the future of our world, and understanding it and applying it to medicine may be beneficial for me. I hope this can be used in dental schools and beyond.
“AI is the future of our world, and understanding it and applying it to medicine may be beneficial for me. I hope this can be used in dental schools and beyond.”
Eichon is the president of Alphaipsilon PI Fraternity and former president of In-Wall Soccer and Zastental Club. He has done his research at Muhlenberg in Mathematics and Chemistry.
