A good scientist follows the data, even if it leads in a surprising direction. 

Thanks to that mindset, Christian Geils experimented with unexpected research opportunities at the University of South Carolina and produced work that connects artificial intelligence, biology, chemistry and more. 

This weekend, Geils will become the first graduate of the University of South Carolina's new data science major. 

Originally from Charleston, South Carolina, Geils came to USC for its Honors College and good pre-med program. 

“I knew there was a lot of variety in terms of what I could study and research opportunities,” he said. 

Initially he chose a biology major, and in his sophomore year he started research for his honors thesis. Professors Katie Kathrein and Hexin Chen mentored him in conducting data analysis related to cancer biology and immunology. That experience introduced him to writing computer code to crunch data. 

“The part that I really enjoyed the most was getting to work with clinical data and working on programming problems,” he said. “That drew me to AI, which was getting big at the time.” 

The summer before his junior year, Geils emailed several professors who did research with AI. He joined in their research and ultimately become one of the first students to sign up for the new data science major, a partnership between the McCausland College of Arts and Sciences and the Molinaroli College of Engineering and Computing. 

His work became increasingly interdisciplinary. While completing his honors thesis, he taught himself more programming and machine learning skills. He helped computer science professor Forest Agostinelli on a project using AI to plan the complex pathways of creating new chemical products.

Then Geils received a Magellan grant from USC to pursue an independent idea. He read about an approach that makes AI more explainable ― meaning its process is easier for humans to understand and trust ― and he wanted to test how this setup could help chemists predict the properties of a new synthetic material. He explored the algorithm’s power to predict how easily the new material would dissolve, how stable it would be and how it might react with other substances. 

“These are all useful things to know if you’re trying to design a drug or a material,” Geils said. 

Chemistry professors Christopher Sutton, Sophya Garashchuk and Vitaly Rassolov mentored him on that project. “They helped me connect my research to the existing body of work,” he said. “That really helps me frame my problem to show how it affects computational chemistry moving forward.” 

Although his research accomplishments are impressive, Geils said he is most proud of his work to start the Gamecock Artificial Intelligence and Machine Learning Association, the first AI club at USC. 

As graduation approaches, he is exploring job opportunities and considering graduate study in statistics or computational chemistry in the future. His advice to future USC students is to be open-minded and get involved on campus. 

“Try new things, explore your interests, and get involved in as many research and extracurricular activities as you can," he said. "USC is a big enough school that you can use its resources and opportunities to pivot your career or future education into whatever direction you like.”