News: Students

For many graduate students, a capstone project marks the culmination of months of learning. For one team of students in the University of Chicago’s MS in Applied Data Science (MS-ADS) program, it became something even more: peer-reviewed published research in Cancers.

The University of Chicago Data Science Institute (DSI) partnered with the Gary Comer Youth Center (GCYC), XChange Chicago, United Airlines, Girl Security, and Chicago Youth Works to launch GCYC’s Tech Pre-Apprenticeship Program – a paid, six-week experience designed to create accessible pathways into the data science field and inspire young adults to explore careers in technology.

PhD student Rodrigo Pires Ferreira, co-advised by statistics Asst. Prof. Claire Donnat, uses his talents for problem solving to discover new materials for future technologies.

G. Jake Chanenson, María Fernanda Muñoz, Anup Sathya, and Alex Wuqi Zhang were selected to the prestigious program’s Class of 2027.

UChicago chemists invent faster, cheaper technique to turn isoxazoles into pyrroles, a building block for medicines.

The Youth Internship Program, a Chicago Youth Works partner, is one of a broad suite of free academic, scientific, and creative initiatives UChicago offers Chicago high school students each summer, offering structured exposure to prospective career pathways across STEM, healthcare, and the arts, while also preparing local youth for college.

When Aaron Garay decided to return to graduate school, he wasn’t looking for an escape from his career; he was looking for a way to expand it.

This summer, 48 undergraduate and high school scholars participated in the UChicago Data Science Institute’s Summer Research Programs — the first cohort hosted in the DSI’s new home, the Lorraine and Yuji Suzuki Center.

The University of Chicago’s MS in Applied Data Science program celebrated the culminating work of its graduating students at the Summer 2026 Capstone Showcase on August 15th.

Studying the atmospheres of lava worlds offers window to Earth’s earliest history, pathway to habitable worlds.

After years of recycling and environmental consciousness, a UChicago alum turned to an old toothbrush, an engineering background, and new knowledge from UChicago’s MS in Environmental Science to create LOOP, a startup reimagining how people approach oral care.

Out of more than 6,000 participants and 800 qualifying teams representing 150 countries, University of Chicago MS in Applied Data Science students Morgan Klutzke and Binjie Wang earned first place in the Graduate Track (Master’s & PhD) of the 2026 U.S. Artificial Intelligence Institute (USAII) Global Hackathon.

In 2024, Arturo Charleston ʼ25 was at a turning point. Living in Evanston and working as a research assistant at Northwestern University, he had originally planned to pursue a PhD. The academic path appealed to his curiosity, but he longed for a way to apply his economic and technical skills more directly in the finance industry.

That search led him to the University of Chicago’s Master of Science in Financial Mathematics (MSFM) program. “I wanted to do something in which I can apply all the technical skills, working in economic finance in a more applied way in the industry,” says Arturo. “And well, UChicago is a great school for that.”

When he decided to apply to the Financial Mathematics (FinMath) program, Chicago native, Kunj Shah, was working as a financial analyst at quant trading firm DRW after graduating from college with a Finance and Psychology degree from the University of Illinois. 
He enjoyed the work he was doing, but he wanted more exposure to quantitative finance. 
For Kunj, there was no other place to learn than the University of Chicago. 

The frequency of extreme weather events can be predicted more accurately than presently possible by combining artificial intelligence (AI) with physical climate modelling, using a protocol called rare-event sampling. Researchers used the approach to model extreme heat events such as the one currently roasting Europe, but they believe it could also be applicable to many other extreme events in climate science.