University of Chicago third-year students Arthur Costa, Shelley Fernando, Mason McCormack and Vincent Wang have been selected as winners of the 2026 Barry Goldwater Scholarship. The four undergraduates are among more than 450 winners selected this year for the award, which aims to help STEM students further their research during the last years of their bachelor’s studies.
The Goldwater Scholarship was created by Congress in 1986 and recognizes undergraduates who intend to pursue research careers in natural science, mathematics and engineering. The prestigious award helps winners cover the cost of tuition, room and board, fees and books up to $7,500.
We spoke with each of the winners about their research and what receiving the honor means to them:
Arthur Costa
Arthur Costa is a chemistry major who wants to know how different scientific disciplines can be combined to solve real-world problems.
“I’ve always been interested in the interface between chemistry and biology,” he said. “Specifically, I’ve been trying to see how we can use chemistry to understand and manipulate biological systems.”
This idea has led him to focus on how we can use this way of thinking to solve problems in the medical field. At UChicago, Costa has worked with doctors, epidemiologists and biologists, and as part of a team in the Genehackers organization to create tools that can be used towards improving global disease detection and treatment.
Tell us about your research.
Most of my work has been in Nobel laureate Prof. Jack Szostak’s lab, which aims to understand how life may have started on Earth in the early days by creating model protocells with materials that could plausibly have been present. The opportunity to work with him has been a tremendous learning experience that has taught me how to think as a scientist.
My research uses small molecules to increase membrane permeability to load nucleotides into protocells and trap them inside. Using this system to load nucleotides increases internal RNA copying yields nearly 10-fold and solves a major problem in origins-of-life research by showing how nucleotides could have entered and accumulated inside those early protocells.
Shelley Fernando
For Shelley Fernando, it all started in the Advanced Biology sequence as a first-year student.
For a final assignment, each student was tasked with choosing a scientific paper and writing a review about it. She decided to write hers on an unpublished preprint covering the mechanisms of DNA-loop extruding proteins and the rest was history.
“I got super excited about these loop extruders and did a deep dive on the subject.”
That curiosity eventually led her to declare a major in biological chemistry and research assistant roles in three different laboratories, all of which study genome architecture and loop extrusion at different levels of abstraction. As she works toward a long-term goal of earning a Ph.D. in molecular biology or biochemistry, Fernando said she hopes for more opportunities to meet scientists and talk about exciting science.
Tell us about your research.
I’m interested in the spatial organization of the genome of the nucleus and the dynamic regulation of the 3D genome architecture. Nearly all the cells in our body have the same genome—genetic information in the cell that is packed in the form of chromatin that can be marked and organized in ways that control which genes are expressed in which cells.
My work at UChicago focuses on the changes in chromatin organization that drive the development of B cells. I hope to use the skills that I am learning here to pursue a PhD project that uses ex vivo microscopy and computational modelling to understand the interplay between loop extrusion and epigenetic state.
Mason McCormack
Space has always pushed the boundaries of human knowledge. The drive to answer these seemingly impossible questions fostered Mason McCormack’s interest in studying distant alien worlds.
“Using cutting-edge technology and pushing the boundaries of what we think we can measure really drew me towards this field,” McCormack, an astrophysics major, said. “The study of space is really a testament to human ingenuity in how much data you can get out of shockingly little information.”
McCormack, the president of the UChicago Space Program, has been an engineering lead of the Polarization modUlated Laser Satellite Experiment (PULSE-A) for the last two years. He also conceived of and secured funding and a NASA grant for the Particle Acquisition from Stratospheric Conditions for Analysis in Laboratory (PASCAL) science balloon experiment and attended international conferences.
McCormack said doing all this at a school without an engineering program was made possible by “the drive and support of my fellow classmates and every professor that has generously given us their time and wisdom.”
Tell us about your research.
My primary research is on exoplanets. Using the James Webb Space Telescope, we are trying to understand what the atmospheres are like on some of the biggest planets we’ve discovered. I run hundreds of atmospheric models based on some planetary and stellar parameters we can observe and a couple of molecules to see if we can deduce the composition of these “hot Jupiters.”
The goal of this research is to find a link between how these planets are formed and their compositions. We know that they couldn’t have been born where they are because they are too close to their stars. The fact that they couldn’t be born where they are currently located opens up the question of how they migrated there from their point of origin. Trying to figure out billions of years of history from a few data points is such a uniquely fascinating problem to be working on.
Vincent Wang
Machine learning is still in its infancy, which is what Vincent Wang finds so fascinating about it. For a technology that has become a household name seemingly overnight, there is much that we still don’t know about it.
“I think a very compelling part of machine learning is that it is a field that has many interesting empirical phenomena that we don’t quite understand,” Wang said.
As a double major in mathematics and computer science, he hopes to use mathematics to better understand why machine learning has improved so much over the past decade in order to make it safer and more rigorous.
Tell us about your research.
I’m broadly interested in finding new ways to understand machine learning theory through mathematics. I’m currently working with Research Asst. Prof. Mahdi Haghifam at the Toyota Technological Institute at Chicago (TTIC) on understanding the optimization of algorithms that satisfy differential privacy, which is a mathematically rigorous guarantee that an algorithm does not leak the data it trains over. In the past, I’ve worked on other projects in combinatorics, tropical geometry and numerical methods for solving partial differential equations.
UChicago and TTIC really shaped how I think about machine learning by describing the field through a consistent theory. It gave me an appreciation of how deep the field runs today.
Each of this year’s Goldwater Scholars was supported by the Office of National Fellowships in the College Center for Research and Fellowships, which guides candidates through rigorous application processes and interview preparation for nationally competitive awards like Goldwater. The Center’s team helps students identify and articulate how their unique talents and distinctive paths prepare them to realize a better world.
—A version of this story was originally posted by The College.
