Dominic Sicilian's path to becoming an applied artificial intelligence and machine learning data scientist at the largest bank in the U.S. began as a fascination with the universe.
As an undergraduate at the University of Miami, where he also briefly played on the football team, Sicilian was drawn to the philosophy of the universe and questions about the nature of existence.
"That is how I realized that I wanted to do physics, and especially astronomy, and I never looked back," he said.
Sicilian double majored in physics and philosophy and went on to complete a master's degree and Ph.D. in physics at the College of Arts and Sciences. As a graduate student, he focused on astrophysics, researching dark matter and black holes using AI applications such as machine learning to analyze big data sets. To study obscured supermassive black holes, for example, which are difficult to observe because they are shrouded by dust and gas, Sicilian analyzed massive data sets from NASA's Chandra X-ray Observatory, developing machine learning models to enhance redshift measurements—a cosmological measurement of the distance to these black holes.
"That really got me into data and machine learning, and then that led to AI," Sicilian said. "It was a whole new side of science for me, the side of science that is covered by the umbrella of AI, which includes machine learning and these large language models that we have today. I saw that as a new and exciting challenge—a new type of science to pursue."
After he finished his Ph.D. in 2022, Sicilian worked as a data scientist at Roc360, a financial services company. Then, earlier this year, he was hired as an applied AI and machine learning data scientist at JPMorgan Chase. In this role, Sicilian is focused on using AI applications such as machine learning to make traditional investment banking methods faster and more efficient, as well as employing this cutting-edge technology to generate new insights.
"Getting to work at one of the biggest banks in the world and getting to experience a whole new application of my data methods and tools has been fascinating and super exciting for me," he said.
In recent years, JPMorgan Chase has incorporated AI into various aspects of its business, including using generative AI in call centers. Sicilian is part of a team that is housed in the investment bank and builds custom AI products specifically for that part of JPMorgan Chase's business.
Although he is no longer working in astrophysics, Sicilian continues to follow developments in the field. Over the past few years, he has co-authored astrophysics papers and served on a NASA proposal review panel.
While he still uses some of the same AI tools he employed as an astrophysics graduate student, the world of banking is far removed from the physics classrooms and laboratories where Sicilian spent much of his time at the University. He said he has found diving into a new field both challenging and rewarding.
"The biggest challenge is stepping far beyond my old sense of familiarity with astronomy and space and stepping into the financial world," he said. "That is also the most exciting part. I love a good challenge."
