Graduating this spring with an MS in Computer Sciences, Andrew Gross pivoted from math and economics because of his interest in development and implementation.
“After working in economic research for four years, I realized I was more interested in the development and implementation of models rather than the economic theory behind them. This intersected with the rise of machine learning and AI, so to pivot to computer sciences I thought it best to formalize my understanding of its foundations by pursuing a master’s,” says Gross.
Originally from Delaware, Gross worked as a research assistant prior to attending graduate school studying academic fairness as it pertains to consumer lending decisions. He hopes to continue this work in some capacity after graduation.
“Lending institutions are adopting increasingly more complex machine learning models to determine a candidate’s ability to pay off a loan. But with added complexity comes less model interpretability. This is important in an industry like financial technology where loan eligibility should only be based on financial history, not personal characteristics like race,” says Gross.
With the knowledge he gained during his program, he hopes to continue this work in some capacity after graduation.
“As part of our research, we had to develop our own models to test against since we don’t have access to lending institutions’ internal models. The master’s program gave me the foundation to understand these models and build my own,” says Gross.
Gross chose the UW-Madison Computer Sciences program because of the program’s reputation and its flexibility.
“The reputation of UW-Madison’s Computer Sciences department was enough of a draw. But on top of that, the design of the program is exactly what I was looking for. We were able to tailor the curriculum to our interests so I could focus solely on courses in machine learning, optimization, and statistics,” says Gross.
One of Gross’s favorite parts of his time at UW-Madison was learning from Rob Nowak. Nowak is the Grace Wahba Professor of Data Science and Keith and Jane Nosbusch Professor in Electrical and Computer Engineering.
“CS 761 (Mathematical Foundations of Machine Learning) was one of the best courses I’ve ever taken because his lectures were so well organized and delivered. He was able to take esoteric topics and make them both interesting and extremely accessible,” says Gross.
Gross says he also loved seeing Bucky out and about on campus, even if there weren’t any events happening.
After he graduates, Gross is moving to New York for a software engineering job at Capital One.