Cusumano Family Doctoral Fellows in Analytics

The Cusumano Family Doctoral Fellowship in Analytics was established in 2024, thanks to a generous gift from Dino M. Cusumano ’96. The Fellowship supports PhD students in Analytics, known as Cusumano Family Fellows, with tuition, stipends and benefits, research support, travel to conferences and networking opportunities.

Current Cusumano Family Fellows

Sofía Calderón, received a BS in Political Science and a BA in Public Administration from Benemérita Universidad Autónoma de Puebla in Mexico. She attained an MA in Economics from USC, and an MIA in International Economic Development from UCSD. Sofía was a research manager in the U.S. Good Business Lab Foundation at the University of Michigan. Sofía is researching how human-robot interventions can be robustly designed and measured to improve instrumental and humanistic outcomes in workforce and healthcare contexts. She is a first year student working with Profs. Ahmed Abbasi and Ken Kelley.

Ryan Cook received a BS in Analytics with a minor in Philosophy from Notre Dame, and an MS in Computer Science from the University of Pennsylvania. He worked as a research scientist in Notre Dame’s Human-centered Analytics Lab and Center for Computer Assisted Synthesis, supporting projects related to NLP and network analysis. Ryan was also previously an analyst at EY in Chicago. At Notre Dame, Ryan is researching how to better explain or predict team outcomes using machine learning tools such as relational event modeling and graph neural networks. He is a 3rd year student working with Profs. Nick Berente and Ahmed Abbasi.

Alyona Nefedova majored in Math at the Higher School of Economics. Her thesis examined classification and discovery of R-matrices. She received the Governor’s medal for academic excellence. Alyona explored trading models at the Center for Mathematical Finance, and assisted with cognitive science projects at the fMRI Lab. She previously taught middle school math and volunteers at Canada/USA Mathcamp. Alyona is a second year student working with Profs. Ken Kelley and Nick Berente.

Kezia Oketch attained a BS in Computer Science from Spelman College and an MS in Engineering, Science, and Technology Entrepreneurship from Notre Dame. She was a Gold Scholar at the Grace Hopper Conference and co-founded a research startup focused on technology-based solutions to the cancer crisis in Kenya. Kezia was also a software engineer at an Ohio-based tech company. Her current research explores fairness of AI systems in healthcare settings. She is a third year student working with Profs. Ahmed Abbasi and John Lalor.

Sunan Qian double majored in Economics and Math, and minored in French, at Mount Holyoke College. She received an MS in Finance with a minor in Quantitative Methods from Carnegie Mellon University – her thesis explored the impact of environmental regulation on firms’ carbon emissions and market value. Sunan was a digital consultant for Accenture in Tokyo. At Notre Dame, her research examines the contagion effects of in-game toxicity as well as machine learning methods for detection and mitigation. She is a third year student working with Profs. Corey Angst and Yoonseock Son.

Will Stamey was a double major in Economics and Math at Baylor University, with a minor in Philosophy. He was a Baylor Fellow and Crane Scholar, and completed the health economics sequence. Will’s honors thesis explored the impact of online education on academic outcomes. He was also a researcher at the Colorado Summer Institute in Biostatistics. At Notre Dame, he studies how sub-group level treatment effects can be efficiently and rigorously extracted from multi-dimensional longitudinal observational data. He is a fourth year student working with Prof. Ken Kelley.

Suzie Xi received her BA degrees in Computer Science and Art History from Smith College, and an MS in Computer Science from the Courant Institute at NYU. She worked for two years as a quantitative management associate at Bank of America. Suzie’s research interests relate to machine learning, large language models, and causal inference. She is a first year student working with Prof. Heng Xu.

Xinyuan Zhang completed her undergraduate coursework from the University of Sydney, where she double majored in Finance and Statistics and researched sentiment analysis in the Computing Finance Lab. Xinyuan received an MS in Statistics from UCLA – her thesis explored preference models for two-sided platforms. She was also a researcher in the Trusted AI Systems Lab at Nankai University. At Notre Dame, she studies human-centered computational design for how high-dimensional user digital trace data for better prediction and explanation of individual behaviors and outcomes. She is a fourth year student working with Profs. Ahmed Abbasi and Jeff Cai.