The Data Science program emerged from the critical need for employees across industries equipped with the skillset to analyze big data sets. The program is interdisciplinary between Computer Science, Economics, Mathematics, and Statistics. Students majoring in Data Science gain a strong foundation in these areas of study while also taking dedicated data science classes. Equipping them with the skills needed to enter directly into the workforce or continue their studies through graduate education. Faculty from all four departments are pursuing data driven research that includes creating human-centered neural networks, tracking global news to predict government stability, and forecasting future economic trends.
Meet Faculty from the Collaborating Departments
Nate Blanchard, assistant professor, Department of Computer Science
Dr. Blanchard’s research focuses on training neural networks to behave with biological consistency, specifically focusing on replicating the perceptive behavior of the human brain as measured by fMRI and EEG recordings.
Sammy Zahran, professor, Department of Economics
Dr. Zahran’s research focuses on understanding the health and human capital effects of pollutant exposure, utilizing various econometric tools that allow one to study cause and effect relationships in observational data.
Emily King, assistant professor, Department of Mathematics
Dr. King’s research involves decomposing data or neural networks into basic building blocks to better understand their features (data) and how they work (neural networks).
Andee Kaplan, assistant professor, Department of Statistics
Dr. Kaplan uses a Bayesian statistics framework to clean up noisy data sets by joining or finding duplicates from multiple data sources.