Eugene Pinsky

Eugene PinskyAssociate Professor of the Practice, Computer Science; Coordinator, Software Development

PhD, Columbia University
BA, Harvard University


Dr. Eugene Pinsky first joined the faculty of Boston University in 1986, after earning his doctorate at Columbia University. He was an assistant professor of computer science in the College of Arts & Sciences until 1993, when he left BU and gained extensive industry experience designing computational methods to analyze and monitor market risk at multiple trading and investment firms, including Bright Trading, F-Squared Investments, and Harvard Management Company. He has also applied his expertise in data mining, predictive analytics, and machine learning to video advertising at Tremor Video. Dr. Pinsky’s areas of expertise include pattern recognition, clustering, regression, prediction, factor models, support vector machines, and other machine learning algorithms and methods for data analysis; multi-dimensional statistical data analysis of large time-series data; data mining and predictive analytics to uncover patterns, correlations, and trends; algorithmic trading, pricing models, financial modeling, risk, and portfolio analysis; Python, R, C/C++, VBA, Weka, MATLAB, and MySQL; Big Data technologies and visualization (Hadoop/Hive, AWS, Tableau); design and implementation of software tools for quantitative analysis; and professional curriculum and course development.

What advice do you have for new students?

Data science and machine learning require an understanding of many interdisciplinary concepts, based on classical results from mathematics and statistics. I would encourage students to study these fundamental sciences and look for solutions that are simple and amenable to intuitive interpretations. As data scientists, you should have an open mind. Negative results are just as important as positive results.”