Pavel Oleinikov uses his background in social and natural sciences to advance the application of quantitative methods to data from the social world. He teaches courses on basics of Big Data, network analysis, text mining, and skills-focused courses. A large part of his work lies in assisting Wesleyan faculty in integrating diverse data sources in the form of text, images, and data from APIs.

Pavel Oleinikov has a PhD in Political Science from University of California, Santa Barbara.  His dissertation focused on paradigms of impatience and their quantitative investigation.  For his MS thesis in computer engineering he studied applications of Hopfield-type neural networks to optimization tasks.