Lisa Dilks

Professor of Practice


Lisa Dilks


Dr. Lisa Dilks is one of the inaugural Professors of Practice at the Connolly Alexander Institute for Data Science. She will aid the institute’s mission to engage, support, and assist in the development of undergraduate students’ data literacy and data analytic skills. Dilks has been teaching data analysis at the undergraduate and graduate levels for 15 years. She envisions not only exposing students to the fundamentals of data science and literacy in her introductory course (DATA 1010), but also through her development of advanced courses in statistical analysis, data management, programming for data science, techniques in machine learning, and experimental design and analysis.

In her role as a Professor of Practice in Data, Dilks is excited by the opportunity to increase data literacy and analysis skills among the undergraduate students, better preparing them to become part of the data science workforce. Her pedagogy emphasizes the importance of developing computational and analytical skills within relatable contexts using a team-based and interdisciplinary approach. Students of any major will develop the analytical and decision-making skills to solve problems using a data-driven approach. In addition, Dilks looks forward to assisting Tulane University in continuing to impact the local New Orleans community. She sees both outreach activities and service-learning courses as opportunities to utilize data to serve the social good.

Dilks is a structural social psychologist and former Associate Professor of Sociology whose research focuses on the impact of external social factors on individuals’ behaviors and interactions with others, in particular the social inequalities they create. Her research is primarily quantitative and can be categorized into two interrelated areas: 1) the creation of and remedies to social inequalities resulting from status differences among individuals, with 2) a specific focus on gender inequalities at both the individual and institutional levels. Dilks’s recent projects utilize both status and gender theories from structural social psychology to explore their application to criminological phenomena, including punishments and arrest likelihoods for both street crime and white-collar crime; the formation of romantic partnerships; and leveraging group level interventions to improve institutional quality, climate, and inclusivity. Her research has been funded by the National Science Foundation. Current research utilizes big data and systems level analytic techniques to understand how micro level interactions lead to inequitable social, political, and economic structures. These projects emphasize a data-driven approach to better leverage models of dynamical and coupled systems to understand social systems.

Dilks received her Bachelor of Arts degree in Women’s Studies and Sociology and Master of Arts in Sociology from the University of Wyoming, before receiving a Master of Applied Statistics and Ph.D. in Sociology from the University of South Carolina.