Probability and Statistics
The Probability and Statistics cluster at Tulane focuses on the theory and application of stochastic processes and advanced statistical methods. Our research addresses the growing need for sophisticated mathematical and computational tools to model uncertainty and analyze complex, high-dimensional data.
Faculty in this group work at the forefront of contemporary applied mathematics, with research in areas such as stochastic analysis, random matrix theory, time series analysis, and statistical inference. This work provides the theoretical foundations for understanding randomness, with direct applications in fields ranging from finance and physics to neuroscience, phylogenetics, and the mathematical foundations of machine learning.
Affiliated Faculty
Our faculty's expertise in probability and statistics drives innovation in data-intensive fields. Explore their profiles to learn more.
Daniel Irving Bernstein (Secondary)
Professor Bernstein's research in applied algebraic geometry, algebraic statistics, and phylogenetics connects pure mathematics with modern data science applications. View Profile »
Gustavo Didier (Primary)
Professor Didier's research spans stochastic processes, high-dimensional probability, and the mathematical foundations of machine learning. View Profile »
Emily Gamundi (Secondary)
Professor Gamundi's teaching focuses on statistics and mathematics for data analysis, particularly at the intersection of mathematics and social sciences. View Profile »
Lifeng Han (Secondary)
Professor Han applies statistical and modeling techniques to understand temporal and spatial dynamics arising from time delay and stochasticity in cancer biology. View Profile »
Xiang Ji (Primary)
Professor Ji is a statistician specializing in phylogenetics, from model development to implementing parallel computing libraries for bioinformatics and cancer biology. View Profile »
Michelle Lacey (Primary)
Professor Lacey's research is rooted in developing and applying statistical methods to biological data, with a primary focus on statistical genetics and epigenetics. View Profile »
Scott McKinley (Primary)
Professor McKinley studies stochastic processes and their applications to characterizing movement in biological systems, from intracellular transport to movement ecology. View Profile »
Kenneth McLaughlin (Primary)
Professor McLaughlin's research in random matrix theory and integrable systems provides a theoretical foundation for modern data science and high-dimensional statistics. View Profile »
Samuel Punshon-Smith (Primary)
Professor Punshon-Smith's research involves stochastic analysis and random dynamical systems applied to the study of chaos and turbulence in fluid mechanics. View Profile »
Norbert Riedel (Secondary)
Professor Riedel's recent research has focused on statistical learning theory, particularly addressing the "small sample size" problem in Linear Discriminant Analysis (LDA). View Profile »
Seminars & Activities
- Faculty and students in this cluster are active participants in the department's weekly Probability and Statistics Seminar.
- Explore all faculty profiles in the Mathematics Department Directory.
