Research Cluster
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.
Key Research Focus: Our research 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.
Gustavo Didier
Primary
Professor Didier's research spans stochastic processes, high-dimensional probability, and the mathematical foundations of machine learning.
Emily Gamundi
Secondary
Professor Gamundi's teaching focuses on statistics and mathematics for data analysis, particularly at the intersection of mathematics and social sciences.
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.
Xiang Ji
Primary
Professor Ji is a statistician specializing in phylogenetics, from model development to implementing parallel computing libraries for bioinformatics and cancer biology.
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.
Scott McKinley
Primary
Professor McKinley studies stochastic processes and their applications to characterizing movement in biological systems, from intracellular transport to movement ecology.
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.
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.
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).
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.
