Ruth's research interests are in the areas of Data Assimilation and Stochastic inference. Currently, she is working on the Bayesian approach for static on-line parameters estimation in state-space models as a filtering problem.

Marcus's research interests are in Computational Algebra. Currently, he is studying linear recurrence operators and determining criterion which guaruntees the existence of their global p-curvatures.

Townsend is interested in learning Algebraic Geometry

With a background in physics and computer science, Alaina's research interests include mathematical modeling and visualizing of astrophysical systems on high-performance computers. She is currently looking into performance improvements in 3-D Supernovae simulations.

Heba is interested in Computer Algebra and Difference Algebra. Currently, she is working on defining and computing a generalization of Liouvillian solutions that correspond to higher order factors.

Audrey is currently working in an interdisciplinary research team applying data science tools to neural datasets to gain insight into how taste is processed in mouse brains, aiming to improve our understanding of the neural coding scheme by incorporating the context of active stimulus sensation. She is also interested in machine learning and mathematical modeling of biological systems.

Rafiq has interests in financial mathematics, machine learning and optimization. He is currently working on stochastic algorithms in optimization and sampling.

Jonathan's research interests include mathematical modeling in physics, finite element methods, numerical linear algebra, and neural networks. Currently, he is studying the Navier Stokes Equations for modeling fluid dynamics at supersonic speed.

Ferhat is interested in topology and its applications in data science. His current project involves algebraic topology.

Pervez is working on Generative AI (application in finance) using diffusion models to calculate Value at Risk (VaR) and Expected Shortfall (ES). By simulating future market scenarios, the aim is to improve risk assessment and management strategies in financial institutions.

Navid focuses on applying high-dimensional data analysis in finance and machine learning, exploring techniques that leverage empirical and simulated data. His work involves investigating optimization, covariance estimation, and the use of advanced statistical methods, with the goal of solving complex financial problems and enhancing machine learning model.

Jonathan's research interests include Game Theory, Dynamical Systems, Social Dynamics and Social Coordination