Projects

Algebraic Aspects of Graphical Models
In this project we focus on using algebraic approaches to understand graphical models arising from probability and statistics. The techniques use tools from algebra and graph theory.


Assessing Wetland Composition and its Risk of Collapse
The project aims at developing methods to monitor wetland plant composition and its relationship with key chemical emissions such as methane to assess the risk of collapse of the ecosystem.

Building a Renewable Energy Portfolio in Saudi Arabia
The project aims at identifying optimal locations for building wind farms and solar panels in Saudi Arabia, using ground simulations, on site observations and new computer simulations.

This project focuses on the derivation and analysis of partitioned methods for FSI problems, where the structure is described using both elastic and poroelastic models.



The goal of the project is to develop methods for monitoring global dynamical data monitored at high temporal resolution (daily or subdaily) in order to assess the risk of floods and droughts in sensitive areas.


Hybridizable Discontinuous Galerkin Methods for Incompressible Flow and Fluidstructure Interaction
The goal of this project is to advance efficient numerical solver for incompressible flow and Fluidstructure interaction (FSI) problems can occur in many fields of engineering. (Guosheng Fu)

Neuronal Functional Connectivity Graph Estimation
One of the most important scientific challenges of the twentyfirst century is to understand how our brain processes information and produces behavior.

Numerical Algebraic Geometry and the Design of Linkages
Creating linkages which satisfy given design constraints produce largescale systems of polynomial equations. (Jonathan Hauenstein)

Many systems arising in science and engineering depend upon parameters such as temperature, pressure, and length. This research project aims to develop tools to describe the behavior of the system as a function of the parameters.

This project explores the use of circuit models of the human cardiovascular system for missing data regularization and disease detection.

The Role of Excitatoryinhibitory Balance in Neural Computation and Learning
How does learning and computation emerge from the complex interactions of interconnected neurons in the brain?

Unified Bayesian Networks for Uncertain Inputs and Partial Model Ensembles
This project proposes a framework for probabilistic reasoning integrating belief networks and deterministic computational models