This area focuses on the development of computational methods in solving physical problems with varying spatial and temporal scales ranging from Particle Physics to the study of substances in their solid-state known as Computational Condensed Matter, to living systems and models of Self Organization, to the modeling of the physical change at the urban scale through the lens of Complexity Science all the way up to the Astrophysical scale modeling increasingly resolved observations of astronomical objects, phenomena, and associated processes.
For Earth Sciences, the research focuses on hydrogeology and the applications of AI and machine learning techniques in the fields of meteorology, agriculture, water and food security. It is also concerned with the application of machine learning in Smart Cities as well as the Oil and Gas Industry.
Below is a list of selected faculty members who conduct research relevant to this area.
Fatima Abu Salem
Advanced machine learning techniques for smart irrigation.
Remote sensing in Agriculture, Water, and Food Security.
Microfluidics & MEMS, Atmospheric & Ocean Modeling, Pollution Transport, Vortex Methods.
Computational astrophysics and dynamical systems.
Use of Machine Learning in the Oil and Gas Industry.
Computational models of soft matter and self-organization.
Generalised hydrodynamics, reaction-diffusion, stochastic differential equations.
Computational condensed matter.
Advanced statistical modelling techniques for smart irrigation.
Computational physics and complexity science applied to urban and biological systems.