Artificial intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of humans or animals. It is also the field of study in computer science that develops and studies intelligent machines. "AI" may also refer to the machines themselves. [Wikipedia]

Atmospheric dynamics deals with motion in the atmosphere and its thermodynamic state. Our research on this subject aims to improve the mathematical equations, numerical methods, and the dynamical core of the forecast model, as well as technical aspects such as implementation on high-performance computers. [Wikipedia]

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Scientific Computing Colloquium
Wednesdays at 3:30 P.M. following Afternoon Tea
499 Dirac Science Library

Compressed sensing (also known as compressive sensing, compressive sampling, or sparse sampling) is a signal processing technique for efficiently acquiring and reconstructing a signal, by finding solutions to underdetermined linear systems. [Compressed sensing From Wikipedia]

Computational epidemiology is a multidisciplinary field that uses techniques from computer science, mathematics, geographic information science and public health to better understand issues central to epidemiology such as the spread of diseases or the effectiveness of a public health intervention. [Computational Epidemiology From Wikipedia]

Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data,[1] including both DNA and RNA sequence as well as other "post-genomic" data (i.e., experimental data obtained with technologies that require the genome sequence, such as genomic DNA microarrays). [Computational Genomics From Wikipedia]

Computational linguistics:

quantitative analyses of language.

Data assimilation is a mathematical discipline that seeks to optimally combine theory (usually in the form of a numerical model) with observations. There may be a number of different goals sought – for example, to determine the optimal state estimate of a system, to determine initial conditions for a numerical forecast model, to interpolate sparse observation data using (e.g. physical) knowledge of the system being observed, to set numerical parameters based on training a model from observed data. Depending on the goal, different solution methods may be used. Data assimilation is distinguished from other forms of machine learning, image analysis, and statistical methods in that it utilizes a dynamical model of the system being analyzed. [Wikipedia]

Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. [Deep learning From Wikipedia]

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Harmonic analysis is a branch of mathematics concerned with the representation of functions or signals as the superposition of basic waves, and the study of and generalization of the notions of Fourier series and Fourier transforms (i.e. an extended form of Fourier analysis). In the past two centuries, it has become a vast subject with applications in areas as diverse as number theory, representation theory, signal processing, quantum mechanics, tidal analysis and neuroscience. [Harmonic analysis From Wikipedia]

Design and use of parallel algorithms and large-scale computing architectures (clusters, GPUs, supercomputers) to solve computationally intensive problems beyond the reach of standard hardware.

Human-AI interaction:

AI-associated language change, societal impact of language technology.

An inverse problem in science is the process of calculating from a set of observations the causal factors that produced them: for example, calculating an image in X-ray computed tomography, source reconstruction in acoustics, or calculating the density of the Earth from measurements of its gravity field. It is called an inverse problem because it starts with the effects and then calculates the causes. It is the inverse of a forward problem, which starts with the causes and then calculates the effects. [Inverse problem From Wikipedia]

Large language models:

model language behaviour, alignment and post-training, learning from human feedback, and automated model diagnostics.

Research in the Computational Intelligence Laboratory addresses different aspects of networks in the human brain and in artificial systems.

Computational Intelligence Laboratory

Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. [Mathematical optimization From Wikipedia]

The field of morphometrics is concerned with the analysis of shape and form (shape+size). Shape is defined as the set of geometric properties of an object that are invariant to position, orientation, and scale (1). Often scale is sequestered in a separate variable and reincorporated into an analysis to examine the totality of variation in a population of specimens of interest or associations of shape variability with size (allometry).

Numerical analysis is the study of algorithms that use numerical approximation (as opposed to symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics). [Numerical Analysis From Wikipedia]

Numerical weather prediction (NWP) uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. Though first attempted in the 1920s, it was not until the advent of computer simulation in the 1950s that numerical weather predictions produced realistic results. A number of global and regional forecast models are run in different countries worldwide, using current weather observations relayed from radiosondes, weather satellites and other observing systems as inputs. [Wikipedia]

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Computational science involves the invention, implementation, testing, and application of algorithms and software used to solve large-scale scientific and engineering problems.

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The following software categories are supported by the department's technical support group. Support for any additional applications needs to be approved by the Technology Committee.

The following software applications are supported by the department's technical support group. Support for any additional applications needs to be approved by the Technology Committee.

The following libraries and compilers are supported by the department's technical support group. Support for any libraries and compilers needs to be approved by the Technology Committee.

The following submission tools are supported by the department's technical support group. Support for any additional submission tools needs to be approved by the Technology Committee.

Uncertainty quantification (UQ) is the science of quantitative characterization and reduction of uncertainties in both computational and real world applications. [Uncertainty quantification From Wikipedia]

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