Computational science and engineering (also called scientific computing) is a multidisciplinary
field that uses advanced computing capabilities to understand and solve complex problems
arising in various applications.Computational science frameworks include the development of
numerical algorithms to solve various problems, methods to extract knowledge from large
scientific data, and methods to model and simulate natural phenomena. The three main
mathematical tools that dominate the field are linear algebra, mathematical optimization, and
partial differential equations. The research in this field is often coupled with high-performance
Vision is arguably the important of all senses, without which our life would be qualitatively
different. For a wide range of applications, from "seeing robots" to the restoration of sight for the
blind, it is indispensable to understand vision as an information processing mechanism. Such
an inquiry is the primary task of Computational Vision , a scientific discipline that explores and
studies vision from an interdisciplinary computational point of view both for the automatic
analysis and interpretation of visual signals (i.e., images and videos) and for explaining and
understanding biological, and in particular, human vision. Unlike Computer Vision that was
mentioned above (which is a field of inquiry that is largely detached from other vision sciences),
exploring vision as a whole must involve an interdisciplinary research where computational
inquiry goes hand in hand with behavioral, cognitive, and neuroscience explorations. We
therefore complement the development of algorithms for the automatic analysis of images and
videos with computational modeling of visual functions, behavioral and psychophysical experimentation with humans and animals, and the computational exploration of physiological
and anatomical aspects of visual cortical regions.
Computer-music concentrates on the involvement of computers in music activities - be it composition, performance, research or education. Computers can be used to compose music, or to assist musicians in performance, improvisation, or investigation of music. Computational methods and techniques such as programming languages, data analysis, knowledge representation, machine learning, algorithmic design, sound analysis and generation are being used for extending, generalizing, investigation and improving traditional music processes. The scope of research in computer music is wide and the methods in use cover a wide variety of computational approaches.
Network Science deals with the analysis of Complex networks such as social networks
and technological networks. These networks are often characterized by a hierarchical
structure, heavy tail degrees distribution, and the small-world property, meaning that the
mean distance between pairs of nodes is small relative to the network's size. The
research on this area is quite diverse and include both the analysis of complex networks
from data and the study of theoretical models aiming to understand how these complex
networks gain these properties.
Time Series Analysis primarily deals with the development of methods and tools for processing time-series data. Generally speaking, any data collection which can be ordered sequentially may be regarded as a time series. There are numerous scientific and engineering examples involving sequential data such as heartbeats of patients, the behavior of stocks, music tunes, etc. Many of the problems in machine learning are also relevant in time series analysis including prediction of future data instances, signal interpolation, model regression for extracting parameters, and much more. Methods and tools originated in the study of time series data are employed in various industries, facilitating the processing and analysis of sequential information.