Computational Science is a mixture of Science, Mathematics and Computer Science.

Wikipedia defines Computational Science as,

*Computational science (also scientific computing or scientific computation) is concerned with constructing mathematical models and quantitative analysis techniques and using computers to analyze and solve scientific problems. In practical use, it is typically the application of computer simulation and other forms of computation from numerical analysis and theoretical computer science to problems in various scientific disciplines.*

Essentially, computational science uses concepts from computer science and mathematics to solve problems arising in natural sciences in a numerical manner rather than in an analytical manner.

- It takes some field of science, say, physics, sociology, informatics, finance, economy, biology, law or linguistics.
- Then it takes a problem from that particular scientific field and constructs mathematical models to try and solve these problems.
- Now, these problems can’t always be solved using qualitative analysis (deriving properties by using the laws and principles). So, we use quantitative analysis to find the answer instead of analytic methods.
- The last part is where Computer Science comes in. You write programs to solve those scientific problems for you based on those mathematical methods. One also makes simulations to visualize the different scenarios in those complex problems.
- High Performance Computing comes in when the program’s run time becomes untenable. Parallel programming tools and techniques are used to enable one to solve the otherwise inaccessible problems.

This institute tackles all aspects of computational science via courses that are offered to computational science students with four core courses that are meant to give the students pursuing it a pretty holistic understanding, knowledge and experience required to be called B. Tech (Honours) in ICT with a minor in CS graduates. The courses range from getting a basic understanding of applying natural sciences in a computational setting via a introductory computational physics course. Then students are exposed to high performance computing techniques through the high performance computing. They also get acquainted with numerical methods via the computational and numerical methods course. Finally, with all the basics done, they are introduced to various modelling and simulation concepts. Apart from these core courses, the students get many electives that boost their domain knowledge and arm them with the tools and concepts needed to analyze and understand these models and make inferences leading to solutions to the real life problems.

The whole scope of computational science ranges from using domain knowledge of the particular domain and then modelling real life problems arising in those domains and simulating those models. Additional courses and electives provide many insights into the results that are produced. Some focus merely on making the computations possible using high performance computing and parallel programming techniques. Others focus on getting a better understanding of these using concepts from say, non-linear science and optimization theory.

With the advent of powerful computing infrastructure and more complex problems arising in many fields, computational science aims to equip practitioners with the required knowledge and prowess to tackle any difficulties with the help of these upcoming modes of problem solving.