M. Tech. in Computational Engineering & Networking

Academics

Computational Engineering is a broad, rapidly growing multidisciplinary area tha encompasses applications in science/engineering, applied mathematics, numerical analysis, and computer science. Going from application area to computational results requires domain expertise, mathematical modeling, numerical analysis, algorithm development, software implementation, visualization and validation of results.

Computational Engineering makes use of the techniques of applied mathematics and computer science for the development of problem-solving methodologies, which will be the building blocks for solutions to scientific engineering problems of ever-increasing complexity. It differs from mathematics or computer science in that analysis and methodologies are directed specifically at the solution of problem classes from science and engineering, and will generally require a substantial collaboration from those disciplines.

On the other hand, it is certainly more than using software packages to generate and visualize the results, since it also concerns the development of algorithms for solving scientific and technical problems. Today, many problems in science and engineering can be treated only by means of efficient use of computers. Computation is now regarded as an equal and indispensable partner, along with theory and experiment, in the advancement of scientific knowledge and engineering practice. Numerical simulation enables the study of complex systems and natural phenomena that would be too expensive or dangerous, or even impossible, to study by direct experimentation.

Fellowship is awarded to meritorious students on the condition that they satisfy the criteria set by the centre.

Duration of the Course : Two years

Highlights of the Programme

CEN offers two M. Tech. level course which lays the foundational bricks for data science, machine learning, automation related areas.

• Computational Engineering and Networking (CEN)
• Remote Sensing and Wireless Sensor Networks (RSW)

Thrust Areas in Research

Research is focused in data science for :

• Machine learning and Pattern Recognition
• Health care
• Driverless Car
• Power Quality Assessment for Smart Grids
• Computer Vision in Robotics
• Natural Language Processing
• Hyper Spectral Imaging based remote sensing
• High Performance Computing
• Speech Processing
• Big data analytics in Text, Vision, health care and Energy

Workshops @ CEN

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Funded Projects in CEN