Computational Science Lab (CSL)

Computational
Science Lab (CSL)

About

We work at the interface between computation and physical sciences related to the simulation of Nature and artificial intelligence.

Computational science is a rapidly growing interdisciplinary field. Many problems in science and technology cannot be sufficiently studied experimentally or theoretically. It may be too expensive or impossible due to the space and timescales involved. The Computational Science Laboratory’s experts in high-performance computing applied mathematics, and domain sciences work together to develop, adapt, and optimize advanced, scalable algorithms to solve problems in computational physics, biology, chemistry, materials science, and energy and environmental sciences with increasingly faster computers. Primarily, researchers collaborate in areas impacting data-intensive applications, performance-specific workflows, and novel computing architectures. Computational science is considered by many to be a third methodology in scientific research, along with theory and experiment, and working in tandem with them. Computational science can be used to corroborate theories that cannot be confirmed or denied experimentally, for example, theories relating to the creation of the universe. On the other hand, advances in experimental techniques and the resulting data explosion allow for data-driven modelling and simulation. to gelatin in sustained drug release systems.

Research Areas

Video processing applications often need to incorporate robust noise reduction techniques that provide visually pleasing effects. For real-time implementation, a novel hardware architecture has been developed which enables noise reduction and object tracking. This project implements automated subparametric mesh-based optical flow estimation and video quality enhancement using Convolutional Neural Networks (CNN). In hardware implementation mesh based median filter with the Lucas-Kanade approach has been used for noise removal and object tracking.