Huge type of data which is not in Linear or polynomial structure can be dealt under 5Gs of GML, here we are focusing on Geometric deep learning to tackle data in higher dimensions.

Deep Learning is evolving exponentially day-by-day, in this research pod we focus on core Deep Learning, we simulate different architecture and try to come up with better results.
The major focused areas are Generative Modelling, Computer Vision, Bayesian Deep-learning and evolution in object detection like tasks.

In this Pod we focus on field of study in which mathematical tools and theories are used to investigate brain function

Drug Discovery has huge potential in GraphML also Biomedical Data can be processed and combined with DL models to produce high efficiency Drugs.

Every growing tecthnology emerges with its own security concerns, we aim to develop self developing security system using artificial intelligence.

Deep Learning provides immence opportunities for growth in field of Natural Sciences, In this research pod, our group studies application of data represetation learning in Meachanical Engineering and its sub fields.