Compute-intensive Monte Carlo methods are at the heart of material research. This project will explore specific software design patterns for heterogeneous computing specific to material research. The system of interest is dislocation loop models i

Apply novel quantum machine learning techniques for applications in chemistry. The focus would be on large-scale models that align with the utility-scale experiments.

Formulate a theoretical approach to allocate multiple circuits on the same hardware without significantly compromising in the quality of layout for each circuit. This will maximise the utilisation of current quantum hardware, and lead to improved use

to use LLM and Q learning for build a model for conversation disentanglement

Classically geometric invariances have been used in machine learning. Some recent works have proposed the same for quantum ML :- https://arxiv.org/pdf/2205.02261.pdf https://arxiv.org/pdf/2210.07980.pdf We will explore some of these and potential

Diffusion modelling is one of very recent approach to generate text using diffusion model after gaining immense success in image generation. The project aims to explore and build diffusion based generative multimodal LLM for code and text generatio

Connected assets are the assets that are together involved in performing one or more business processes. If vulnerability/threat on one of the assets is exploited, because of the connectedness - it could lead to failures or disruptions to assets it i

The project aims to explore the impact of Dynamic In-context learning approach for Generative MultiModal LLM and develop algorithm to enhance the LLM performance through representation learning approach.

To determine the Handwriting of a user to analyze PSYCHOLOGICAL behaviour