Current project's

Project - Adaptation of Geospatial Foundation Models (GFMs) for Finer Scale Soil

Soil moisture is a critical parameter that influences agricultural practices, climate conditions, hydrology, and various other phenomena. It also plays a significant role in nature-based carbon sequestration. However, different applications require s

  • In progress

Project - Exploring Graph foundation model for power utility usecases

Graph Foundation Models (GFMs) are designed to work with graph data (networks of interconnected entities). They are pre-trained on massive graph datasets to learn the inherent structure and patterns within networks. It is excel at network analysis, i

  • In progress

Project - Power plant emissions quatifications

This proposal aims to leverage deep learning techniques, specifically neural networks, to enhance the accuracy of emission quantification from XCO2 images provided by OCO2/3 satellites.

  • In progress

Project - EDI Specs Generation

Bot to generate EDI Specification

  • In progress

Project - Speech Emotion Detection

AI model to detect emotion in speech.

  • In progress

Project - Code data preprocessing module to remove the headers and commented cod

This module is designed to automatically remove license headers and commented code from source code files. It will support multiple programming languages and can be easily extended to accommodate new ones. The module will be integrated into the data

  • In progress

Project - AI powered intelligent glasses for deaf and mute individuals.

The objective of this research work is to find possible way of detecting finger movements with help of powerful sensors, which would thereafter be used to detect the sign language that was made and then convert it to audio.

  • In progress

Project - Prediction of False Positives Alerts from QRadar SIEM

The objective is to predict the false positive alerts from the alerts present in QRadar SIEM by using Machine Learning and Data Science.

  • In progress

Project - Exploration of Geometric QML/ Group Invariant QML/ symmetries for op

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

  • In progress

How it Work

Mentor and Student do the registration

Menter create the project and student applies on it.

Student Upload the Terms & Conditions and Mentor approves it

Mentor Reviews the Required document uploaded by student

Student submits the project