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Data in sign languages in general is scarce, and in ISL in particular. For the estimated 10 to 20 lakh hearing impaired people in our country, the number of ISL interpreters are in hundreds. This project aims at creating intreprator for ISL.


Escalation of technology led to an increase in the capability to record and store personal data about consumers and individuals. Data anonymization will allow for the re-use of personal data in privacy- preserving ways and If stolen, it is very hard to re- identify it.


This project aims at developing a precision learning model. Navigated learning implements precision learning, by computing a variety of semantic embeddings. This project explores Navigated Learning models for enterprise settings.

Clinical Decision Support System

This solution is designed to enable easy integration with external applications. If you are a healthcare application developer and would like to integrate this solution to your application, we expose REST APIs that you can use.


A Bloackchain based platform which allows to create digital records like certificates, which will be retrieved by contact tracing application through API’s. Moreover such records retrieved are with user consent and without doubting the authenticity.


Project aims to design an interpretable, scalable deep model that can handle high-dimensional imbalanced datasets arising in various applied AI domains.

Remotely Accessible lab

Project aims to make a remotely accessible lab that uses hardware on which experiments can be performed. Students can perform experiments through a website where experimental parameters can be configured.

Deep Generative Models

This project aims to developing novel methods which utilize trained deep generative models for improving the deep learning models on diverse geospatial dataset for Earth science applications.


Project aims at improving  Speech to text conversion for Kannada, and develop semantic processing models like topic modeling, argument mining, and sentiment analysis.

CT scan analysis for COVID-19 screening

The goal of the project is to build a system that takes as input CT scans, and answers the following: Covid-infected: Yes or No, along with a confidence score and Contour detection of the lesions.

Automatic Document Processing

Project goal is to generates a structured output, say as an xml format, that gives various information in the document. This can reduce the huge manual effort of entering the data into the system

Privacy preserving ML and neuroscience

A main contribution of this work will be creation and deployment of a privacy preserving machine learning infrastructure for health care, applicable in general.

Medical images segmentation

Project aim to develop novel and robust techniques for identifying “super-pixels” in medical images based on self-supervision learning.