DEPARTMENT OF
SCHOOL OF ENGINEERING
S C H O O L O F E N G I N E E R I N G
COMPUTER SCIENCE
Symptoms-Disease Detecting Conversation Agent using Knowledge Graphs
Conversational agents often lack dynamic responses in medical conversations. Our project introduces an adaptive agent blending natural conversation with medical expertise to address this. Our proposed End-to-End system integrates a rich medical knowledge graph using Natural Language Understanding to bridge the gaps in symptom-disease relations. However, limitations in standalone knowledge graphs are overcome by incorporating a fine-tuned GPT-3 model. This fusion allows more human-like and contextually relevant interactions in medical dialogue systems.
Snehasis Mukherjee
Achievement: Selected as Eminent Speaker by ACM India for the ACM ESP programme.
Selected as an Eminent Speaker by ACM India.
Working on a Research project on Image Dehazing
Working on a Research project to find a Neural Network specific to a task (NAS).
Ila Ananta Dr. Sonia Khetarpaul Dr. Dolly Sharma
S C H O O L O F E N G I N E E R I N G
COMPUTER SCIENCE
Dr. Sonia Khetarpaul, Lakshay Jain, Kush Goyal, and P Vishnu Tej
Lecture Video Summarisation using Deep Learning
In today’s rapidly evolving digital era, educational institutions and professors are increasingly sharing video lectures online to support students. While these lectures effectively teach topics from scratch, they pose challenges for quick revisions. Viewers struggle to control the pace, often interrupting playback to navigate the content. Additionally, finding specific information within the video and skimming the unstructured transcript for relevant content can be cumbersome, hindering efficient learning.
S C H O O L O F E N G I N E E R I N G
COMPUTER SCIENCE
Dr. Dolly Sharma, Dr. Sonia Khetarpaul, Shashwat Tiwari, Lakshman Aakash, and Aryan Gupta
Predicting Epidemic Outbreak using Climatic Factors
This research explores the intricate relationship between weather-related variables and the transmission dynamics of two pivotal diseases: Covid-19 and dengue. Our primary goal is to advance our understanding of how climate factors influence the occurrence and spread of these diseases through a comparative analysis. In the context of the pressing need for accurate prediction systems, our research aims to contribute to the refinement of public health planning and decision-making strategies. In this work, our findings underscore the superiority of certain models in predicting epidemic outbreaks.
Dr. Sonia Khetarpaul
Dr. Dolly Sharma