PhD Seminar Presentation " COVID-19 Analysis in Canada using Deep Learning and Multi-Factor Data-Driven Approach with a Novel Dataset" By: Shaon Bhatta Shuvo

Friday, February 16, 2024 - 11:00 to 12:00

The School of Computer Science at the University of Windsor is pleased to present …
COVID-19 Analysis in Canada Using Deep Learning and Multi-Factor Data-Driven Approach with a Novel Dataset

PhD. Seminar by: Shaon Bhatta Shuvo

Date: Friday, February 16, 2024

Time: 11:00 am – 12:00 pm

Location: Essex Hall 122


As the world recovers from the COVID-19 pandemic, there is a growing need for effective strategies to prepare for future health crises. Artificial Intelligence (AI), driven by comprehensive and up-to-date data, can play a crucial role in addressing such challenges. Focusing on Canadian data, this study demonstrates the importance of extensive data collection and its implications for global health crisis management. Using feature extraction and deep learning-based regression techniques, we identified key predictors of COVID-19, achieving an $R^2$ of 0.93 and 0.80 for predicting new cases and deaths. The results emphasize AI's potential in guiding data-driven strategies, stressing the need for global collaboration in data collection and AI deployment to prepare for future health crises.

PhD Doctoral Committee:

Internal Reader: Dr. Dan Wu
Internal Reader: Dr. Saeed Samet
External Reader: Dr. Abdulkadir A Hussain
Advisor (s): Dr. Ziad Kobti, Dr. Narayan C Kar