Research Experience

"InnerEye: A Tale on Images Filtered using Instagram Filters - How Do We Interact with Them And How Can We Automatically Identify The Extent of Filtering?" EAI MobiQuitous 2022

This project aims to assess public perception regarding the prevalence of filtered images in social media and the application of automated assistance in recognizing filtered images and determining the extent of filtering applied to these images. We developed InnerEye, an automated tool capable of providing both qualitative and quantitative analyses of the extent of filtering applied to an image. Additionally, we conducted a user survey to evaluate the tool's effectiveness and usability.

"DeepHealth: A secure framework to manage health certificates through medical IoT, blockchain and deep learning." MeMeA 2021

In this project, we designed an Electronic Health Record (EHR) storage system that utilizes blockchain and off-chain technologies to store individuals' COVID-19 status, enabling verification before granting access to public places. Furthermore, we integrated a deep learning-based facial recognition system to ensure the integrity of health certificates.

"Security Code Review Analysis & Automated Detection" BUET Undergrad Thesis 2019

In this project, we performed qualitative and quantitative analyses on the prevalence of security code review in a code review dataset collected from Chromium Gerrit and annotated by expert researchers. We also built a security code review detection pipeline based on classical machine learning algorithms and improved the result using boosting frameworks, namely LightGBM.