Developed a React application to Visualize 3, Classical Path Finding Algorithms: Breadth First Search(BFS), Depth First Search(DFS), and Dijkstra’s Algorithm(Shortest Path Algorithm).

Enhanced the Visualization of the algorithms through Implementation of CSS3 animations, and Optimized visualization of algorithms by writing logic to clear walls, grid and nodes in JS.

Created an interactive user experience by Designing a Customizable GUI, with Functionality to modify grid, walls, source and destination node.

Developed a deep learning system to detect AI-generated deepfake videos and images. Used a ResNext CNN for frame-level feature extraction and an LSTM RNN for classification, addressing concerns like political manipulation, fake terrorism events, revenge porn, and blackmail.

Implemented additional detection for deepfake images using a separate CNN-based classifier to identify manipulated content.

Evaluated the system’s performance with real-world data by creating a comprehensive, balanced dataset sourced from various datasets like the Deepfake Detection Challenge.Optimized the models to handle real-time data and scenarios, providing a robust solution to detect deepfakes with high accuracy.

Developed a web-based application to assist educators in calculating and analyzing Course Outcomes (CO) and Program Outcomes (PO) based on data collected through Excel spreadsheets.

Designed a user-friendly interface using Material UI to allow educators to input data and generate outcome analysis reports.

Implemented JavaScript functionality to process and analyze data, providing real-time feedback and insights to educators.Utilized Microsoft Excel for data storage and operations, optimizing performance and simplifying data handling for users.Delivered an intuitive solution that enables educators to assess educational outcomes efficiently, contributing to curriculum improvement and academic planning.