Pranav's
Project Portfolio

Real time Chat-application

Leveraged the MERN stack (MongoDB, Express.js, React, Node.js) enhanced with Socket.io for real-time bi-directional communication between clients and servers. Integrated JWT (JSON Web Tokens) to handle secure authentication and authorization processes, safeguarding user interactions and data. Engineered comprehensive error handling mechanisms on both the server and client sides to enhance application reliability and user trust.

Instagram Engagement Prediction

Developed a model using YOLOv8 and LSTM to predict Instagram engagement based on visual content and historical data. This project showcases my skills in machine learning and data handling, providing actionable insights for marketing strategies.

Pacman Game Development

Recreated the classic Pacman game using Java. This project highlights my ability to design and implement game mechanics and user interfaces, enhancing player engagement and interaction.

Comparative Analysis of Probabilistic Data Structures for Genomic Membership Testing

The exponential growth of genomic data, particularly DNA sequences that can span billions of base pairs, presents significant challenges related to storage, indexing, and querying due to the immense computational and memory resources required. Modern sequencing technologies that generate datasets from millions of individuals exacerbate these challenges, rendering traditional data structures such as hash tables and trees inefficient due to their substantial memory footprint. The project focuses on evaluating and comparing the performance of three probabilistic data structures— Traditional Bloom Filters, Cuckoo Filters, and RAMBO Bloom Filters—in the context of genomic data membership testing. The objective is to measure their effective- ness in terms of False Positive Rate (FPR), memory efficiency, and query time, particularly for large-scale genomic datasets.

Sentiment analysis using python

The goal of this project is to develop a sentiment analysis tool that can accurately determine the emotional tone behind a body of text. This tool is intended to help businesses monitor brand sentiment from customer feedback and social media posts, enabling them to respond more effectively to customer needs and market trends.

URL Shortner

Developing a URL shortening service that includes the use of Redis for caching to ensure quick retrieval of NoSQL data and effective response times. Implemented selective caching strategies to optimize performance. For data storage, the project utilizes Google Cloud Bigtable to manage large-scale data, including both short and long URLs, along with user IP addresses.