• I am currently an undergraduate student majoring in Computer Science & minoring in Economics and Data Science
• My technical experience includes:
  • Software Engineering Intern @ ARUP Laboratories
  • Undergraduate Research Assistant @ Michigan State University Civil and Environmental Engineering Department
  • Undergradutate Research Assistant @ Michigan State University Office of Medical Education Research and Development
  • Backend Developer @ Quarry
• My main areas of expertise are:
  • Building full-stack web applications using Django + RESTful API + SQL Databases
  • Machine Learning, specifically Transformer models in Natural Language Processing
  • AWS for cloud services for system design & practical ML

The Shopping Assistant project is a full-stack web-based application designed to enhance online shopping experiences through web scraping, chatbot assistance, and wishlist management. Built using Django, Celery, Redis, and TailwindCSS, this project provides real-time price tracking, automated notifications, and a chatbot interface.

The Genesis project is a full-stack web app developed during a Datathon, where I won $1,500 with 1st place in the GenAI track. It leverages Generative AI to create personalized travel itineraries, including flights, hotels, and transportation, tailored to users' preferences and budgets. With automation and AI-driven recommendations, Genesis simplifies trip planning, making travel seamless and hassle-free.

The Jack in the Box project is a C++ application designed to simulate and animate various machine systems and characters. It features an animation framework, actor and timeline management, and machine system integrations. The project is built using CMake for cross-platform compatibility and includes a robust testing suite powered by Google Test.

Built for educational and research purposes, this project enhances animation and machine simulation using wxWidgets for UI, Google Test for validation, and Doxygen for documentation.

This web application is designed to make video editing easy and intuitive. It uses a combination of front-end and back-end technologies to provide users with a powerful tool that allows them to edit their videos quickly and efficiently using the generated transcript from the video you can delete words from the transcript to remove that section of the video.

This is an android app developed in Java to allow student organizations on campus to gain more exposure for their events with RSVPing functionality, Google Maps API to find the location and other cool features.

The Retrieval-Augmented Generation (RAG) System developed at ARUP Laboratories is an advanced AI-powered solution designed to enhance genetic variant information retrieval and report generation for clinical variant scientists. By integrating large-scale document processing, fine-tuned embedding models, and an interactive chatbot UI, the system streamlines access to critical genetic insights.

Quarry is an AI-powered content creation platform that helps podcasters and long-form video creators efficiently generate short-form content for social media. Using advanced machine learning models trained on thousands of high-performing short-form videos, Quarry automatically identifies the most engaging moments from long videos or podcasts, generates captions, and formats the content for optimal online reach.

The Geo-ML Project, developed at the Civil Engineering Department, Michigan State University, is an AI-powered web-based toolkit designed to streamline geotechnical data analysis using machine learning and automation. This project aims to assist engineers and researchers by simplifying the extraction, processing, and visualization of geotechnical data.