Information Technology at VIT, Vellore | Open Source Lead @MFC-VIT
B.Tech Information Technology student at Vellore Institute of Technology with experience building backend systems, machine learning applications, and full-stack projects.
Mozilla Firefox Club VIT
4 mos · Vellore, Tamil Nadu, India
Enhanced backend systems for Scavenger of the Year by implementing Server-Sent Events; resolved backend bugs in the Code2Innovate Yantra portal supporting 500+ concurrent users; delivered a cybersecurity awareness session; guided and supervised junior developers.
Mozilla Firefox Club VIT
11 mos · Vellore, Tamil Nadu, India
Playanamics - GameDev Workshop held during Gravitas '25, contributed and helped organise the flow of event by helping and clearing doubts of participants' doubts regarding GameDev. CodeXcape - Contributed to the website building of CodeXcape held during Gravitas '25, built the backend of Jeopardy and Scotland Yard. Unplugged & Secured – A Talk on Awareness on Cybersecurity - Conducted the event by being one of the speakers by explaining awareness of CyberSecurity and the explaining the use of CTFs.
Bachelor of Technology - BTech, Information Technology
Jul 2024 - Jun 2028
CGPA: 9.20/10
Class XII, CBSE
May 2011 - Jun 2024
86.2%; Bengaluru
Class X, ICSE
2022
91%; Bengaluru
Developed a full-stack email classification system for real-time processing and organization using Node.js, Express, FastAPI, DistilBERT, Hugging Face, and React. Built secure email fetching and preprocessing with zero storage, a low-latency batch inference service, and a fine-tuned DistilBERT model achieving 90% accuracy across 8 email categories.
Engineered the backend for a competitive tech event by MFC-VIT during Gravitas. Developed REST APIs for Jeopardy and Scotland Yard, handled registrations, team formation, and submissions, and containerized the backend with Docker and PostgreSQL via Supabase.
Developed a Python application for interacting with offline large language models. Built setup utilities with Tkinter, a Streamlit UI, document-based querying with RAG, multimodal AI support, and image generation using Stable Diffusion with PyTorch.