💡 I'm a Computer Science student at Chinmaya Vishwavidyapeeth (2027 batch) with a passion for building scalable web systems and diving deep into the world of AI and optimization algorithms.
🚀 Current Focus:
- StudyQuest: Building an AI-powered, terminal-style learning platform with adaptive quizzes and gamified progress.
- Lokha: Developing a community-driven hub for discovering, sharing, and voting on the best AI prompts.
🔬 Research: I recently reimplemented the Lion Optimizer from a NeurIPS 2023 paper, outperforming AdamW on FashionMNIST!
🌊 Leadership: I lead the Oceanic IEEE Student Chapter, where I organize AI + Ocean-tech events and foster industry-academia collabs.
Languages: Python | Java | C++ | JavaScript | TypeScript | SQL
Frontend: React.js | Next.js | Tailwind CSS | HTML5 | CSS3
Backend: Django | Node.js
Database: MySQL | Firebase
Tools: Git | GitHub | VS Code
| 🔧 Project | 💡 Description | 🛠 Stack |
|---|---|---|
| StudyQuest | A terminal-style, AI-powered learning platform with adaptive quizzes, real-time XP tracking, and a minimalist B/W dashboard. | Next.js, FastAPI, Supabase, Gemini AI |
| Lokha | A community-driven web app for discovering, sharing, and voting on AI prompts with interactive voting and Google OAuth. | Next.js, Prisma, tRPC, Supabase |
| Lion Optimizer | Recreated NeurIPS 2023 paper logic with symbolic optimizer search engine. Achieved 88.26% test accuracy on FashionMNIST. | Python, PyTorch |
| IEEE Website | Built multiple frontend sections with clean UI and responsive design for the university’s IEEE branch site. | React, CSS3 |
🧠 "Build boldly. Learn relentlessly. Ship proudly."