Professional Summary
Second-year undergraduate with a strong interest in programming, problem-solving, and technology. Actively participating in competitive programming, with 400+ problems solved across platforms like CodeChef (2+) and Codeforces (Pupil). Committed to learning core computer science concepts, including data structures, algorithms, and web development. A fast learner with a growth mindset, currently building foundational skills to contribute to real-world software projects in the future.
Projects
Drug Discovery ADMET Predictor
Full-stack bioinformatics app for AI-powered ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) prediction from SMILES input.
- Users draw or paste SMILES strings; backend uses ML models to predict properties like solubility, permeability, and mutagenicity in real time.
- Built with JavaScript, Node.js, Express, Mongoose, and integrated ML pipeline.
- AI assistance (ChatGPT + documentation tools) was used throughout development for model integration and backend logic.
- Deployed on Render: admet-5.onrender.com
MoodLit: AI Mood-Based Book Recommender
Interactive React app recommending books based on the user's mood using AI sentiment detection.
- Users input or select mood, which is analyzed using emotion-detection logic; matched books are fetched via Open Library API.
- Built with React, Node.js, Express; features real-time interaction and mood-based suggestions.
- Took assistance from AI tools (e.g., ChatGPT) for frontend logic, mood mapping, and API integration.
- Deployed on Vercel: v0-moodlit1-blmw5o.vercel.app