class ShreyanshGupta:
role = "AI Research Engineer"
location = "NIT Patna, India"
focus = ["Deep Learning", "Computer Vision", "NLP", "Graph ML"]
engineering = ["Full-stack web", "MLOps / DevOps fundamentals"]
mindset = "Research the idea → prototype it → ship it to production"- 🔬 I build explainable, lightweight deep-learning systems — from terrain-recognition CNNs to hybrid graph + language embeddings for citation sentiment analysis.
- ⚙️ I'm an AI engineer first, but I take models the full distance: data → training → API → deployed app.
- 🌐 Comfortable across the MERN / TypeScript stack and the Python ML ecosystem (PyTorch, scikit-learn).
- 🚀 Currently going deeper on applied deep learning, model deployment, and reproducible ML pipelines.
- 🤝 Open to research collaborations, ML internships, and applied-AI projects.
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High-accuracy, explainable, lightweight CNN for terrain classification — designed to be deployable on constrained hardware without trading away interpretability.
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Research on hybrid graph + language embeddings for citation sentiment — combining structural signals from citation graphs with contextual language models.
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Full-stack MERN streaming app — TMDB API, JWT auth, search history & trailers, with a live Netlify frontend.
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A gamified spatial experience built in TypeScript — interactive, immersive front-end engineering.
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👾 Pac-Man munches through my commits — regenerates every 24h via GitHub Actions