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imayankss/README.md

⭐ About Me:

About Me

AI/ML Engineer and Integrated M.Tech (AI) student at VIT Bhopal, building reliable end-to-end ML systems across NLP, financial analytics, forecasting, and decision support.

- 🔭 I’m currently working on reliability-aware on-device scientific-paper summarization and production-minded ML systems.
- 👯 I’m looking to collaborate on applied AI/ML, NLP, LLM systems, and data-driven products.
- 🤝 I’m looking for help with reproducible ML evaluation, model deployment, and open-source AI projects.
- 🌱 I’m currently learning reliable LLM systems, calibration, evaluation, and on-device AI.
- 💬 Ask me about Python, machine-learning pipelines, fraud-risk modelling, NLP, forecasting, FastAPI, and XGBoost.
- ⚡ Fun fact: I care as much about evidence, limitations, and safe failure modes as I do about model metrics.

🌐 Socials:

LinkedIn email

💻 Tech Stack:

Python HTML5 Markdown C++ R TypeScript AWS Cloudflare Firebase Vercel Apache Spark Bootstrap nVIDIA Django Express.js FastAPI JWT NodeJS OpenCV Streamlit Apache MySQL Postgres Redis NumPy Pandas PyTorch scikit-learn GitLab CI Git GitHub

📊 GitHub Stats:


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  1. SecureSwipe SecureSwipe Public

    Capacity-aware fraud-risk manager: ranks suspicious card transactions under a fixed review budget, exposes the legitimate-customer workload every operating point creates, and returns bounded, audit…

    Python

  2. Amazon-ML-Challenge-2026 Amazon-ML-Challenge-2026 Public

    Hackaton

    Python 1

  3. reliability-aware-on-device-summarization reliability-aware-on-device-summarization Public

    Evidence-first research on reliability-aware selection and abstention for on-device scientific-paper summarization.

    Python