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Rupesh4604/README.md

About Me

Data Scientist at Esri R&D, building geospatial vision-language models, end-to-end from data pipelines through model architecture to deployed APIs. My Background spans deep learning, computer vision, and quantum-classical hybrid ML, with research training from IIT Bombay (M.Tech, Geoinformatics and Natural Resource Engineering) and NIT Andhra Pradesh (B.Tech, CSE). Prior experience at CAIR, DRDO.

  • 🔭 Building: Geospatial vision-language models at Esri
  • 🌱 Studying: World models (VL-JEPA), Diffusion Models, agentic systems, quantum-classical hybrid architectures for vision
  • 🤝 Collaborating on: Multimodal LLMs, agentic AI, NLP, applied CV/DL research
  • 💬 Talk to me about: Deep learning, ML systems, computer vision, AI architecture
  • 🌐 Portfolio: rupesh-portfolio
  • 📫 Contact: rupesh32003@gmail.com

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  1. Intelligent-Multi-Agent-Knowledge-Assistant Intelligent-Multi-Agent-Knowledge-Assistant Public

    A multi-agent system designed to provide specialized answers from multiple knowledge bases using an advanced Retrieval-Augmented Generation (RAG) pipeline. This project demonstrates a robust archit…

    Jupyter Notebook

  2. ProdHub ProdHub Public

    ProdHub is a modern, all-in-one web application built to help you organize, achieve, and grow. Seamlessly manage projects, tasks, habits, and your calendar from a single, intuitive platform - all w…

    JavaScript 1 1

  3. Quantum-Convolutional-Neural-Network-for-Slum-Classification Quantum-Convolutional-Neural-Network-for-Slum-Classification Public

    Quantum Information Processing (QIP) Journal 2026 - Official implementation of the paper "QCNN for Urban Informal Settlement Detection".

    Jupyter Notebook 1

  4. rs-dl-architect rs-dl-architect Public

    Build, analyze, and review deep-learning architectures for computer vision with strong specialization in remote sensing, GIS, and satellite imagery.

    1

  5. Awesome-Geospatial-Vision-Language-Foundation-Models Awesome-Geospatial-Vision-Language-Foundation-Models Public

    A curated map of geospatial foundation models both pure-vision GeoFMs and vision-language models (RS-VLMs) plus a learning roadmap, open-problem gap map, and benchmark tracker.

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