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NeelM47/README.md

πŸš€ AI Engineer | MSc Artificial Intelligence @ University of Manchester

πŸ‘‹ About Me

I'm a passionate Artificial Intelligence Engineer specializing in building intelligent systems that bridge cutting-edge research with real-world applications. With a strong foundation in Machine Learning, Computer Vision, and Natural Language Processing, I thrive on solving complex problems through data-driven solutions.

πŸ”¬ Current Focus

  • Advanced RAG Systems: Architecting full-stack, containerized RAG applications using Django, Neo4j, and Google Gemini
  • Multi-Modal AI: Developing conversational agents capable of reasoning, planning, and autonomous task execution
  • Production ML: Transitioning academic AI research into robust, scalable enterprise solutions

πŸ’» Technical Arsenal

πŸ€– AI & Machine Learning

Deep Learning: PyTorch, TensorFlow, Computer Vision, NLP, LLMs, Transformers
MLOps: Model Optimization, Vector Databases (FAISS), Hybrid Retrieval Systems
AI Architectures: RAG Pipelines, LangChain, Multi-Agent Systems, Cognitive Robotics

πŸ’Ύ Data Engineering

Data Pipelines: AWS Databricks, ETL/ELT, Apache Spark, Data Warehousing
Databases: Neo4j (Graph), PostgreSQL, MySQL, Vector Databases
Cloud & DevOps: AWS (S3, EC2), Docker, Git, CI/CD, Agile Methodologies

πŸ›  Software Engineering

Languages: Python, R, Java, C++, SQL, JavaScript
Backend Development: Django, REST APIs, System Architecture
Tools & Platforms: Linux, Windows, Tableau, Power BI, Jupyter

πŸŽ“ Education

MSc Artificial Intelligence | University of Manchester (2023-2025)
Relevant Coursework: Computer Vision, Large Language Models, Cognitive Robotics, Machine Learning Optimization

B.E. Computer Engineering | Bharati Vidyapeeth College of Engineering (2019-2023)
Focus: CNNs, Natural Language Processing, Data Science, Network Security

πŸ† Notable Projects

πŸ” Knowledge-Extractor RAG System

Full-stack AI application featuring hybrid graph-vector retrieval, cross-encoder re-ranking, and verifiable cited answers from PDF documents

πŸ“Š Enterprise Data Pipeline Architecture

End-to-end AWS Databricks pipelines processing large-scale e-commerce data with Power BI dashboards for business intelligence

🎯 Symbolic Machine Learning Prover

Intel-partnered project enhancing SMLP for machine learning model analysis and optimization

πŸ“ˆ What I Bring to the Table

  • Research-to-Production Mindset: Bridging academic AI advancements with practical business applications
  • Full-Stack AI Development: From algorithm design to deployment and monitoring
  • Data-Driven Decision Making: Leveraging analytics to drive AI system improvements
  • Cross-Functional Collaboration: Experience working in Agile teams with stakeholders at all levels

🌐 Let's Connect

⚑ Beyond Code

  • 🧠 Continuously exploring the intersection of human cognition and artificial intelligence
  • πŸ“š Passionate about knowledge sharing and mentoring in the AI community
  • β˜• Fueled by coffee and complex problem-solving challenges

"Engineering intelligent systems that learn, adapt, and deliver real-world impact."

Pinned Loading

  1. video-to-book video-to-book Public

    AI-powered pipeline to transform YouTube videos into polished Bionic Reading eBooks. Leveraging Groq (Llama 3.3 & Whisper-Large-v3) for ensemble transcript synthesis.

    Python

  2. mdm-adaptive-inference mdm-adaptive-inference Public

    PyTorch implementation of "Train for the Worst, Plan for the Best." Investigating adaptive token ordering in Masked Diffusion Models (MDMs) to sidestep hard subproblems and elicit reasoning in disc…

  3. Knowledge-Extractor-RAG Knowledge-Extractor-RAG Public

    Production-ready Agentic RAG system featuring an asynchronous Django ingestion pipeline, hybrid Neo4j graph/vector retrieval, cross-encoder re-ranking, and a multi-tool LangChain agent powered by G…

    Python

  4. smlp smlp Public

    Forked from SMLP-Systems/smlp

    Symbolic ML Prover

    Python

  5. Road_Damage_Detection Road_Damage_Detection Public

    Deep Learning-based road damage detection and classification. Features a CNN pipeline for image analysis, a web-based monitoring dashboard, and an integrated messaging service for real-time safety …

    Python

  6. summarizer summarizer Public

    Hybrid multi-document summarization system using Sentence-Transformers and KMeans clustering for semantic topic extraction, followed by BART-based abstractive refinement. Fully containerized with F…

    Python