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sjagadee/README.md

Hi there, I'm Srini Jagadeesh 👋

🚀 About Me

I'm a Lead Software Developer with 10+ years of experience specializing in healthcare interoperability and AI/ML engineering. I'm passionate about bridging the gap between healthcare technology and artificial intelligence to create innovative solutions that improve patient care and data accessibility.

Currently working at HealthChain.io (part of iNetFrame Technology), where I architect healthcare data exchange solutions and build intelligent systems powered by AI.

🔭 What I'm Working On

  • Building conversational AI chatbots and RAG applications with LangChain and LangGraph
  • Developing agentic AI architectures for healthcare applications
  • Implementing FHIR R4 resource extraction systems and data transformation workflows
  • Creating machine learning models for classification tasks with real-world healthcare data

💼 Core Expertise

Healthcare Interoperability

  • FHIR R4 | HL7v2 | EDI | CCDA
  • Healthcare Terminology Servers
  • Clinical Data Transformation
  • Healthcare Data Standards & Compliance

AI/ML Engineering

  • LangChain & LangGraph for orchestration
  • RAG Applications with Vector Stores
  • Conversational AI & Chatbots
  • Classical ML (Random Forest, XGBoost, Decision Trees)
  • Deep Learning & Neural Networks
  • Imbalanced Dataset Handling (SMOTE)

Full-Stack Development

  • Backend: Node.js, Java, Python
  • Frontend: JavaScript, TypeScript
  • Databases: MongoDB, PostgreSQL, Vector Databases
  • Cloud: AWS, Azure
  • Architecture: Microservices, Docker, Apache NiFi

🛠️ Technical Stack

Languages:        Node.js, Python, Java, JavaScript, TypeScript
AI/ML:            LangChain, LangGraph, Scikit-learn, XGBoost, TensorFlow
Healthcare:       FHIR R4, HL7v2, CCDA, EDI
Databases:        MongoDB, PostgreSQL, Vector DBs
Cloud & DevOps:   AWS, Azure, Docker, Microservices
Tools:            Git, REST APIs, Azure Functions, Streamlit, Gradio

🎯 Current Focus

  • 🤖 Transitioning deeper into GenAI and Agentic AI roles
  • 📚 Mastering LangGraph workflow execution and state management
  • 🏥 Innovating at the intersection of healthcare and AI
  • 🔬 Exploring advanced RAG architectures and guardrail implementations

📫 Connect With Me

LinkedIn

🎓 Education

Master of Science in Information Technology and Management
Illinois Institute of Technology, Chicago

📊 GitHub Stats

GitHub Stats

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  1. GenAI_LangChain_Models GenAI_LangChain_Models Public

    Implementing LangChain to build application on top of Language Models

    Python

  2. eda eda Public

    Feature Engineering and Exploratory Data Analysis

    Jupyter Notebook

  3. GenAI_LC_Coversational_Chat_bot GenAI_LC_Coversational_Chat_bot Public

    Jupyter Notebook

  4. GenAI_LangChain_RAG_APP GenAI_LangChain_RAG_APP Public

    Text to SQL using Gemini and RAG

    Jupyter Notebook

  5. GenAI_LangChain_VideoQ-A GenAI_LangChain_VideoQ-A Public

    An application that has question and answering capabilities based on video (Youtube) context.

    Jupyter Notebook

  6. RAG_Conversational_App RAG_Conversational_App Public

    A full-stack Retrieval-Augmented Generation (RAG) chatbot application built with LangChain, FastAPI, and Streamlit. This application allows users to upload documents, ask questions about them, and …

    Python