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atharvaaswale/readme.md

👋 Hi, I'm Atharva

💡 AI Engineer | Ex-Android Developer

I build AI-powered applications that solve real-world problems — combining my software engineering background (2.5+ years) with modern AI systems like LLMs, RAG pipelines, and intelligent automation.

🚀 What I Do

  • Build LLM-powered applications using LangChain, LangGraph, Vector DBs, and modern APIs
  • Design Retrieval-Augmented Generation (RAG) systems for domain-specific Q&A
  • Develop end-to-end AI solutions — from data processing → model → deployment
  • Leverage prior experience in Android & backend systems to ship production-ready apps

🛠️ Tech Stack

AI / ML

  • LLM APIs, LangChain, LangGraph RAG
  • FAISS, Embeddings, Vector Search
  • Scikit-learn, NLP

Backend & Deployment

  • Python, FastAPI
  • Streamlit, Docker

Software Engineering

  • Android (2.5 yrs), REST APIs
  • SQL, Data Handling, System Design

📈 Current Focus

  • Building production-ready AI applications
  • Advancing LLM system design (agents, tools, memory)
  • Improving backend + deployment skills for AI systems

📫 Contact

Pinned Loading

  1. MediSage-AI MediSage-AI Public

    A medical question-answering system powered by Retrieval-Augmented Generation (RAG). MedSage AI uses vector embeddings and a large language model to answer medical queries based on the Gale Encyclo…

    Jupyter Notebook

  2. MTb-epitope-immunogenicity-prediction MTb-epitope-immunogenicity-prediction Public

    An ML-based immunogenicity predictor for T-cell epitopes of Mycobacterium Tuberculosis. It is purely based on amino acid sequences of epitope. Used Physicochemical descriptors and Amino Acid compos…

    Python

  3. multi-agent-pr-reviewer multi-agent-pr-reviewer Public

    Multi-agent AI GitHub PR reviewer with security, architecture, and code quality analysis using LLM orchestration and structured review aggregation.

    Python

  4. stroke-prediction stroke-prediction Public

    Stroke Risk Prediction system featuring an optimized XGBoost pipeline and a real-time Streamlit dashboard. The model focuses on clinical reliability by prioritizing Recall (57%) and removing subjec…

    Jupyter Notebook