Building intelligent solutions with Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI.
Built using RAG, LangChain, FAISS, Ollama (Llama 3), Streamlit, and Sentence Transformers.
🔗 GitHub Repository: https://github.com/sanjaikmca/DocMind-AI
🎓 MCA Graduate (CGPA 9.46) from Hindustan Institute of Technology & Science, Chennai
📄 IEEE Published Researcher in Brain Tumor Segmentation using Deep U-Net
🎤 IEEE Conference Presenter – ICCRTEE 2026
🏆 Academic Rank Holder
💡 Passionate about Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Data Engineering, and Data Analytics.
🌱 Currently learning
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- LangChain
- LlamaIndex
- Hugging Face
- AI Agents
- MLOps
- Data Engineering
🎯 Looking for opportunities as a
- Machine Learning Engineer
- AI Engineer
- Data Engineer
Libraries
- Scikit-learn
- Keras
- Pandas
- NumPy
- Matplotlib
- LangChain
- LlamaIndex
- Hugging Face Transformers
- OpenAI API
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- ETL Pipelines
- Data Ingestion
- Data Wrangling
- MySQL
- Power BI
- MS Excel
Jupyter Notebook • Google Colab
- Built an AI-powered Multi-Document Question Answering System using Retrieval-Augmented Generation (RAG)
- Supports PDF, DOCX, TXT, and Markdown documents
- Semantic search using FAISS Vector Store
- Llama 3 (Ollama) for context-aware answer generation
- LangChain-based retrieval pipeline with source citations
- Interactive Streamlit interface with document preview
- Tech Stack: Python, Streamlit, LangChain, FAISS, Ollama, Llama 3, Sentence Transformers
🔗 GitHub: https://github.com/sanjaikmca/DocMind-AI
- IEEE Published Research Paper
- Deep U-Net architecture for MRI brain tumor segmentation
- Achieved high Dice Score and IoU performance
- Optimized using TensorFlow, OpenCV, and Keras
- Tech Stack: Python, TensorFlow, Keras, OpenCV
🔗 GitHub: https://github.com/sanjaikmca/Brain-MRI-Segmentation
- Medical image classification using MobileNet Transfer Learning
- Applied Grad-CAM for model interpretability
- Fine-tuned pretrained CNN for improved accuracy
- Tech Stack: Python, TensorFlow, MobileNet, OpenCV
🔗 GitHub: https://github.com/sanjaikmca/Research-Intern---X-ray-at-HITS
- Automatic image caption generation using CNN-LSTM architecture
- VGG16 feature extraction with LSTM-based text generation
- Trained on the MS COCO dataset
- Tech Stack: Python, TensorFlow, VGG16, LSTM, NLP
🔗 GitHub: https://github.com/sanjaikmca/Academic-Project-Image-Captioning
🥇 MCA First Rank Holder
🥈 MCA Second Rank Holder
📄 IEEE Published Researcher
🎤 IEEE Conference Presenter
🏅 Introduction to Algorithms and Analysis – NPTEL (Elite)
☁️ Cloud Computing – NPTEL
💬 Enhancing Soft Skills and Personality – NPTEL (Elite)
🍃 MongoDB Basics for Students
🤖 AI Research Internship
💻 Intellithon'25 – National Hackathon
📊 SQL & Cloud Services Workshop
🌱 Currently exploring
- AI Agents
- LangGraph
- MLOps
- Data Engineering
- FastAPI
- MLflow
✅ Build Production-Ready AI Applications
✅ Master LLMs & RAG
✅ Learn Data Engineering
✅ Learn MLOps
✅ Contribute to Open Source
✅ Publish More Research Papers
"Curiosity drives learning, consistency builds expertise, and every project is a step toward creating impactful AI solutions."