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About

Motivated and detail-oriented Computer Science graduate with strong foundations in Data Science, Machine Learning, and Artificial Intelligence. Skilled in Python, SQL, RAG, LangChain, Vector Databases, Deep Learning and Data Visualization.

Experience2

  1. Data Science Intern

    Oct. 2025 — March 2026

    BDreamz Global Solutions Pvt. Ltd.

    Implemented end-to-end data science pipelines including data preprocessing, feature engineering, model training, and evaluation. Applied machine learning algorithms such as KNN, Decision Trees, and Random Forest for predictive modeling. Optimized model performance using techniques like hyperparameter tuning and cross-validation.

  2. Data Science Intern

    March 2026 — April 2026

    Sysslan IT Solutions

    Performed exploratory data analysis (EDA) to identify trends and correlations in datasets. Developed machine learning models using Scikit-learn including Linear Regression and Random Forest. Evaluated models using MSE, RMSE and r2 score to improve prediction performance. Built data visualizations and dashboards using Power BI and Matplotlib to communicate insights.

Projects3

  • Docx-Based Question Answering System using RAG

    Developed an intelligent document retrieval system using LangChain, FAISS, and Large Language Models. Implemented semantic search using Hugging Face embeddings for accurate information retrieval, improving retrieval relevance by 30–40%. Created an interactive web interface using Streamlit for real-time document upload and querying.

    • Python
    • LangChain
    • FAISS
    • Hugging Face
    • RAG
    • Streamlit
    • NLP
    • Vector Databases

  • Real-Time Video Analytics System using YOLO and Object Tracking

    Built a scalable real-time video analytics system using YOLO and tracking algorithms for object identification across frames. Implemented trajectory tracking and event detection (line-crossing) to analyze object movement patterns in video streams. Achieved real-time performance with FPS monitoring and optimized inference pipeline for low-latency video processing.

    • YOLOv8
    • CNN
    • Python
    • NumPy
    • TensorFlow
    • OpenCV

  • Heart Disease Prediction

    Performed exploratory data analysis to identify relationships between medical attributes. Built classification models including Logistic Regression and Random Forest to predict disease risk. Achieved ~90% accuracy on test data.

    • Python
    • Scikit-learn
    • Pandas

Education2

  • Bachelor of Technology

    2021 — 2025

    THDC Institute of Hydropower Engineering and Technology

    Computer Science

  • CBSE Class XII

    2019 — 2020

    DON BOSCO SEN. SEC. SCHOOL