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About

Computer Engineering graduate (CGPA 8.66/10) with hands-on experience in software development and AI/ML. Built and deployed AI and web applications using Python, Java, SQL, React and FastAPI, with deep learning models (UNet + LSTM, YOLOv8), LLM API integration, RAG concepts and REST APIs. Completed three internships, led two four-member team projects, and work comfortably with Git, SQL and NoSQL databases. Quick learner with strong problem-solving skills and clear communication.

Experience3

  1. IoT & AI Developer Intern

    Jan 2026 — Mar 2026

    Core2Web

    Built AI module of LifeXRobo emergency-response robot by training YOLOv8 accident-detection model on Roboflow-labeled dataset for live camera frames. Added a two-stage verification to reduce false alerts and served model via FastAPI backend alongside real-time sensor data using ESP32-CAM.

  2. Software Developer Intern

    Dec 2024 — Feb 2025

    NeuAI

    Developed and tested 8+ RESTful API endpoints with MVC architecture and JWT authentication, integrated with React front end. Improved performance by reducing unnecessary re-renders by 30%.

  3. AI/ML Intern

    Nov 2024 — Dec 2024

    AICTE Virtual Internship Programme

    Built an email classifier on over 1,000 samples comparing Naive Bayes, SVM, and Logistic Regression to achieve over 92% accuracy using Python and Scikit-learn.

Projects3

  • VastuVision - AI-Based 3D Interior Design System

    Led a 4-member team to build and deploy a platform that converts 2D floor plans into 3D layouts using a UNet + LSTM model with 95% accuracy, supplemented by an LLM API for design suggestions, a rule-based scoring engine, and SQL/MongoDB for data storage.

    • PyTorch
    • UNet
    • LSTM
    • React
    • FastAPI
    • SQL
    • MongoDB
    • Docker

  • JuriForge - AI-Driven Legal Management System

    Led a team of 4 to build a JavaFX application featuring an NLP navigation chatbot and an LLM API-integrated chatbot for answering legal queries.

    • Java
    • JavaFX
    • Firebase
    • NLP

  • IPL Win-Probability Prediction System

    Developed a web app that merges and queries IPL data from 2008-2026 using SQL and Pandas, tested 9 classification algorithms with hyperparameter tuning, and deployed an XGBoost model achieving 92% accuracy using FastAPI and Streamlit.

    • Python
    • SQL
    • Pandas
    • Scikit-learn
    • XGBoost
    • FastAPI
    • Streamlit

Education2

  • Bachelor of Engineering

    2022 — 2026

    Sinhgad College of Engineering, Pune (Savitribai Phule Pune University)

    Computer Engineering

  • Higher Secondary Certificate (HSC)

    2022

    Smt. P. K. Kotecha Mahila College, Bhusawal