Work Experience

Software Engineer (Tech Lead) at Rosa Tech Pvt Ltd

Leading the development of robotic automation and AI-driven testing systems, improving efficiency and performance.

  • Developed an automated rebar detection and tensile strength testing system using computer vision, CNNs, and robotic automation, boosting efficiency by 50% and contributing to 15% of company revenue.
  • Designed real-time data processing architectures, ensuring response times under 0.01 milliseconds.
  • Engineered a Python library for IMU calibration with I2C integration for sensor precision.
  • Built 10+ high-impact microservices improving backend operations and data processing efficiency.

Projects

Automated Rebar Strength Testing

Developed a machine learning and computer vision-based system for rebar detection and tensile strength analysis.

  • Designed and deployed an AI-powered robotic pick-and-place system, increasing testing efficiency by 50%.
  • Implemented CNN-based computer vision models for rebar detection and strength analysis.
  • Utilized Python, TensorFlow, OpenCV, and robotic control frameworks for automation.

SimpliQ - Question Similarity Predictor

Built an NLP-based model for predicting question similarity using the Quora dataset.

  • Developed a model with 80.14% accuracy using advanced NLP techniques.
  • Implemented feature extraction pipelines and optimized performance using Random Forest.
  • Created a user-friendly Streamlit-based web app for real-time predictions.

Football Analysis System

Designed an AI-driven system for real-time football player tracking and analysis.

  • Integrated YOLOv8 for detecting players, referees, and footballs in real-time.
  • Used KMeans clustering for player segmentation and optical flow for tracking movements.
  • Applied OpenCV perspective transformation to convert pixel data into real-world player metrics.