Vedu

Result driven Computer Engineer with expertise in machine learning, real-time object detection, pose estimation, and motion capture. Skilled in building end-to-end pipelines, including model training, GPU-accelerated inference, and deployment. Experienced with YOLO-based architectures and integrating vision systems into applications.

Python Developer Intern at Nilee Games and Future Technologies (2025-09 – 2026-03)

Developed real-time computer vision and motion capture systems

• Engineered a real-time ball impact detection system using a custom YOLO model, achieving 300+ FPS with TensorRT-optimized GPU inference.
• Trained and fine-tuned a YOLO-based object detection model for ball tracking, achieving ~95–99% accuracy under controlled conditions.
• Developed a full-body motion capture system tracking 33 skeletal landmarks, delivering ~90% accuracy for Unity avatar mirroring.
• Optimized Python-to-Unity communication latency to under 20 ms using MediaPipe-based streaming for real-time interaction.
• Designed gesture-based control systems replacing physical inputs, enabling 4 game actions with near-zero false triggers.

10th – Pria School (2019)

12th – HOCL pillai (2019 – 2021)

Bachelor's in Computer Engineering in Computer Engineering – Vi-MEET, University of Mumbai (2021 – 2025)