Nitin Ravat

Innovative Data Scientist with extensive experience in machine learning, deep learning and computer vision, specializing in AI-driven IoT solutions for enhanced cattle management. Skilled in Python and statistical analysis, delivering impactful insights through collaborative teamwork. Proven track record of developing efficient solutions in fast-paced environments.

• Developed AI-Driven IoT Solutions- Designed and deployed LiveStock Heat detection and health monitoring system using machine learning algorithms & statistics, enabling real-time insights for farmers and improving cattle management efficiency.
• Developed a generalized YOLOv11-based vision model for automated milk parameter extraction, allowing machine calibration through simple image capture, streamlining dairy operations.
• Created application for measuring cattle body traits from images using YOLOv11 and PoseNet, converting pixel-based measurements into centimeter values during prediction.
• Implemented data reduction techniques to optimize IoT device battery life, reducing operational costs significantly.
• Medical VQA : This project combines NLP and computer vision, using BERT and vision transformers to interpret and answer complex queries from medical images like X-rays, MRIs, and CT scans.
• Plant disease classification & localization : Developed a plant disease classification and localization solution using a hybrid approach with pretrained ResNet-50 and YOLOv8 models, achieving a classification accuracy of 97% and an IoU score of 95%.
• https://github.com/NitinRavat2000/Plant-DiseaseDetection

• Increased Product Accuracy: Enhanced AI product accuracy by 21% at Prompt Dairy Tech by using the hybrid machine learning algorithms.
• Enhanced Battery Life: Developed and implemented a data preprocessing method that extended the AI product's battery life from 1.5 years to over 3 years.