Developed:Environmental Health and Safety System: Designed and implemented an AI-based Environmental Health and Safety system for steel mill monitoring. Real-time anomaly detection on Jetson Orin Nano significantly lowered incidents.Collaborated: Collaborated with experts to ensure compliance and increased efficiency of the system. Presented project success to stakeholders, facilitating industry adoption.Innovated:Sugarcane Variety Identification System: Developed a computer vision-based system for sugarcane variety identification. Improved accuracy by 20% with a curated dataset and ML models achieving 90% accuracy. Reduced identification time by 40% compared to manual methods.

Communication: Selected from over 4,500 applicants for an intensive 3-month Fellowship funded by Stanford University, following a competitive written application and interview process.Skills Development: Invested 150 hours in honing business skills (e.g., communication, leadership, problem-solving, teamwork) to make a profound impact in the workplace.

Collaborated: Worked on a resume ranker project with the development team, involving data collection, annotation, and text data preprocessing to enhance candidate matching accuracy.Contributed: Played a key role in project monitoring construction workers, ensuring safety protocol adherence. Utilized TAO Toolkit to train Yolov4 for object detection and deployed it on Jetson Nano using DeepStream.

Fabric Defect Detection: Implemented a fabric defect detection system using CNN and OpenCV, resulting in a 50% accuracy improvement compared to previous methods.Implemented: Deployed a warehouse monitoring system encompassing object detection, worker counting, and vehicle entranceway monitoring, enhancing operational efficiency and safety.

Object Detection: Developed an object detector using Yolo and OpenCV, identifying 80 classes with an average precision of 0.90.Innovated: Created image color detector, social distancing detector, and real-time face mask detector, ensuring adherence to safety protocols.Implemented: Deployed a real-time traffic sign classifier, accurately recognizing traffic signs with a precision rate of 95%.

Data Analysis: Conducted Exploratory Data Analysis (EDA) on the "SampleSuperstore" dataset, identifying weak areas for profit improvement and providing actionable recommendations.Machine Learning: Created a student percentage detector with an achieved R2 score of 0.94 based on study hours, demonstrating proficiency in predictive modeling.Visualization: Predicted the optimal number of clusters from the Iris Dataset and visually represented the results for easy interpretation, showcasing expertise in data visualization techniques.Research & Analysis: Analyzed the Global Terrorism Dataset, identifying hot zones of terrorism and suggesting security measures for improved safety, highlighting strong research and analytical skills.Sports Analytics: Performed EDA on the Indian Premier League dataset, identifying successful teams, players, and factors contributing to team performance, providing insights for endorsements.