About

Yash Yamsanwar is a highly motivated and skilled Machine Vision Intern at AGCO Corporation, where he is currently working on developing computer vision algorithms to detect carbon organic matter in soil. He is also training deep learning models for image classification using Pytorch, Numpy, Pandas, Sci-kit learn, regex, and TensorFlow. Yash is a Research Assistant at the Research and Advance Engineering Team at AGCO-UIUC and has relevant experience of 1.52 years. Before joining AGCO Corporation, Yash worked as a Software Development Engineer at Willis Towers Watson, where he developed a web application that acted as an interface for managing existing products and their services. He also automated many tasks such as associating a single service with multiple products. Yash used .NET Core framework particularly Razor pages, C#, SQL, and Azure to deploy this. He simultaneously handled DevOps tasks like creating CI/CD pipelines, creating APIs, and deployments for the products. Yash has also worked as a Cloud Engineer at Searce Inc, where he integrated and automated internal tools for performance improvement by writing cloud functions in GCP using Python. He migrated on-premise applications to AWS, which helped customers reduce their recurring cloud costs by 30%. Yash has a Bachelor of Engineering degree in Computer Science from Savitribai Phule Pune University and is currently pursuing an MS in Machine Learning and Systems from the University of Illinois, which he expects to complete in December 2023. He has also completed his middle school/high school education from Z.P High School, Pandharkawada. Yash's technical skills include research scientist, computer vision, edge detection, deep learning, SQL, TensorFlow, Pandas, Pytorch, software engineer, CI/CD, DevOps, Azure, web, AWS, Python, and GCP. He is a highly motivated individual who is always eager to learn new skills and technologies.