About

Vaibhav Vemula is a highly ambitious and energetic individual with a mature and responsible approach to his work. He is a programming and technology enthusiast with a strong interest in deep learning, object detection, and blockchain. Vaibhav is currently working as an R&D intern at Bosch, where he is involved in developing robust object detection and segmentation models using ensemble learning techniques for the autonomous driving domain. He is also responsible for constructing ML pipelines that use ensemble models for automated deployment, testing, validation, and training. Vaibhav is adept at creating visualizations and outcome reports to analyze and gain insights into the numerous models employed in the pipeline. Prior to his current role, Vaibhav worked as a project intern at IEEE Computer Society Bangalore Chapter, where he worked on a project titled "Zemoo - an e-commerce platform based on the blockchain." He developed an NFT-based warranty system that auto-decays after the warranty period of the product purchased to verify the authenticity of the product. Vaibhav also created a community forum where content creators can upload valuable material and be compensated by the product's retailer. As an undergraduate student researcher at PES University, Vaibhav worked on a project titled "Smart City Planning" under the guidance of Dr. Natarajan S. This project aimed to build an application that produces an urban city plan for the region of interest specified. Vaibhav developed a system that takes an area (location/coordinate) as input and generates the required data analysis report for it. The solution provided smart data analysis, which was in accordance with creating a smart and sustainable city. Vaibhav is skilled in NFT, blockchain, object detection, deep learning, and ML. He has relevant experience of 0.77 years and is always eager to learn and explore new technologies. Vaibhav's portfolio can be found on vaibhavvemula.me.