About

Rajagopala Rao Srinadhuni is a highly experienced Machine Learning Engineer with over 6 years of relevant experience in the field. He is skilled in Deep Learning and Computer Vision and is comfortable working with both C++ and Python. Rajagopala has worked with various networks in Caffe, Pytorch, Tensorflow, and Darknet, and has extensive experience managing data and utilizing augmentation to improve network performance. Currently working with Vehant Technologies, Rajagopala is part of the original team developing Video Analytics solutions for Smart City-based use cases using DL and CV. He is experienced in Quantization and model conversion to suit performance and business needs. Prior to this, he worked in the STG group at Infosys, where he developed a couple of POC-based projects in Instance Segmentation. He also had the opportunity to work on Semantic Segmentation and Collision Avoidance systems with regard to ADAS technologies. Rajagopala is a self-learner and is constantly updating his perspective to crack new challenges. He completed his NanoDegree in Self-Driving Car from Udacity in 2018 and holds a Bachelor of Technology degree in Computer Science from Guru Gobind Singh Indraprastha University. Rajagopala's technical skills include ML, Deep Learning, Computer Vision, Python, Tensorflow, Pytorch, and Software Engineering. With his extensive experience and technical skills, Rajagopala is a valuable asset to any organization looking to develop cutting-edge Machine Learning solutions.