Ashwini Rajasekhar
About Ashwini Rajasekhar
Ashwini Rajasekhar is a Computer Vision Engineer I at Wobot.ai with expertise in multi-modal machine learning and generative adversarial networks. She holds a Master's degree in Electrical and Computer Engineering from Georgia Institute of Technology and a Bachelor's degree in Electronics and Communication Engineering from Vellore Institute of Technology.
Work at Wobot AI
Ashwini Rajasekhar currently holds the position of Computer Vision Engineer I at Wobot.ai, a role she began in 2023. Her responsibilities include applying her skills in multi-modal machine learning and implementing generative adversarial networks for machine vision applications. Prior to this role, she interned at Wobot.ai as a Computer Vision Intern for four months in 2023, where she gained practical experience in the field.
Education and Expertise
Ashwini Rajasekhar earned her Bachelor of Technology in Electronics and Communication Engineering from Vellore Institute of Technology, completing her studies from 2015 to 2019. She further advanced her education by obtaining a Master of Science in Electrical and Computer Engineering from Georgia Institute of Technology, where she studied from 2019 to 2023. Her academic background supports her expertise in multi-modal machine learning and generative adversarial networks.
Background
Before her current role, Ashwini gained valuable experience through internships. She worked as an Engineering Intern at Saankhya Labs Pvt. Ltd. for four months in 2018, and later at Videonetics Technology Pvt Ltd. for two months in 2020. These internships provided her with foundational skills in engineering and computer vision, contributing to her professional development.
Technical Skills
Ashwini Rajasekhar possesses technical skills in multi-modal machine learning and cross-camera re-identification techniques. Her work focuses on enhancing security and surveillance systems through advanced machine vision applications. She has a strong foundation in implementing generative adversarial networks, which are critical for her role in computer vision.