Akhil Bharadwaj Mateti
About Akhil Bharadwaj Mateti
Akhil Bharadwaj Mateti is a Technical Support Assistant II at The George Washington University, where he provides technical assistance and collaborates with the IT team to implement IT policies. He holds a Bachelor's degree in Computer Science from Vellore Institute of Technology and a Master's degree in Data Science from The George Washington University.
Work at The George Washington University
Currently, Akhil Bharadwaj Mateti serves as a Technical Support Assistant - II at The George Washington University, a position he has held since 2023. In this role, he collaborates with the IT team to implement and maintain IT policies and procedures. He provides technical assistance and troubleshooting support using various software and hardware systems. During his tenure, he contributed to achieving a 60% first meeting resolution rate and a 75% on-time total resolution rate in the walk-in support team.
Education and Expertise
Akhil Bharadwaj Mateti earned his Bachelor's degree in Computer Science from Vellore Institute of Technology, completing his studies from 2015 to 2019. He furthered his education at The George Washington University, where he pursued a Master's degree in Data Science from 2022 to 2024. This academic background has equipped him with a strong foundation in technical skills and data analysis.
Background in IT and Data Science
Prior to his current role, Akhil worked as a Project Engineer at Wipro Limited from 2019 to 2022, where he developed and deployed machine learning models for autonomous vehicles. He also gained experience as a Data Science Researcher at Data Science for Sustainable Development for three months in 2024. His early career included an internship at gnani.ai in 2018, which provided him with initial exposure to the tech industry.
Professional Experience at Wipro Limited
At Wipro Limited, Akhil Bharadwaj Mateti held the position of Project Engineer for three years. During this time, he focused on developing and deploying machine learning models specifically for autonomous vehicles. This experience contributed to his technical expertise and understanding of machine learning applications in real-world scenarios.