Sravani Teeparthi
About Sravani Teeparthi
Sravani Teeparthi is a Data Science and Machine Learning Intern with a Master's degree in Computer Engineering from the University of New Mexico. She has experience in developing data-driven solutions and has worked on various projects related to demographics estimation, cyber-attack difficulty calculation, and fraud detection.
Current Role at RS21
Sravani Teeparthi serves as a Data Science and Machine Learning Intern at RS21. In this role, she develops solutions tailored to client-specific problems using data science and statistical techniques. Her internship focuses on applying machine learning methodologies to real-world challenges, enhancing her practical experience in the field.
Education and Expertise
Sravani Teeparthi holds a Master's degree in Computer Engineering from the University of New Mexico School of Engineering, where she studied from 2018 to 2021. Prior to this, she earned a Bachelor of Technology (B.Tech.) in Electronics and Communications Engineering from Pragati Engineering College, completing her studies from 2011 to 2015. She also achieved an Intermediate certification with a score of 9.8/10.0 at Sri Chaitanya Junior College from 2009 to 2011.
Professional Background
Sravani Teeparthi has a diverse professional background. She worked as an Associate Software Engineer at Infor from 2015 to 2017 in Hyderabad, Telangana, India. Following this, she transitioned to a research role at The University of New Mexico, where she has been a Research Assistant since 2018. Her experience spans various aspects of data science and software engineering.
Projects and Contributions
During her internship at RS21, Sravani Teeparthi has worked on several projects that include demographics estimation, cyber-attack difficulty calculation, and fraud detection. These projects demonstrate her ability to apply data science techniques to address complex issues and contribute to meaningful outcomes.