Zaid G
About Zaid G
Zaid G is a Machine Learning Engineer with a Master's degree in Electrical and Computer Engineering from the University of Washington. He specializes in interactive and reinforcement learning, focusing on developing machine learning models to enhance user engagement.
Current Role at MINDBODY
Zaid G currently serves as a Machine Learning Engineer at MINDBODY, a position he has held since 2020. Based in San Diego, he focuses on developing machine learning models that enhance user engagement through interactive systems. His work contributes to the company's mission of improving user interaction and decision-making processes.
Education and Expertise
Zaid G earned a Master's degree in Electrical and Computer Engineering from the University of Washington, where he studied from 2017 to 2019. Prior to that, he obtained a Bachelor of Science in Electrical Engineering with a Computer Engineering Track from Ohio University, completing his studies from 2013 to 2017. His academic background supports his specialization in interactive and reinforcement learning within the machine learning field.
Research Experience
Zaid G has held multiple research assistant positions during his academic career. He worked at the University of Washington from 2017 to 2019 for two years, contributing to various research projects. He also served as a research assistant at Ohio University for a total of ten months, including a two-month stint in 2016. His research experience has provided him with a solid foundation in machine learning applications.
Internship Experience
Zaid G has gained practical experience through several internships. He worked as a Robotics Research Engineering Intern at TerraClear Inc for four months in 2019, where he applied his engineering skills. Additionally, he interned at Nationwide Financial as a Software Development Intern for three months in 2017. These internships have contributed to his technical proficiency in software and robotics.
Machine Learning Projects
Zaid G has been involved in various machine learning projects that emphasize enhancing user interaction and decision-making processes. His expertise in developing machine learning models is geared towards improving user engagement through interactive systems, showcasing his commitment to advancing the field of machine learning.