John Kinnebrew
About John Kinnebrew
John Kinnebrew is a Machine Learning Engineer with a Ph.D. in Computer Science from Vanderbilt University. He has extensive experience in research, having worked at various institutions including Bridj and Lockheed Martin, and focuses on coordination in multi-agent systems.
Work at mabl
John Kinnebrew has been employed at mabl as a Machine Learning Engineer since 2017. In this role, he applies his expertise in machine learning to develop solutions that enhance software testing and quality assurance processes. His work focuses on integrating AI-driven methodologies to improve the efficiency and effectiveness of automated testing frameworks.
Education and Expertise
John Kinnebrew holds a Doctor of Philosophy (Ph.D.) in Computer Science from Vanderbilt University, where he studied from 2007 to 2010. He also earned a Master of Science (M.S.) in Computer Science from Vanderbilt University from 2005 to 2007. Additionally, he completed a Bachelor of Arts (B.A.) in Computer Science at Harvard University from 1997 to 2001. His educational background provides a strong foundation in machine learning and artificial intelligence.
Background
Before joining mabl, John Kinnebrew held several positions in research and development. He worked as a Research Scientist at the Institute for Software Integrated Systems, Vanderbilt University, from 2013 to 2015, and at Bridj from 2015 to 2017. He also served as a Graduate Research Assistant at Vanderbilt University from 2005 to 2010, contributing to various projects in machine learning and intelligent systems.
Research Interests
John Kinnebrew's research interests include coordination in multi-agent systems. This area focuses on designing systems where multiple intelligent agents can interact and collaborate effectively. His work has involved developing intelligent pedagogical agents and machine learning techniques to model learning behaviors, such as metacognition and self-regulated learning strategies.
Previous Experience
John Kinnebrew has a diverse background in research roles. He worked as a Research Intern at Lockheed Martin Advanced Technology Center in 2007 and at Lockheed Martin Advanced Technology Laboratories in 2006. His experience also includes a position as a Research Associate at the Institute for Software Integrated Systems, Vanderbilt University, from 2010 to 2013, where he continued to advance his research in machine learning applications.