David Kroell
About David Kroell
David Kroell is a Machine Learning and Software Engineer specializing in Reinforcement Learning and Markov Decision Processes. He has over five years of experience in data science and engineering, currently working at Expedition Technology Inc in Herndon, Virginia.
Work at Expedition Technology
David Kroell has been employed at Expedition Technology Inc since 2021, serving as a Machine Learning and Software Engineer. His role involves applying advanced machine learning techniques to solve complex problems. He operates within a high-energy team environment, which fosters collaboration and innovation in data science and engineering. His contributions to the company align with its focus on leveraging technology to enhance operational efficiency and effectiveness.
Previous Experience at Lockheed Martin
Before joining Expedition Technology, David Kroell worked at Lockheed Martin from 2016 to 2021 as a Software Engineer. During his five years at the company, he developed skills in software development and engineering practices. His experience at Lockheed Martin contributed to his technical expertise and understanding of complex systems, which he applies in his current role.
Education and Expertise
David Kroell holds a Bachelor of Science in Computer Science and Engineering from Christopher Newport University, where he studied from 2014 to 2018. He furthered his education by obtaining a Master of Science in Computer Science from the Georgia Institute of Technology, completing his studies from 2019 to 2022. His academic background provides a strong foundation in computational thinking and engineering principles, with a specialization in reinforcement learning and Markov Decision Processes.
Background in Software Engineering
David Kroell began his career in software engineering at Jefferson Lab, where he worked for four months in 2016. This initial experience laid the groundwork for his subsequent roles in the industry. Over the years, he has accumulated over five years of experience in the technical domain, focusing on data science and engineering. His commitment to solving complex problems is evident in his work and ongoing professional development.