Eddie (Wonryeol) Yang
About Eddie (Wonryeol) Yang
Eddie (Wonryeol) Yang is a Tech Lead specializing in ML & Data Platforms, focusing on AutoML and MLOps. He has extensive experience in software engineering and machine learning, having worked for notable companies such as LG Electronics, NHN, Oracle, and Sun Microsystems.
Current Role at 42dot
Eddie Yang serves as the Tech Lead for the ML & Data Platform at 42dot, a position he has held since 2020. In this role, he focuses on AutoML, MLOps, and the development of machine learning and data pipelines. His expertise contributes to the advancement of continuous learning systems, particularly for autonomous vehicles and mobility services. Yang's work is pivotal in enhancing the efficiency and effectiveness of machine learning applications within the organization.
Previous Experience in Software Engineering
Eddie Yang has extensive experience in software engineering, having worked at several prominent companies. He spent eight years at LG Electronics in the Mobile Communications division from 2001 to 2009. Following this, he worked at Sun Microsystems for one year and then at Oracle as a Senior Software Engineer from 2011 to 2016. He also served as Lead Software Engineer in the Machine Learning Lab at NHN from 2016 to 2020. His diverse background in software development has equipped him with a robust skill set in various technologies.
Educational Background
Eddie Yang completed his Bachelor's degree in Electronics and Computer Science at Sungkyunkwan University, studying from 1993 to 1999. He furthered his education at the same institution, obtaining a Master's degree in Pattern Recognition, AI, Speech Recognition, Text-to-Speech, and Audio/Speech signal processing from 1999 to 2001. This academic foundation has significantly contributed to his expertise in machine learning and data platforms.
Expertise in Machine Learning and Data Platforms
Eddie Yang specializes in developing and maintaining machine learning and data platforms, particularly in hybrid cloud environments. His focus on AutoML and MLOps reflects his commitment to advancing machine learning technologies. Yang's experience in creating continuous learning systems for autonomous vehicles highlights his contributions to the field of mobility services and intelligent systems.