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LG Energy Solution’s New Chief Data Officer to Lead Digital Transformation of Battery Manufacturing Unit

SEOUL, February 21, 2022 – LG Energy Solution (LGES; KRX: 373220) today announced it welcomed Dr. Peter Kyungsuk Pyun as the newly created position of Chief Data Officer, CDO, as the company ramps up efforts to digitally transform its entire global facilities into data-centric operations.

Before joining LGES, Pyun worked at Nvidia Corporation, Silicon Valley headquarters, as one of five principal data scientists. Widely known as a skilled individual in the manufacturing field of global data science, Pyun brings over 20 years of expertise in machine learning and extensive global experience.

At Nvidia, Pyun led multiple projects as a lead architect in the field of Autonomous Vehicle, Industrial AI and Cloud AI. His successful leadership of an industrial AI team on defect inspection for manufacturing products is now a part of an AI curriculum at Massachusetts Institute of Technology.

Pyun received MS and PhD degrees in Electrical Engineering from Stanford University focusing on Machine Learning and Computer Vision. He received his BS in Control and Instrumentation Engineering from Seoul National University with great distinction.

“Dr. Pyun has gained global perspective and experience in operating and developing solutions for AI-based monitoring in smart manufacturing. We are thrilled to have him as Dr. Pyun is the right fit who is capable of accelerating efforts to turn LGES’s global battery manufacturing facilities into smart factories,” LG Energy Solution said in a statement.

“Based on his accumulated experience in world-renowned firms, we expect LGES to take a further step forward in battery manufacturing processes by utilizing AI and big-data technology,” added the company spokesperson.

LG Energy Solution had earlier announced plans to transform all its global manufacturing facilities into smart factories, to better improve battery manufacturing process. By converting into smart factories, LGES believes it can make data-driven decisions, enable automatic calibration and reduce potential battery-related issues. The company is confident it can also improve its profitability by yielding higher value and cutting quality-related costs.

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