LG Energy Solution said Monday it held its Battery Tech Conference in Chicago, stepping up efforts to recruit top global research talent in next-generation battery technologies, energy storage systems and artificial intelligence.
As the company’s key platform for recruitment, the BTC was attended by more than 40 graduate students, doctoral candidates and researchers from leading North American universities and research institutions, including the Massachusetts Institute of Technology, Stanford University, University of California, Berkeley, University of Chicago and Argonne National Laboratory.
LG Energy Solution CEO and President Kim Dong-myung, along with Chief Digital Officer Lee Jin-kyu, Chief Human Resources Officer Kim Ki-soo and senior executives overseeing advanced cell development, ESS, AI and big data technologies, participated in the event.
During a session, Kim shared his career journey from materials engineering researcher to chief executive and took part in an open Q&A with participants.
“I want LG Energy Solution to become an energy platform company providing total solutions rather than remaining only as a battery manufacturer,” Kim said, underscoring the key role of R&D talent in shaping the company’s future.
The conference also featured presentations from LG Energy Solution’s key research organizations, including its technology and digital divisions, highlighting the company’s technological prowess and future growth strategy.
Lee Sang-young, a chemical and biological engineering professor of Yonsei University, was invited to speak about the latest trends in battery research.
Industry insiders say LG Energy Solution’s focus on physical AI talent in particular likely signals its commitment to the emerging humanoid robotics as well as advanced manufacturing capabilities.
When integrated with physical AI — which enables humanoid robots to understand and interact with real-world environments — the company’s next-generation Battery Management Total Solution could monitor how real-world industrial settings, such as lifting heavy objects or operating in extreme temperatures, impact battery health in real time, providing more accurate predictions of performance, degradation and lifespan.
Physical AI-driven smart factory solutions could also help boost production yields.
Using digital twin technology to create virtual replicas of manufacturing facilities, engineers can simulate production processes, identify potential defects and optimize key parameters such as electrode coating before large-scale operations begin. This can significantly shorten plant ramp-up periods and reduce costly production losses. hyejin2@heraldcorp.com