- AI-Driven Hydrogen Technology Innovation Center (hydro*studio)
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AI-Driven Hydrogen Technology Innovation Center (hydro*studio)
KEYWORDKeyword
OBJECTIVE Objectives
· To overcome the limitations of conventional hydrogen value-chain technologies through integration with multi-scale AI, while strengthening global collaboration and linkage
· To develop nationally strategic talent with integrated expertise in AI and hydrogen science and technology (S&T) for global leadership
INTRODUCTION Director's Profile
● Professor, Department of Energy and Chemical Engineering, UNIST
● Director, Institute for Next-Generation Hydrogen Convergence Technology, UNIST
● h-index 58 | Citation > 12k
He has published over 160 SCI-indexed papers in energy storage and conversion, focusing on electrocatalysis and electrochemical systems. His research emphasizes not only catalyst materials but also the surrounding reaction environment, with particular expertise in multi-activation strategies.
In the field of AI, he developed an artificial neural network-based model at LG Chem (as early as 2007) to predict long-term cycling performance from early-cycle data, which was successfully applied in industrial practice.
He serves as an advisor to the President of UNIST on hydrogen initiatives and actively engages in policy and regional collaboration, including representing UNIST in cooperation with the Ulsan Metropolitan Government to support the hydrogen industry ecosystem.
Based on his academic, industrial, and policy experience, he leads the InnoCORE hydro.studio research center, aiming to drive AI-powered innovation in hydrogen technologies and establish a global research hub.
IMPACT Impact
Technical
· Significantly enhance the speed and efficiency of hydrogen technology development
· Drive next-generation hydrogen technology innovation through integrated design of materials, devices, and processes
Industrial
· Establish a cost-competitive clean hydrogen supply chain
· Promote the transition of the existing petrochemical industry toward low-carbon operations
Talent Development
· Foster next-generation global research leaders with interdisciplinary expertise in both AI and hydrogen science and technology
TALENT Ideal Talent
○ Globally oriented interdisiplinary researchers with expertise in AI and hydrogen science and technology
○ AI-driven researchers with strong capabilities in data-driven research
○ Researchers focused on technology development with strong industry linkage