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Discover not only Research Findings and event news, but also the diverse facets of UNIST presented by reporters and writers.

UNIST News

Faculty Honors & Awards: From Human Senses to Theoretical Physics

Two UNIST professors have been honored for breakthroughs that bridge human experience and fundamental science.

  • Community
  • JooHyeon Heo
  • 2026.04.30
  • 288

Faculty Honors & Awards: From Human Senses to Theoretical Physics

Across disciplines ranging from human‑inspired engineering to the frontiers of theoretical physics, UNIST scholars are earning distinction for work that broadens the reach of scientific understanding and innovation.

   


    

Engineering Human Senses | Professor Hyunhyub Ko Honored with Presidential Commendation


Professor Hyunhyub Ko, Head of the School of Energy and Chemical Engineering, has received a Presidential Commendation at the commemorative ceremony of the 2026 Science and ICT Day for his groundbreaking work in bio-inspired electronic systems. 


Professor Ko's research translates human sensory functions—touch, taste, and hearing—into flexible electronic platforms. His team developed electronic skin capable of detecting pressure, fine texture, and temperature, as well as artificial sensory systems, such as electronic tongues and cochlea-inspired acoustic sensors. They also introduced ultrathin, skin-attachable speakers and microphones that expand possibilities for wearable interfaces. 


Beyond devices, his lab designs functional materials inspired by nature, including MXene-based nanochannels and temperature-responsive adhesives. These technologies are regarded as enabling components for next-generation wearable healthcare, tactile robotics, immersive AR/VR, and the Internet of Things (IoTs). 


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AI Meets Fundamental Physics | Professor Rak-Kyeong Seong Wins 2026 Baekcheon Physics Award 


Professor Rak-Kyeong Seong from the Department of Mathematical Sciences has received the 2026 Baekcheon Physics Award from the Korean Physical Society (KPS), recognizing his pioneering contributions to theoretical particle physics. 


Professor Seong introduced machine learning to tackle non-perturbative problems in quantum field theory and string theory—long viewed as analytically intractable. His early work, using AI to predict the complex geometry of Calabi–Yau manifolds remain a cornerstone in bridging data science and mathematical physics. 


Invited talks at major international forums—including the University of Cambridge, the California Institute of Technology (Caltech), and Kyoto University—underscore the global impact of his research. His work embodies a new paradigm in fundamental science, where the boundaries between physics and artificial intelligence (AI) grow increasingly porous. 


Read More at UNIST News