Holographic cameras can provide more realistic images than ordinary cameras thanks to their ability to acquire 3D information about objects. However, existing holographic cameras use interferometers that measure the wavelength and refraction of light through the interference of light waves, which makes them complex and sensitive to their surrounding environment. On August 23, a KAIST research team led by Professor YongKeun Park from the Department of Physics announced a new leap forward in 3D
2023-09-05[ From left, Ph.D. candidates See-On Park and Hakcheon Jeong, along with Master's student Jong-Yong Park and Professor Shinhyun Choi ] See-On Park, Hakcheon Jeong, Jong-Yong Park - a team of researchers under the leadership of Professor Shinhyun Choi of the School of Electrical Engineering, developed a highly reliable variable resistor (memristor) array that simulates the behavior of neurons using a metal oxide layer with an oxygen concentration gradient, and published their work in Nature
2022-11-01- The first images of mid-infrared optical waves compressed 1,000 times captured using a highly sensitive scattering-type scanning near-field optical microscope. - KAIST researchers and their collaborators at home and abroad have successfully demonstrated a new methodology for direct near-field optical imaging of acoustic graphene plasmon fields. This strategy will provide a breakthrough for the practical applications of acoustic graphene plasmon platforms in next-generation, high-perfor
2021-03-16- Researchers reports a new strategy for the microbial production of multiple short-chain primary amines via retrobiosynthesis. - KAIST metabolic engineers presented the bio-based production of multiple short-chain primary amines that have a wide range of applications in chemical industries for the first time. The research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering designed the novel biosynthetic pathways for short-chain primary
2021-01-14A deep-learning powered single-strained electronic skin sensor can capture human motion from a distance. The single strain sensor placed on the wrist decodes complex five-finger motions in real time with a virtual 3D hand that mirrors the original motions. The deep neural network boosted by rapid situation learning (RSL) ensures stable operation regardless of its position on the surface of the skin. Conventional approaches require many sensor networks that cover the entire curvilinear surfac
2020-06-10