people
(Professor Poong-Hyun Seong)
Chair Professor Poong-Hyun Seong from the Department of Nuclear & Quantum Engineering was selected as the recipient of the Don Miller Award by the American Nuclear Society.
The award, established in 2009 by the American Nuclear Society in honor of former ANS President Don Miller, is given to an individual or team who has made a significant contribution to the advancement of one or both of the fields of nuclear instrumentation and control of human-machine interfaces through individual or combined activities. The award ceremony will be held on June 10 during the 2019 annual meeting of the ANS in Minneapolis in the US.
Professor Seong is being recognized for his pioneering research and training in the fields of nuclear instrumentation control and human factor engineering at Korea. His research significantly contributed to safety improvements in nuclear power plants and have been recognized worldwide. Professor Seong, a fellow of the ANS, now serves as the first vice chair of the International Nuclear Societies Council and will take up the role of chair in 2021.
Professor Seong said that, “ Korea is one of the most outstanding countries working on research in the fields of nuclear instrumentation control and human factors. KAIST PhDs are teaching at many universities at home and abroad. I look forward this award bringing new hope to our nuclear research and the domestic nuclear industry, which is now in difficult times.”
-
research KAIST Proposes a New Way to Circumvent a Long-time Frustration in Neural Computing
The human brain begins learning through spontaneous random activities even before it receives sensory information from the external world. The technology developed by the KAIST research team enables much faster and more accurate learning when exposed to actual data by pre-learning random information in a brain-mimicking artificial neural network, and is expected to be a breakthrough in the development of brain-based artificial intelligence and neuromorphic computing technology in the future.
2024-10-23 -
research KAIST Develops Janus-like Metasurface Technology that Acts According to the Direction of Light
Metasurface technology is an advanced optical technology that is thinner, lighter, and capable of precisely controlling light through nanometer-sized artificial structures compared to conventional technologies. KAIST researchers have overcome the limitations of existing metasurface technologies and successfully designed a Janus metasurface capable of perfectly controlling asymmetric light transmission. By applying this technology, they also proposed an innovative method to significantly enhance
2024-10-15 -
research Revolutionary 'scLENS' Unveiled to Decode Complex Single-Cell Genomic Data
Unlocking biological information from complex single-cell genomic data has just become easier and more precise, thanks to the innovative 'scLENS' tool developed by the Biomedical Mathematics Group within the IBS Center for Mathematical and Computational Sciences led by Chief Investigator Jae Kyoung Kim, who is also a professor at KAIST. This new finding represents a significant leap forward in the field of single-cell transcriptomics. Single-cell genomic analysis is an advanced technique that m
2024-05-09 -
research Genome Sequencing Unveils Mutational Impacts of Radiation on Mammalian Cells
Recent release of the waste water from Japan's Fukushima nuclear disaster stirred apprehension regarding the health implications of radiation exposure. Classified as a Group 1 carcinogen, ionizing radiation has long been associated with various cancers and genetic disorders, as evidenced by survivors and descendants of atomic bombings and the Chernobyl disaster. Despite much smaller amount, we remain consistently exposed to low levels of radiation in everyday life and medical procedures. Radi
2024-02-15 -
research KAIST-UCSD researchers build an enzyme discovering AI
- A joint research team led by Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering and Bernhard Palsson of UCSD developed ‘DeepECtransformer’, an artificial intelligence that can predict Enzyme Commission (EC) number of proteins. - The AI is tasked to discover new enzymes that have not been discovered yet, which would allow prediction for a total of 5,360 types of Enzyme Commission (EC) numbers - It is expected to be used in the devel
2023-11-24