A study published by Prof. Hee-Tae Jung’s group on the efficient production of renewable energy through the search for optimal bifunctional multimetallic alloy catalysts has shown promising results. The study used a Pareto active learning framework and carbothermal shock method for nanoparticle synthesis to efficiently determine optimal metallic compositions for bifunctional catalysts of up to four component elements for electrocatalytic reactions. The approach can be extended to different catalytic reaction fields and other multifunctional applications....read more
PIM is an abbreviation of Processing In Memory and is a kind of future semiconductor memory architecture. It makes it possible for memory and logic processing to operate together with higher speed and less energy consumption. In this bulletin, the three major activities of PIM-SDRC and its achievements are briefly introduced. The center will carry out key roles in building a PIM IP hub, making the infrastructure design service and relevant IP business, and training competent design manpower....read more
By recording neuronal activity in the hippocampus during memory recall in freely behaving mice, Prof. Han’s group has identified neural activity pattern correlates of memory recall....read more
AAILab, KAIST has developed various deep generative model structures and inference methods to synthesize realistic images through diffusion processes. ...read more
KAIST researchers have developed MARVEL, a fast and agile quadrupedal robot equipped with an Electro-Permanent Magnet (EPM) and a Magneto-Rheological Elastomer (MRE) foot sole that enables it to climb on steel walls and ceilings for efficient and safe inspection and maintenance tasks in various industrial settings....read more
The research project on AI for social good aimed at using AI and Digital technologies to transform maternal healthcare in Bangladesh has recently entered a new phase by working directly with the country’s government agencies. The UNESCAP-APRU-Goolge.org-funded Project aims to strengthen AI Capabilities and Governing Frameworks in Asia and the Pacific. As part of this project, KAIST KPC4IR is collaborating with NUS IPUR to support and accelerate the use of AI in medicine and healthcare in Bangladesh. The expert team is focusing i research and analysis on identifying crucial bottlenecks and gaps that impede the beneficial use of AI. These efforts are aimed at providing the Bangladesh Government with the technological and policy tools to address challenges in Pregnancy Monitoring & health care systems using Artificial Intelligence and digital technologies....read more
Prof. Doh Chang Lee’s group has developed a novel photocatalyst based on ultrathin CdS nanosheets for selective and efficient light-driven conversion of CO2 into CO. Surface engineering at atomic precision on CdS nanosheets enabled spatial separation of the reductive active sites and the oxidative active sites to designated facets. The facet-resolved redox-active sites favored efficient charge separation in the CdS nanosheets under light, leading to two-orders-of-magnitude increase in conversion rate of CO2-to-CO. ...read more
A new algorithm has been developed to generate omnidirectional images to super-resolve a low-resolution 360° image into a high-resolution image with arbitrary projection type via continuous spherical image representation....read more
Prof. Yoon’s group has developed a facile approach for optical physical unclonable function using spontaneous mirror symmetry breaking of molecular self-assembly. ...read more
This UNESCAP-APRU-Goolge.org funded Project Supports the Bangladeshi Government to Address Challenges in Pregnancy Monitoring & Health Care Technologies using Artificial Intelligence (AI). The United Nations ESCAP-APRU-Google.org ‘AI for Social Good’ project team includes Dr. Olivia Jensen, Mr. Nathaniel Tan from the National University of Singapore’s Institute for Public Understanding of Risks (NUS IPUR), and Dr. Cornelius Kalenzi from KAIST KPC4IR as lead researchers to support Bangladesh government in strengthening the maternal care health workforce and achieving SDG 3, which will transform methods of treatment as well as the relationships among health professionals and patients. Dr. Jensen, Mr. Tan, and Dr. Cornelius Kalenzi will address challenges in perceptions and reception of incorporating AI into continuous pregnancy monitoring systems, as well as related tech challenges. They will investigate technological issues in Bangladesh’s health care sector and how these impact AI-based data analysis and decision-making processes. Project outcomes will support the Bangladeshi Government in developing policies to promote and enable AI policy frameworks and AI capability-building for social good....read more