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Category: Research Highlight
  • Research Highlight

    Reinforcement Learning Algorithm for Batch Chemical Process Control

    Haeun Yoo, a member of Prof. Jay H. Lee’s group, has proposed a phase segmentation approach and modified deep deterministic policy gradient algorithm for batch process optimal control under uncertainty....read more

    Actor-Critic AI Applications Batch process KAIST Institute for Artificial Intelligence Machine Learning Optimal control Reinforcement Learning
  • Research Highlight

    Breathable polymer membranes for wearable devices

    Prof. Young-Ho Cho’s group has developed a new fabrication technique for breathable polymer patches that rapidly wick sweat away from the skin. The technique could reduce the redness and itching caused by wearable biosensors that trap sweat beneath them....read more

    AI Emergings Breathable polymer skins Emotion monitoring wearable devices KAIST Institute for Artificial Intelligence Skin-attachable patches Skin-trouble-free wearables Water vapor permeable polymers
  • Research Highlight Top Story

    Unique metal-polymer interaction enables the design of chemoselective and long-lived hydrogenation catalysts

    Dynamic coverage of metal catalysts with polymer chains can control the transport/reaction of molecules, remarkably increasing catalytic selectivity and lifetime....read more

    Catalysis Chemoselectivity Hydrogenation Interaction KI for NanoCentry (KINC) Metal NT for Customized Nanomaterials & Nano Devices Polymer
  • Research Highlight

    Accelerated Material Design Framework using Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory Approach

    Prof. Yousung Jung’s group has developed a new accelerated high throughput screening (HTS) method using uncertainty-quantified machine learning (ML) and density functional theory (DFT) that was applied to explore the Mg-Mn-O chemical space for photoanode application. Notably, the proposed HTS scheme required only 1.5% of the target chemical space for further DFT calculations, accelerating the entire process by > 50 times for the same discovery compared to the brute-force DFT-HTS done previously. This means an improvement of the screening performance (discoverability) by more than a factor of 2 compared to the conventional ML-based HTS approach....read more

    CO2 Conversion Density functional theory High throughput Screening Machine Learning Saudi-Aramco-KAIST CO2 Management Center Uncertainty quantification
  • Research Highlight

    The KPC4IR hosted a second GSI international forum to envision challenges for educational innovation in the non-contact society in the post-coronavirus era.

    KPC4IR (Korea Policy Center for the 4th Industrial Revolution) together with GSI (Global Strategy Institute) hosted the Second GSI International Forum on challenges for educational innovation in the non-contact society in the post-coronavirus era. Live-streamed on Youtube, Naver TV, and KTV on June 24, 2020, the Forum gathered 15 global experts and advisors of educational issues to examine significant challenges for the future of education in an increasingly non-contact society and envision inclusive educational innovations in the post-COVID-19 era....read more

    Inclusive educational innovations in the post-COVID-19 era
  • Research Highlight

    BAF53b regulates memory persistence via FGF1

    Delayed induction of BAF53b in the amygdala after fear learning has a crucial role for memory persistence via regulating FGF1 expression....read more

    BAF53b Brain Cognitive Function Control Brain science Fear conditioning FGF1 KI for the BioCentury Memory Biology Lab Memory persistence
  • Research Highlight

    Development of AI/ML based User Anomaly Detection Solution for Enterprise Resource Planning System

    At the KAIST Institute for Information Technology Convergence, the Intelligent Technology Research team has conducted research and development of an AI/ML based user anomaly detection solution for enterprise resource planning system (ERP), particularly targeted at SAP ERP, by collaborating with ARMIQ (a company with SAP ERP system expertise). The team is developing core modules for ERP user anomaly detection solutions such as user behavior categorizers, AI/ML inference models, model optimization methods). By utilizing domain expertise related to SAP ERP and cutting-edge AI/ML techniques, it is expected to achieve cost-effective localized ML based user anomaly detection solutions....read more

    AI/ML Anomaly detection ERP Internet of Things IoT/WoT KI for Information Technology Convergence Web of Things
  • Research Highlight

    Imaging with Events: High-resolution High-quality HDR Imaging using Event Cameras

    New algorithms have been developed to generate non-blurry, high-resolution, high-quality, and high-dynamic range intensity images using sparse event streams from an event camera, which is a new imaging sensor able to capture visual information with low latency even under extremely low illumination....read more

    AI for Cooperative Robots Computer Vision Deep Learning Event Camera KI for Robotics (KIR) Machine Learning Super-resolution Super-resolution with Event Camera
  • Research Highlight

    Ultra-large and Multi-stimuli-responsive Smart Windows

    Prof. Il-Doo Kim, Prof. Hong Jung-Wuk, and Prof. Seokwoo Jeon jointly developed a novel multi-stimuli-responsive (thermochromic and mechanochromic) membrane based on light scattering at strain-induced nanogaps from oxides and elastomers together with thermochromic dyes. The combination of the polymer writing technique with roll-to-roll production effectively expanded the production area of the smart window membrane to an exceptionally large scale of nearly 300 cm2, far beyond those of previously reported optical modulating membranes to date....read more

    Color change KI for the NanoCentury (KINC) Membrane Innovation Center for Anti-Virus & Air-Quality Control Multi-stimuli-responsive Membrane NT for Advanced Opto-Electronics Polymer writing Smart window
  • Research Highlight

    New Nanoparticle Drug Combination Treats and Prevents Atherosclerosis

    Dr. Ji-Ho Park’s group developed a cargo-switching nanoparticle (CSNP) system that can bind to cholesterol and then release an anti-inflammatory drug (statin) in a plaque-containing microenvironment. The as-developed CSNP had a core-shell structure, with a core composed of cyclodextrin and statin and a shell of phospholipids. In vitro, once interacting with cholesterol, which had a higher affinity to cyclodextrin than statin, the CSNP can instantly release statin and scavenge cholesterol by cargo-switching. In vivo, in a mouse model of atherosclerosis, the CSNP administered systemically can effectively target atherosclerotic plaques and reduce their associated cholesterol and macrophages, leading to prevention of atherogenesis and regression of established plaques....read more

    Atherosclerosis Cargo-switching nanoparticles Cyclodextrin KI for Health Science and Technology Statin Therapeutic Bioengineering Therapeutics development

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