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2022 Global Startup Internship Fair (GSIF)
From November 30 to December 1, 2022, the Center for Global Strategies and Planning at KAIST held the 2022 Global Startup Internship Fair (GSIF) on-line and off-line, as well. Including the globally acknowledged unicorn companies such as PsiQuantum and Moloco, eleven startups — ImpriMed, Vessel AI, Genedit, Medic Life Sciences, Bringko, Brave Turtles, Neozips, Luckmon and CUPIX — joined the fair. Among the eleven invited companies, six were founded by KAIST Alumni representatives. The invited companies sought student interns in the field of AI, biotechnology, quantum, logistics, games, advertisement, real estate, and e-commerce. In response, about 100 KAIST students with various backgrounds have shown their interest in the event through pre-reservation. Participating companies at this fair introduced their companies and conducted recruitment and career counseling with KAIST students. Sungwon Lim, the CEO of ImpriMed and a KAIST alumni, said, “It was very meaningful to introduce ImpriMed to junior students and share my experiences that I gained while pioneering and operating startups in the United States.” To share his journey as a global startup CEO, Lim has been invited as an off-line speaker during this event. < ImpriMed CEO, Sungwon Lim > In addition to the recruiting sessions, the fair held information sessions offering guidelines and useful tips on seeking opportunities overseas including information on obtaining a J1 visa, applying to U.S. internships, relocating to Silicon Valley, and writing CVs, cover letters, and business emails. Professor Man-Sung Yim, the Associate Vice President of the International Office at KAIST, stressed, “A growing number of students at KAIST want to become a global entrepreneur, and hands-on experience gained from U.S. startups is absolutely necessary to achieve their goals.” He added, “the 2022 GSIF was one of those opportunities for KAIST students to further their dream of becoming global leaders.”
2022.12.01
View 6995
Yuji Roh Awarded 2022 Microsoft Research PhD Fellowship
KAIST PhD candidate Yuji Roh of the School of Electrical Engineering (advisor: Prof. Steven Euijong Whang) was selected as a recipient of the 2022 Microsoft Research PhD Fellowship. < KAIST PhD candidate Yuji Roh (advisor: Prof. Steven Euijong Whang) > The Microsoft Research PhD Fellowship is a scholarship program that recognizes outstanding graduate students for their exceptional and innovative research in areas relevant to computer science and related fields. This year, 36 people from around the world received the fellowship, and Yuji Roh from KAIST EE is the only recipient from universities in Korea. Each selected fellow will receive a $10,000 scholarship and an opportunity to intern at Microsoft under the guidance of an experienced researcher. Yuji Roh was named a fellow in the field of “Machine Learning” for her outstanding achievements in Trustworthy AI. Her research highlights include designing a state-of-the-art fair training framework using batch selection and developing novel algorithms for both fair and robust training. Her works have been presented at the top machine learning conferences ICML, ICLR, and NeurIPS among others. She also co-presented a tutorial on Trustworthy AI at the top data mining conference ACM SIGKDD. She is currently interning at the NVIDIA Research AI Algorithms Group developing large-scale real-world fair AI frameworks. The list of fellowship recipients and the interview videos are displayed on the Microsoft webpage and Youtube. The list of recipients: https://www.microsoft.com/en-us/research/academic-program/phd-fellowship/2022-recipients/ Interview (Global): https://www.youtube.com/watch?v=T4Q-XwOOoJc Interview (Asia): https://www.youtube.com/watch?v=qwq3R1XU8UE [Highlighted research achievements by Yuji Roh: Fair batch selection framework] [Highlighted research achievements by Yuji Roh: Fair and robust training framework]
2022.10.28
View 13391
KAIST develops biocompatible adhesive applicable to hair transplants
Aside from being used as a new medical adhesive, the new material can be applied to developing a new method of hair transplants, which cannot be repeated multiple times using current method of implanting the wholly intact follicles into the skin. Medical adhesives are materials that can be applied to various uses such as wound healing, hemostasis, vascular anastomosis, and tissue engineering, and is expected to contribute greatly to the development of minimally invasive surgery and organ transplants. However, adhesives with high adhesion, low toxicity, and capable of decomposing in the body are rare. Adhesives based on natural proteins, such as fibrin and collagen, have high biocompatibility but insufficient adhesive strength. Synthetic polymer adhesives based on urethane or acrylic have greater adhesion but do not decompose well and may cause an inflammatory reaction in the body. A joint research team led by Professor Myungeun Seo and Professor Haeshin Lee from the KAIST Department of Chemistry developed a bio-friendly adhesive from biocompatible polymers using tannic acid, the source of astringency in wine. The research team focused on tannic acid, a natural polyphenolic product. Tannic acid is a polyphenol present in large amounts in fruit peels, nuts, and cacao. It has a high affinity and coating ability on other substances, and we sense the astringent taste in wine when tannic acid sticks to the surface of our tongue. When tannic acid is mixed with hydrophilic polymers, they form coacervates, or small droplets of jelly-like fluids that sink. If the polymers used are biocompatible, the mixture can be applied as a medical adhesive with low toxicity. However, coacervates are fundamentally fluid-like and cannot withstand large forces, which limits their adhesive capabilities. Thus, while research to utilize it as an adhesive has been actively discussed, a biodegradable material exhibiting strong adhesion due to its high shear strength has not yet been developed. The research team figured out a way to enhance adhesion by mixing two biocompatible FDA-approved polymers, polyethylene glycol (PEG) and polylactic acid (PLA). While PEG, which is used widely in eyedrops and cream, is hydrophilic, PLA, a well-known bioplastic derived from lactic acid, is insoluble in water. The team combined the two into a block copolymer, which forms hydrophilic PLA aggregates in water with PEG blocks surrounding them. A coacervate created by mixing the micelles and tannic acid would behave like a solid due to the hard PLA components, and show an elastic modulus improved by a thousand times compared to PEG, enabling it to withstand much greater force as an adhesive. Figure 1. (Above) Principle of biodegradable adhesive made by mixing poly(ethylene glycol)-poly(lactic acid) diblock copolymer and tannic acid in water. Yellow coacervate is precipitated through hydrogen bonding between the block copolymer micelles and tannic acid, and exhibits adhesion. After heat treatment, hydrogen bonds are rearranged to further improve adhesion. (Bottom) Adhesion comparison. Compared to using poly(ethylene glycol) polymer (d), it can support 10 times more weight when using block copolymer (e) and 60 times more weight after heat treatment (f). The indicated G' values represent the elastic modulus of the material. Furthermore, the research team observed that the material’s mechanical properties can be improved by over a hundred times through a heating and cooling process that is used to heat-treat metals. They also discovered that this is due to the enforced interactions between micelle and tannic acid arrays. The research team used the fact that the material shows minimal irritation to the skin and decomposes well in the body to demonstrate its possible application as an adhesive for hair transplantation through an animal experiment. Professor Haeshin Lee, who has pioneered various application fields including medical adhesives, hemostatic agents, and browning shampoo, focused on the adhesive capacities and low toxicity of polyphenols like tannic acid, and now looks forward to it improving the limitations of current hair transplant methods, which still involve follicle transfer and are difficult to be repeated multiple times. Figure 2. (a) Overview of a hair transplantation method using a biodegradable adhesive (right) compared to a conventional hair transplantation method (left) that transplants hair containing hair follicles. After applying an adhesive to the tip of the hair, it is fixed to the skin by implanting it through a subcutaneous injection, and repeated treatment is possible. (b) Initial animal test results. One day after 15 hair transplantation, 12 strands of hair remain. If you pull the 3 strands of hair, you can see that the whole body is pulled up, indicating that it is firmly implanted into the skin. All strands of hair applied without the new adhesive material fell off, and in the case of adhesive without heat treatment, the efficiency was 1/7. This research was conducted by first co-authors Dr. Jongmin Park (currently a senior researcher at the Korea Research Institute of Chemical Technology) from Professor Myeongeun Seo’s team and Dr. Eunsook Park from Professor Haeshin Lee’s team in the KAIST Department of Chemistry, and through joint research with the teams led by Professor Hyungjun Kim from the KAIST Department of Chemistry and Professor Siyoung Choi from the Department of Chemical and Biomolecular Engineering. The research was published online on August 22 in the international journal Au (JACS Au) under the title Biodegradable Block Copolymer-Tannic Acid Glue. This study was funded by the Support Research Under Protection Project of the National Research Foundation (NRF), Leading Research Center Support Project (Research Center for Multiscale Chiral Structure), Biodegradable Plastics Commercialization and Demonstration Project by the Ministry of Trade and Industry, and institutional funding from the Korea Research Institute of Chemical Technology.
2022.10.07
View 11317
Phage resistant Escherichia coli strains developed to reduce fermentation failure
A genome engineering-based systematic strategy for developing phage resistant Escherichia coli strains has been successfully developed through the collaborative efforts of a team led by Professor Sang Yup Lee, Professor Shi Chen, and Professor Lianrong Wang. This study by Xuan Zou et al. was published in Nature Communications in August 2022 and featured in Nature Communications Editors’ Highlights. The collaboration by the School of Pharmaceutical Sciences at Wuhan University, the First Affiliated Hospital of Shenzhen University, and the KAIST Department of Chemical and Biomolecular Engineering has made an important advance in the metabolic engineering and fermentation industry as it solves a big problem of phage infection causing fermentation failure. Systems metabolic engineering is a highly interdisciplinary field that has made the development of microbial cell factories to produce various bioproducts including chemicals, fuels, and materials possible in a sustainable and environmentally friendly way, mitigating the impact of worldwide resource depletion and climate change. Escherichia coli is one of the most important chassis microbial strains, given its wide applications in the bio-based production of a diverse range of chemicals and materials. With the development of tools and strategies for systems metabolic engineering using E. coli, a highly optimized and well-characterized cell factory will play a crucial role in converting cheap and readily available raw materials into products of great economic and industrial value. However, the consistent problem of phage contamination in fermentation imposes a devastating impact on host cells and threatens the productivity of bacterial bioprocesses in biotechnology facilities, which can lead to widespread fermentation failure and immeasurable economic loss. Host-controlled defense systems can be developed into effective genetic engineering solutions to address bacteriophage contamination in industrial-scale fermentation; however, most of the resistance mechanisms only narrowly restrict phages and their effect on phage contamination will be limited. There have been attempts to develop diverse abilities/systems for environmental adaptation or antiviral defense. The team’s collaborative efforts developed a new type II single-stranded DNA phosphorothioation (Ssp) defense system derived from E. coli 3234/A, which can be used in multiple industrial E. coli strains (e.g., E. coli K-12, B and W) to provide broad protection against various types of dsDNA coliphages. Furthermore, they developed a systematic genome engineering strategy involving the simultaneous genomic integration of the Ssp defense module and mutations in components that are essential to the phage life cycle. This strategy can be used to transform E. coli hosts that are highly susceptible to phage attack into strains with powerful restriction effects on the tested bacteriophages. This endows hosts with strong resistance against a wide spectrum of phage infections without affecting bacterial growth and normal physiological function. More importantly, the resulting engineered phage-resistant strains maintained the capabilities of producing the desired chemicals and recombinant proteins even under high levels of phage cocktail challenge, which provides crucial protection against phage attacks. This is a major step forward, as it provides a systematic solution for engineering phage-resistant bacterial strains, especially industrial bioproduction strains, to protect cells from a wide range of bacteriophages. Considering the functionality of this engineering strategy with diverse E. coli strains, the strategy reported in this study can be widely extended to other bacterial species and industrial applications, which will be of great interest to researchers in academia and industry alike. Fig. A schematic model of the systematic strategy for engineering phage-sensitive industrial E. coli strains into strains with broad antiphage activities. Through the simultaneous genomic integration of a DNA phosphorothioation-based Ssp defense module and mutations of components essential for the phage life cycle, the engineered E. coli strains show strong resistance against diverse phages tested and maintain the capabilities of producing example recombinant proteins, even under high levels of phage cocktail challenge.
2022.08.23
View 13528
KAIST Honors BMW and Hyundai with the 2022 Future Mobility of the Year Award
BMW ‘iVision Circular’, Commercial Vehicle-Hyundai Motors ‘Trailer Drone’ selected as winners of the international awards for concept cars established by KAIST Cho Chun Shik Graduate School of Mobility to honor car makers that strive to present new visions in the field of eco-friendly design of automobiles and unmanned logistics. KAIST (President Kwang Hyung Lee) hosted the “2022 Future Mobility of the Year (FMOTY) Awards” at the Convention Hall of the BEXCO International Motor Show at Busan in the afternoon of the 14th. The Future Mobility of the Year Awards is an award ceremony that selects a model that showcases useful transportation technology and innovative service concepts for the future society among the set of concept cars exhibited at the motor show. As a one-of-a-kind international concept car awards established by KAIST's Cho Chun Shik Graduate School of Mobility (Headed by Professor Jang In-Gwon), the auto journalists from 11 countries were invited to be the jurors to select the winner. With the inaugural awards ceremony held in 2019, over the past three years, automakers from around the globe, including internationally renowned automakers, such as, Volvo/Toyota (2019), Honda/Hyundai (2020), and Renault (2021), even a new start-up car manufacturer like Canoo, the winner of last year’s award for commercial vehicles, were honored for their award-winning works. At this year’s awards ceremony, the 4th of its kind, BMW's “iVision Circular” and Hyundai's “'Trailer Drone” were selected as the best concept cars of the year, the former from the Private Mobility category and the latter from the Public & Commercial Vehicles category. The jury consisting of 16 domestic and foreign auto journalists, including BBC Top Gear's Paul Horrell and Car Magazine’s Georg Kacher, evaluated 53 concept car contestants that made their entry last year. The jurors’ general comment was that while the trend of the global automobile market flowing fast towards electric vehicles, this year's award-winning works presented a new vision in the field of eco-friendly design and unmanned logistics. Private Mobility Categry Winner: BMW iVision Circular BMW's 'iVision Circular', the winner of the Private Mobility category, is an eco-friendly compact car in which all parts of the vehicle are designed with recycled and/or natural materials. It has received favorable reviews for its in-depth implementation of the concept of a futuristic eco-friendly car by manufacturing the tires from natural rubber and adopting a design that made recycling of its parts very easily when the car is to be disposed of. Public & Commercial Vehicles Categry Winner: Hyundai Trailer Drone Hyundai Motor Company’s “Trailer Drone”, the winner of the Public & Commercial Vehicles category, is an eco-friendly autonomous driving truck that can transport large-scale logistics from a port to a destination without a human driver while two unmanned vehicles push and drag a trailer. The concept car won supports from a large number of judges for the blueprint it presented for a groundbreaking logistics service that applied both eco-friendly hydrogen fuel cell and fully autonomous driving technology. Jurors from overseas congratulated the development team of BMW and Hyundai Motor Company via a video message for providing a new direction for the global automobile industry as it strives to transform in line with the changes in the post-pandemic era. Professor Bo-won Kim, the Vice President for Planning and Budget of KAIST, who presented the awards, said, “It is time for the K-Mobility wave to sweep over the global mobility industry.” “KAIST will lead in the various fields of mobility technologies to support global automakers,” he added. Splitting the center are KAIST Vice President Bo-Won Kim on the right, and Seong-Kwon Lee, the Deputy Mayor of the City of Busan on the left. To Kim's left is the Senior VP of BMW Asia-Pacific, Eastern Europe, Middle East, Africa, Jean-Philippe Parain, and to Lee's Right is Sangyup Lee, the Head of Hyundai Motor Design Center and the Executive VP of Hyundai Motors. At the ceremony, along with KAIST officials, including Vice President Bo-Won Kim and Professor In-Gwon Jang, the Head of Cho Chun Shik Graduate School of Mobility, are the Deputy Mayor Seong-Kwon Lee of the City of Busan and the figures from the automobile industry, including Jean-Philippe Parain, the Senior Vice President of BMW Asia-Pacific, Eastern Europe, Middle East, Africa, who is visiting Korea to receive the '2022 Future Mobility' award, and Sangyup Lee, the Head of Hyundai Motor Design Center and the Executive Vice President of Hyundai Motor Company, were in the attendance. More information about the awards ceremony and winning works are available at the official website of this year's Future Mobility Awards (www.fmoty.org). Profile:In-Gwon Jang, Ph.D.Presidentthe Organizing Committeethe Future Mobility of the Year Awardshttp://www.fmoty.org/ Head ProfessorKAIST Cho Chun Shik Graduate School of Mobilityhttps://gt.kaist.ac.kr
2022.07.14
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Professor Jae-Woong Jeong Receives Hyonwoo KAIST Academic Award
Professor Jae-Woong Jeong from the School of Electrical Engineering was selected for the Hyonwoo KAIST Academic Award, funded by the HyonWoo Cultural Foundation (Chairman Soo-il Kwak, honorary professor at Seoul National University Business School). The Hyonwoo KAIST Academic Award, presented for the first time in 2021, is an award newly founded by the donations of Chairman Soo-il Kwak of the HyonWoo Cultural Foundation, who aims to reward excellent KAIST scholars who have made outstanding academic achievements. Every year, through the strict evaluations of the selection committee of the HyonWoo Cultural Foundation and the faculty reward recommendation board, KAIST will choose one faculty member that may represent the school with their excellent academic achievement, and reward them with a plaque and 100 million won. Professor Jae-Woong Jeong, the winner of this year’s award, developed the first IoT-based wireless remote brain neural network control system to overcome brain diseases, and has been leading the field. The research was published in 2021 in Nature Biomedical Engineering, one of world’s best scientific journals, and has been recognized as a novel technology that suggested a new vision for the automation of brain research and disease treatment. This study, led by Professor Jeong’s research team, was part of the KAIST College of Engineering Global Initiative Interdisciplinary Research Project, and was jointly studied by Washington University School of Medicine through an international research collaboration. The technology was introduced more than 60 times through both domestic and international media, including Medical Xpress, MBC News, and Maeil Business News. Professor Jeong has also developed a wirelessly chargeable soft machine for brain transplants, and the results were published in Nature Communications. He thereby opened a new paradigm for implantable semi-permanent devices for transplants, and is making unprecedented research achievements.
2022.06.13
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Neuromorphic Memory Device Simulates Neurons and Synapses
Simultaneous emulation of neuronal and synaptic properties promotes the development of brain-like artificial intelligence Researchers have reported a nano-sized neuromorphic memory device that emulates neurons and synapses simultaneously in a unit cell, another step toward completing the goal of neuromorphic computing designed to rigorously mimic the human brain with semiconductor devices. Neuromorphic computing aims to realize artificial intelligence (AI) by mimicking the mechanisms of neurons and synapses that make up the human brain. Inspired by the cognitive functions of the human brain that current computers cannot provide, neuromorphic devices have been widely investigated. However, current Complementary Metal-Oxide Semiconductor (CMOS)-based neuromorphic circuits simply connect artificial neurons and synapses without synergistic interactions, and the concomitant implementation of neurons and synapses still remains a challenge. To address these issues, a research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering implemented the biological working mechanisms of humans by introducing the neuron-synapse interactions in a single memory cell, rather than the conventional approach of electrically connecting artificial neuronal and synaptic devices. Similar to commercial graphics cards, the artificial synaptic devices previously studied often used to accelerate parallel computations, which shows clear differences from the operational mechanisms of the human brain. The research team implemented the synergistic interactions between neurons and synapses in the neuromorphic memory device, emulating the mechanisms of the biological neural network. In addition, the developed neuromorphic device can replace complex CMOS neuron circuits with a single device, providing high scalability and cost efficiency. The human brain consists of a complex network of 100 billion neurons and 100 trillion synapses. The functions and structures of neurons and synapses can flexibly change according to the external stimuli, adapting to the surrounding environment. The research team developed a neuromorphic device in which short-term and long-term memories coexist using volatile and non-volatile memory devices that mimic the characteristics of neurons and synapses, respectively. A threshold switch device is used as volatile memory and phase-change memory is used as a non-volatile device. Two thin-film devices are integrated without intermediate electrodes, implementing the functional adaptability of neurons and synapses in the neuromorphic memory. Professor Keon Jae Lee explained, "Neurons and synapses interact with each other to establish cognitive functions such as memory and learning, so simulating both is an essential element for brain-inspired artificial intelligence. The developed neuromorphic memory device also mimics the retraining effect that allows quick learning of the forgotten information by implementing a positive feedback effect between neurons and synapses.” This result entitled “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse” was published in the May 19, 2022 issue of Nature Communications. -Publication:Sang Hyun Sung, Tae Jin Kim, Hyera Shin, Tae Hong Im, and Keon Jae Lee (2022) “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse,” Nature Communications May 19, 2022 (DOI: 10.1038/s41467-022-30432-2) -Profile:Professor Keon Jae Leehttp://fand.kaist.ac.kr Department of Materials Science and EngineeringKAIST
2022.05.20
View 13982
Energy-Efficient AI Hardware Technology Via a Brain-Inspired Stashing System
Researchers demonstrate neuromodulation-inspired stashing system for the energy-efficient learning of a spiking neural network using a self-rectifying memristor array Researchers have proposed a novel system inspired by the neuromodulation of the brain, referred to as a ‘stashing system,’ that requires less energy consumption. The research group led by Professor Kyung Min Kim from the Department of Materials Science and Engineering has developed a technology that can efficiently handle mathematical operations for artificial intelligence by imitating the continuous changes in the topology of the neural network according to the situation. The human brain changes its neural topology in real time, learning to store or recall memories as needed. The research group presented a new artificial intelligence learning method that directly implements these neural coordination circuit configurations. Research on artificial intelligence is becoming very active, and the development of artificial intelligence-based electronic devices and product releases are accelerating, especially in the Fourth Industrial Revolution age. To implement artificial intelligence in electronic devices, customized hardware development should also be supported. However most electronic devices for artificial intelligence require high power consumption and highly integrated memory arrays for large-scale tasks. It has been challenging to solve these power consumption and integration limitations, and efforts have been made to find out how the human brain solves problems. To prove the efficiency of the developed technology, the research group created artificial neural network hardware equipped with a self-rectifying synaptic array and algorithm called a ‘stashing system’ that was developed to conduct artificial intelligence learning. As a result, it was able to reduce energy by 37% within the stashing system without any accuracy degradation. This result proves that emulating the neuromodulation in humans is possible. Professor Kim said, "In this study, we implemented the learning method of the human brain with only a simple circuit composition and through this we were able to reduce the energy needed by nearly 40 percent.” This neuromodulation-inspired stashing system that mimics the brain’s neural activity is compatible with existing electronic devices and commercialized semiconductor hardware. It is expected to be used in the design of next-generation semiconductor chips for artificial intelligence. This study was published in Advanced Functional Materials in March 2022 and supported by KAIST, the National Research Foundation of Korea, the National NanoFab Center, and SK Hynix. -Publication: Woon Hyung Cheong, Jae Bum Jeon†, Jae Hyun In, Geunyoung Kim, Hanchan Song, Janho An, Juseong Park, Young Seok Kim, Cheol Seong Hwang, and Kyung Min Kim (2022) “Demonstration of Neuromodulation-inspired Stashing System for Energy-efficient Learning of Spiking Neural Network using a Self-Rectifying Memristor Array,” Advanced FunctionalMaterials March 31, 2022 (DOI: 10.1002/adfm.202200337) -Profile: Professor Kyung Min Kimhttp://semi.kaist.ac.kr https://scholar.google.com/citations?user=BGw8yDYAAAAJ&hl=ko Department of Materials Science and EngineeringKAIST
2022.05.18
View 11420
Professor Lik-Hang Lee Offers Metaverse Course for Hong Kong Productivity Council
Professor Lik-Hang Lee from the Department of Industrial System Engineering will offer a metaverse course in partnership with the Hong Kong Productivity Council (HKPC) from the Spring 2022 semester to Hong Kong-based professionals. “The Metaverse Course for Professionals” aims to nurture world-class talents of the metaverse in response to surging demand for virtual worlds and virtual-physical blended environments. The HKPC’s R&D scientists, consultants, software engineers, and related professionals will attend the course. They will receive a professional certificate on managing and developing metaverse skills upon the completion of this intensive course. The course will provide essential skills and knowledge about the parallel virtual universe and how to leverage digitalization and industrialization in the metaverse era. The course includes comprehensive modules, such as designing and implementing virtual-physical blended environments, metaverse technology and ecosystems, immersive smart cities, token economies, and intelligent industrialization in the metaverse era. Professor Lee believes in the decades to come that we will see rising numbers of virtual worlds in cyberspace known as the ‘Immersive Internet’ that will be characterized by high levels of immersiveness, user interactivity, and user-machine collaborations. “Consumers in virtual worlds will create novel content as well as personalized products and services, becoming as catalyst for ‘hyperpersonalization’ in the next industrial revolution,” he said. Professor Lee said he will continue offering world-class education related to the metaverse to students in KAIST and professionals from various industrial sectors, as his Augmented Reality and Media Lab will focus on a variety of metaverse topics such as metaverse campuses and industrial metaverses. The HKPC has worked to address innovative solutions for Hong Kong industries and enterprises since 1967, helping them achieve optimized resource utilization, effectiveness, and cost reduction as well as enhanced productivity and competitiveness in both local and international markets. The HKPC has advocated for facilitating Hong Kong’s reindustrialization powered by Industry 4.0 and e-commerce 4.0 with a strong emphasis on R&D, IoT, AI, digital manufacturing. The Augmented Reality and Media Lab led by Professor Lee will continue its close partnerships with HKPC and its other partners to help build the epicentre of the metaverse in the region. Furthermore, the lab will fully leverage its well-established research niches in user-centric, virtual-physical cyberspace (https://www.lhlee.com/projects-8 ) to serve upcoming projects related to industrial metaverses, which aligns with the departmental focus on smart factories and artificial intelligence.
2022.04.06
View 8631
CXL-Based Memory Disaggregation Technology Opens Up a New Direction for Big Data Solution Frameworks
A KAIST team’s compute express link (CXL) provides new insights on memory disaggregation and ensures direct access and high-performance capabilities A team from the Computer Architecture and Memory Systems Laboratory (CAMEL) at KAIST presented a new compute express link (CXL) solution whose directly accessible, and high-performance memory disaggregation opens new directions for big data memory processing. Professor Myoungsoo Jung said the team’s technology significantly improves performance compared to existing remote direct memory access (RDMA)-based memory disaggregation. CXL is a peripheral component interconnect-express (PCIe)-based new dynamic multi-protocol made for efficiently utilizing memory devices and accelerators. Many enterprise data centers and memory vendors are paying attention to it as the next-generation multi-protocol for the era of big data. Emerging big data applications such as machine learning, graph analytics, and in-memory databases require large memory capacities. However, scaling out the memory capacity via a prior memory interface like double data rate (DDR) is limited by the number of the central processing units (CPUs) and memory controllers. Therefore, memory disaggregation, which allows connecting a host to another host’s memory or memory nodes, has appeared. RDMA is a way that a host can directly access another host’s memory via InfiniBand, the commonly used network protocol in data centers. Nowadays, most existing memory disaggregation technologies employ RDMA to get a large memory capacity. As a result, a host can share another host’s memory by transferring the data between local and remote memory. Although RDMA-based memory disaggregation provides a large memory capacity to a host, two critical problems exist. First, scaling out the memory still needs an extra CPU to be added. Since passive memory such as dynamic random-access memory (DRAM), cannot operate by itself, it should be controlled by the CPU. Second, redundant data copies and software fabric interventions for RDMA-based memory disaggregation cause longer access latency. For example, remote memory access latency in RDMA-based memory disaggregation is multiple orders of magnitude longer than local memory access. To address these issues, Professor Jung’s team developed the CXL-based memory disaggregation framework, including CXL-enabled customized CPUs, CXL devices, CXL switches, and CXL-aware operating system modules. The team’s CXL device is a pure passive and directly accessible memory node that contains multiple DRAM dual inline memory modules (DIMMs) and a CXL memory controller. Since the CXL memory controller supports the memory in the CXL device, a host can utilize the memory node without processor or software intervention. The team’s CXL switch enables scaling out a host’s memory capacity by hierarchically connecting multiple CXL devices to the CXL switch allowing more than hundreds of devices. Atop the switches and devices, the team’s CXL-enabled operating system removes redundant data copy and protocol conversion exhibited by conventional RDMA, which can significantly decrease access latency to the memory nodes. In a test comparing loading 64B (cacheline) data from memory pooling devices, CXL-based memory disaggregation showed 8.2 times higher data load performance than RDMA-based memory disaggregation and even similar performance to local DRAM memory. In the team’s evaluations for a big data benchmark such as a machine learning-based test, CXL-based memory disaggregation technology also showed a maximum of 3.7 times higher performance than prior RDMA-based memory disaggregation technologies. “Escaping from the conventional RDMA-based memory disaggregation, our CXL-based memory disaggregation framework can provide high scalability and performance for diverse datacenters and cloud service infrastructures,” said Professor Jung. He went on to stress, “Our CXL-based memory disaggregation research will bring about a new paradigm for memory solutions that will lead the era of big data.” -Profile: Professor Myoungsoo Jung Computer Architecture and Memory Systems Laboratory (CAMEL)http://camelab.org School of Electrical EngineeringKAIST
2022.03.16
View 23021
Scientist Discover How Circadian Rhythm Can Be Both Strong and Flexible
Study reveals that master and slave oscillators function via different molecular mechanisms From tiny fruit flies to human beings, all animals on Earth maintain their daily rhythms based on their internal circadian clock. The circadian clock enables organisms to undergo rhythmic changes in behavior and physiology based on a 24-hour circadian cycle. For example, our own biological clock tells our brain to release melatonin, a sleep-inducing hormone, at night time. The discovery of the molecular mechanism of the circadian clock was bestowed the Nobel Prize in Physiology or Medicine 2017. From what we know, no one centralized clock is responsible for our circadian cycles. Instead, it operates in a hierarchical network where there are “master pacemaker” and “slave oscillator”. The master pacemaker receives various input signals from the environment such as light. The master then drives the slave oscillator that regulates various outputs such as sleep, feeding, and metabolism. Despite the different roles of the pacemaker neurons, they are known to share common molecular mechanisms that are well conserved in all lifeforms. For example, interlocked systems of multiple transcriptional-translational feedback loops (TTFLs) composed of core clock proteins have been deeply studied in fruit flies. However, there is still much that we need to learn about our own biological clock. The hierarchically-organized nature of master and slave clock neurons leads to a prevailing belief that they share an identical molecular clockwork. At the same time, the different roles they serve in regulating bodily rhythms also raise the question of whether they might function under different molecular clockworks. Research team led by Professor Kim Jae Kyoung from the Department of Mathematical Sciences, a chief investigator at the Biomedical Mathematics Group at the Institute for Basic Science, used a combination of mathematical and experimental approaches using fruit flies to answer this question. The team found that the master clock and the slave clock operate via different molecular mechanisms. In both master and slave neurons of fruit flies, a circadian rhythm-related protein called PER is produced and degraded at different rates depending on the time of the day. Previously, the team found that the master clock neuron (sLNvs) and the slave clock neuron (DN1ps) have different profiles of PER in wild-type and Clk-Δ mutant Drosophila. This hinted that there might be a potential difference in molecular clockworks between the master and slave clock neurons. However, due to the complexity of the molecular clockwork, it was challenging to identify the source of such differences. Thus, the team developed a mathematical model describing the molecular clockworks of the master and slave clocks. Then, all possible molecular differences between the master and slave clock neurons were systematically investigated by using computer simulations. The model predicted that PER is more efficiently produced and then rapidly degraded in the master clock compared to the slave clock neurons. This prediction was then confirmed by the follow-up experiments using animal. Then, why do the master clock neurons have such different molecular properties from the slave clock neurons? To answer this question, the research team again used the combination of mathematical model simulation and experiments. It was found that the faster rate of synthesis of PER in the master clock neurons allows them to generate synchronized rhythms with a high level of amplitude. Generation of such a strong rhythm with high amplitude is critical to delivering clear signals to slave clock neurons. However, such strong rhythms would typically be unfavorable when it comes to adapting to environmental changes. These include natural causes such as different daylight hours across summer and winter seasons, up to more extreme artificial cases such as jet lag that occurs after international travel. Thanks to the distinct property of the master clock neurons, it is able to undergo phase dispersion when the standard light-dark cycle is disrupted, drastically reducing the level of PER. The master clock neurons can then easily adapt to the new diurnal cycle. Our master pacemaker’s plasticity explains how we can quickly adjust to the new time zones after international flights after just a brief period of jet lag. It is hoped that the findings of this study can have future clinical implications when it comes to treating various disorders that affect our circadian rhythm. Professor Kim notes, “When the circadian clock loses its robustness and flexibility, the circadian rhythms sleep disorders can occur. As this study identifies the molecular mechanism that generates robustness and flexibility of the circadian clock, it can facilitate the identification of the cause of and treatment strategy for the circadian rhythm sleep disorders.” This work was supported by the Human Frontier Science Program. -PublicationEui Min Jeong, Miri Kwon, Eunjoo Cho, Sang Hyuk Lee, Hyun Kim, Eun Young Kim, and Jae Kyoung Kim, “Systematic modeling-driven experiments identify distinct molecularclockworks underlying hierarchically organized pacemaker neurons,” February 22, 2022, Proceedings of the National Academy of Sciences of the United States of America -ProfileProfessor Jae Kyoung KimDepartment of Mathematical SciencesKAIST
2022.02.23
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A Mathematical Model Shows High Viral Transmissions Reduce the Progression Rates for Severe Covid-19
The model suggests a clue as to when a pandemic will turn into an endemic A mathematical model demonstrated that high transmission rates among highly vaccinated populations of COVID-19 ultimately reduce the numbers of severe cases. This model suggests a clue as to when this pandemic will turn into an endemic. With the future of the pandemic remaining uncertain, a research team of mathematicians and medical scientists analyzed a mathematical model that may predict how the changing transmission rate of COVID-19 would affect the settlement process of the virus as a mild respiratory virus. The team led by Professor Jae Kyoung Kim from the Department of Mathematical Science and Professor Eui-Cheol Shin from the Graduate School of Medical Science and Engineering used a new approach by dividing the human immune responses to SARS-CoV-2 into a shorter-term neutralizing antibody response and a longer-term T-cell immune response, and applying them each to a mathematical model. Additionally, the analysis was based on the fact that although breakthrough infection may occur frequently, the immune response of the patient will be boosted after recovery from each breakthrough infection. The results showed that in an environment with a high vaccination rate, although COVID-19 cases may rise temporarily when the transmission rate increases, the ratio of critical cases would ultimately decline, thereby decreasing the total number of critical cases and in fact settling COVID-19 as a mild respiratory disease more quickly. Conditions in which the number of cases may spike include relaxing social distancing measures or the rise of variants with higher transmission rates like the Omicron variant. This research did not take the less virulent characteristic of the Omicron variant into account but focused on the results of its high transmission rate, thereby predicting what may happen in the process of the endemic transition of COVID-19. The research team pointed out the limitations of their mathematical model, such as the lack of consideration for age or patients with underlying diseases, and explained that the results of this study must be applied with care when compared against high-risk groups. Additionally, as medical systems may collapse when the number of cases rises sharply, this study must be interpreted with prudence and applied accordingly. The research team therefore emphasized that for policies that encourage a step-wise return to normality to succeed, the sustainable maintenance of public health systems is indispensable. Professor Kim said, “We have drawn a counter-intuitive conclusion amid the unpredictable pandemic through an adequate mathematical model,” asserting the importance of applying mathematical models to medical research. Professor Shin said, “Although the Omicron variant has become the dominant strain and the number of cases is rising rapidly in South Korea, it is important to use scientific approaches to predict the future and apply them to policies rather than fearing the current situation.” The results of the research were published on medRxiv.org on February 11, under the title “Increasing viral transmission paradoxically reduces progression rates to severe COVID-19 during endemic transition.” This research was funded by the Institute of Basic Science, the Korea Health Industry Development Institute, and the National Research Foundation of Korea. -PublicationHyukpyo Hong, Ji Yun Noh, Hyojung Lee, Sunhwa Choi, Boseung Choi, Jae Kyung Kim, Eui-Cheol Shin, “Increasing viral transmission paradoxically reduces progression rates to severe COVID-19 during endemic transition,” medRxiv, February 9, 2022 (doi.org/10.1101/2022.02.09.22270633) -ProfileProfessor Jae Kyung KimDepartment of Mathematical SciencesKAIST Professor Eui-Cheol ShinGraduate School of Medical Science and EngineeringKAIST
2022.02.22
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