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KAIST and Merck Sign MOU to Boost Biotech Innovation
< (From left) KAIST President Kwang-Hyung Lee and Merck CEO Matthias Heinzel > KAIST (President Kwang-Hyung Lee) signed a Memorandum of Understanding (MOU) with Merck Life Science (CEO Matthias Heinzel) on May 29 to foster innovation and technology creation in advanced biotechnology. Since May of last year, the two institutions have been discussing multidimensional innovation programs and will now focus on industry-academia cooperation to tackle bioindustry challenges with this MOU as a foundation. KAIST will conduct joint research projects in various advanced biotechnology fields, such as synthetic biology, mRNA, cell line engineering, and organoids, using the chemical and biological portfolios provided by Merck. Additionally, KAIST will establish an Experience Lab in collaboration with the Department of Materials Science and Engineering and the Graduate School of Medical Science and Engineering. This lab will support the discovery and analysis of candidate substances in materials science and biology. Programs to enhance researchers' capabilities will also be offered. Scholarships for graduate students and awards for professors will be implemented. Researchers will have opportunities to participate in global academic events and educational programs hosted by Merck, such as the Curious 2024 Future Insight Conference and the Innovation Cup. M Ventures, a venture capital subsidiary of Merck Group, will collaborate with KAIST's startup institute to support technology commercialization and continue to develop their startup ecosystem. The signing ceremony at KAIST's main campus in Daejeon was attended by the CEO of Merck Life Science and the President of KAIST along with representatives from both institutions. Matthias Heinzel, a member of the Executive Board of Merck and CEO Life Science, said, “This agreement with KAIST is a significant step toward accelerating the development of the life science industry both in Korea and globally. Advancing life science research and fostering the next generation of scientists is essential for discovering new medicines to meet global health needs.” President Kwang-Hyung Lee responded, “We are pleased to share a vision for scientific advancement with Merck, a leading global technology company. We anticipate that this partnership will strengthen the connection between Merck’s life science business and the global scientific community.” In March, Merck, a global science and technology company with over 350 years of history, announced a plan to invest 430 billion KRW (€300 million) to build a bioprocessing center in Daejeon, where KAIST is located. This is Merck's largest investment in the Asia-Pacific region.
2024.05.30
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A KAIST Research Team Develops Diesel Reforming Catalyst Enabling Hydrogen Production for Future Mobile Fuel Cells
This catalyst capability allowing stable hydrogen production from commercial diesel is expected to be applied in mobile fuel cell systems in the future hydrogen economy On August 16, a joint research team led by Professors Joongmyeon Bae and Kang Taek Lee of KAIST’s Department of Mechanical Engineering and Dr. Chan-Woo Lee of Korea Institute of Energy Research (KIER) announced the successful development of a highly active and durable reforming catalyst allowing hydrogen production from commercial diesel. Fuel reforming is a hydrogen production technique that extracts hydrogen from hydrocarbons through catalytic reactions. Diesel, being a liquid fuel, has a high storage density for hydrogen and is easy to transport and store. There have therefore been continuous research efforts to apply hydrogel supply systems using diesel reformation in mobile fuel cells, such as for auxiliary power in heavy trucks or air-independent propulsion (AIP) systems in submarines. However, diesel is a mixture of high hydrocarbons including long-chained paraffin, double-bonded olefin, and aromatic hydrocarbons with benzene groups, and it requires a highly active catalyst to effectively break them down. In addition, the catalyst must be extremely durable against caulking and sintering, as they are often the main causes of catalyst degradation. Such challenges have limited the use of diesel reformation technologies to date. The joint research team successfully developed a highly active and durable diesel reforming catalyst through elution (a heat treatment method used to uniformly grow active metals retained in an oxide support as ions in the form of metal nanoparticles), forming alloy nanoparticles. The design was based on the fact that eluted nanoparticles strongly interact with the support, allowing a high degree of dispersion at high temperatures, and that producing an alloy from dissimilar metals can increase the performance of catalysts through a synergistic effect. The research team introduced a solution combustion synthesis method to produce a multi-component catalyst with a trace amount of platinum (Pt) and ruthenium (Ru) penetrated into a ceria (CeO2) lattice, which is a structure commonly used as a support for catalysts in redox reactions. When exposed to a diesel reforming reaction environment, the catalyst induces Pt-Ru alloy nanoparticle formation upon Pt and Ru elution onto the support surface. In addition to the catalyst analysis, the research team also succeeded in characterizing the behaviour of active metal elution and alloy formation from an energetic perspective using a density functional theory-based calculation. In a performance comparison test between the Pt-Ru alloy catalyst against existing single-metal catalysts, the reforming activity was shown to have improved, as it showed a 100% fuel conversion rate even at a low temperature (600oC, compared to the original 800oC). In a long-term durability test (800oC, 200 hours), the catalyst showed commercial stability by successfully producing hydrogen from commercial diesel without performance degradation. The study was conducted by Ph.D. candidate Jaemyung Lee of KAIST’s Department of Mechanical Engineering as the first author. Ph.D. candidate Changho Yeon of KIER, Dr. Jiwoo Oh of KAIST’s Department of Mechanical Engineering, Dr. Gwangwoo Han of KIER, Ph.D. candidate Jeong Do Yoo of KAIST’s Department of Mechanical Engineering, and Dr. Hyung Joong Yun of the Korea Basic Science Institute contributed as co-authors. Dr. Chan-Woo Lee of KIER and Professors Kang Taek Lee and Joongmyeon Bae of KAIST’s Department of Mechanical Engineering contributed as corresponding authors. The research was published in the online version of Applied Catalysis B: Environmental (IF 24.319, JCR 0.93%) on June 17, under the title “Highly Active and Stable Catalyst with Exsolved PtRu Alloy Nanoparticles for Hydrogen Production via Commercial Diesel Reforming”. Professor Joongmyeon Bae said, “The fact that hydrogen can be stably produced from commercial diesel makes this a very meaningful achievement, and we look forward to this technology contributing to the active introduction of mobile fuel cell systems in the early hydrogen economy.” He added, “Our approach to catalyst design may be applied not only to reforming reactions, but also in various other fields.” This research was supported by the National Research Foundation of Korea through funding from the Ministry of Science, ICT and Future Planning. Figure. Schematic diagram of high-performance diesel reforming catalyst with eluted platinum-ruthenium alloy nanoparticles and long-term durability verification experiment results for commercial diesel reforming reaction
2022.09.07
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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
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Thermal Superconductor Lab Becomes the 7th Cross-Generation Collaborative Lab
The Thermal Superconductor Lab led by Senior Professor Sung Jin Kim from the Department of Mechanical Engineering will team up with Junior Professor Youngsuk Nam to develop next-generation superconductors. The two professor team was selected as the 7th Cross-Generation Collaborative Lab last week and will sustain the academic legacy of Professor Kim’s three decades of research on superconductors. The team will continue to develop thin, next-generation superconductors that carry super thermal conductivity using phase transition control technology and thin film packaging. Thin-filmed, next-generation superconductors can be used in various high-temperature flexible electronic devices. The superconductors built inside of the semiconductor device packages will also be used for managing the low-powered but high-performance temperatures of semiconductor and electronic equipment. Professor Kim said, “I am very pleased that my research, know-how, and knowledge from over 30 years of work will continue through the Cross-Generation Collaborative Lab system with Professor Nam. We will spare no effort to advance superconductor technology and play a part in KAIST leading global technology fields.” Junior Professor Nam also stressed that the team is excited to continue its research on crucial technology for managing the temperatures of semiconductors and other electronic equipment. KAIST started this innovative research system in 2018, and in 2021 it established the steering committee to select new labs based on: originality, differentiation, and excellence; academic, social, economic impact; the urgency of cross-generation research; the senior professor’s academic excellence and international reputation; and the senior professor’s research vision. Selected labs receive 500 million KRW in research funding over five years.
2022.01.27
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Eco-Friendly Micro-Supercapacitors Using Fallen Leaves
Green micro-supercapacitors on a single leaf could easily be applied in wearable electronics, smart houses, and IoTs A KAIST research team has developed graphene-inorganic-hybrid micro-supercapacitors made of fallen leaves using femtosecond laser direct writing. The rapid development of wearable electronics requires breakthrough innovations in flexible energy storage devices in which micro-supercapacitors have drawn a great deal of interest due to their high power density, long lifetimes, and short charging times. Recently, there has been an enormous increase in waste batteries owing to the growing demand and the shortened replacement cycle in consumer electronics. The safety and environmental issues involved in the collection, recycling, and processing of such waste batteries are creating a number of challenges. Forests cover about 30 percent of the Earth’s surface and produce a huge amount of fallen leaves. This naturally occurring biomass comes in large quantities and is completely biodegradable, which makes it an attractive sustainable resource. Nevertheless, if the fallen leaves are left neglected instead of being used efficiently, they can contribute to fire hazards, air pollution, and global warming. To solve both problems at once, a research team led by Professor Young-Jin Kim from the Department of Mechanical Engineering and Dr. Hana Yoon from the Korea Institute of Energy Research developed a novel technology that can create 3D porous graphene microelectrodes with high electrical conductivity by irradiating femtosecond laser pulses on the leaves in ambient air. This one-step fabrication does not require any additional materials or pre-treatment. They showed that this technique could quickly and easily produce porous graphene electrodes at a low price, and demonstrated potential applications by fabricating graphene micro-supercapacitors to power an LED and an electronic watch. These results open up a new possibility for the mass production of flexible and green graphene-based electronic devices. Professor Young-Jin Kim said, “Leaves create forest biomass that comes in unmanageable quantities, so using them for next-generation energy storage devices makes it possible for us to reuse waste resources, thereby establishing a virtuous cycle.” This research was published in Advanced Functional Materials last month and was sponsored by the Ministry of Agriculture Food and Rural Affairs, the Korea Forest Service, and the Korea Institute of Energy Research. -Publication Truong-Son Dinh Le, Yeong A. Lee, Han Ku Nam, Kyu Yeon Jang, Dongwook Yang, Byunggi Kim, Kanghoon Yim, Seung Woo Kim, Hana Yoon, and Young-jin Kim, “Green Flexible Graphene-Inorganic-Hybrid Micro-Supercapacitors Made of Fallen Leaves Enabled by Ultrafast Laser Pulses," December 05, 2021, Advanced Functional Materials (doi.org/10.1002/adfm.202107768) -ProfileProfessor Young-Jin KimUltra-Precision Metrology and Manufacturing (UPM2) LaboratoryDepartment of Mechanical EngineeringKAIST
2022.01.27
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AI Light-Field Camera Reads 3D Facial Expressions
Machine-learned, light-field camera reads facial expressions from high-contrast illumination invariant 3D facial images A joint research team led by Professors Ki-Hun Jeong and Doheon Lee from the KAIST Department of Bio and Brain Engineering reported the development of a technique for facial expression detection by merging near-infrared light-field camera techniques with artificial intelligence (AI) technology. Unlike a conventional camera, the light-field camera contains micro-lens arrays in front of the image sensor, which makes the camera small enough to fit into a smart phone, while allowing it to acquire the spatial and directional information of the light with a single shot. The technique has received attention as it can reconstruct images in a variety of ways including multi-views, refocusing, and 3D image acquisition, giving rise to many potential applications. However, the optical crosstalk between shadows caused by external light sources in the environment and the micro-lens has limited existing light-field cameras from being able to provide accurate image contrast and 3D reconstruction. The joint research team applied a vertical-cavity surface-emitting laser (VCSEL) in the near-IR range to stabilize the accuracy of 3D image reconstruction that previously depended on environmental light. When an external light source is shone on a face at 0-, 30-, and 60-degree angles, the light field camera reduces 54% of image reconstruction errors. Additionally, by inserting a light-absorbing layer for visible and near-IR wavelengths between the micro-lens arrays, the team could minimize optical crosstalk while increasing the image contrast by 2.1 times. Through this technique, the team could overcome the limitations of existing light-field cameras and was able to develop their NIR-based light-field camera (NIR-LFC), optimized for the 3D image reconstruction of facial expressions. Using the NIR-LFC, the team acquired high-quality 3D reconstruction images of facial expressions expressing various emotions regardless of the lighting conditions of the surrounding environment. The facial expressions in the acquired 3D images were distinguished through machine learning with an average of 85% accuracy – a statistically significant figure compared to when 2D images were used. Furthermore, by calculating the interdependency of distance information that varies with facial expression in 3D images, the team could identify the information a light-field camera utilizes to distinguish human expressions. Professor Ki-Hun Jeong said, “The sub-miniature light-field camera developed by the research team has the potential to become the new platform to quantitatively analyze the facial expressions and emotions of humans.” To highlight the significance of this research, he added, “It could be applied in various fields including mobile healthcare, field diagnosis, social cognition, and human-machine interactions.” This research was published in Advanced Intelligent Systems online on December 16, under the title, “Machine-Learned Light-field Camera that Reads Facial Expression from High-Contrast and Illumination Invariant 3D Facial Images.” This research was funded by the Ministry of Science and ICT and the Ministry of Trade, Industry and Energy. -Publication“Machine-learned light-field camera that reads fascial expression from high-contrast and illumination invariant 3D facial images,” Sang-In Bae, Sangyeon Lee, Jae-Myeong Kwon, Hyun-Kyung Kim. Kyung-Won Jang, Doheon Lee, Ki-Hun Jeong, Advanced Intelligent Systems, December 16, 2021 (doi.org/10.1002/aisy.202100182) ProfileProfessor Ki-Hun JeongBiophotonic LaboratoryDepartment of Bio and Brain EngineeringKAIST Professor Doheon LeeDepartment of Bio and Brain EngineeringKAIST
2022.01.21
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Face Detection in Untrained Deep Neural Networks
A KAIST team shows that primitive visual selectivity of faces can arise spontaneously in completely untrained deep neural networks Researchers have found that higher visual cognitive functions can arise spontaneously in untrained neural networks. A KAIST research team led by Professor Se-Bum Paik from the Department of Bio and Brain Engineering has shown that visual selectivity of facial images can arise even in completely untrained deep neural networks. This new finding has provided revelatory insights into mechanisms underlying the development of cognitive functions in both biological and artificial neural networks, also making a significant impact on our understanding of the origin of early brain functions before sensory experiences. The study published in Nature Communications on December 16 demonstrates that neuronal activities selective to facial images are observed in randomly initialized deep neural networks in the complete absence of learning, and that they show the characteristics of those observed in biological brains. The ability to identify and recognize faces is a crucial function for social behavior, and this ability is thought to originate from neuronal tuning at the single or multi-neuronal level. Neurons that selectively respond to faces are observed in young animals of various species, and this raises intense debate whether face-selective neurons can arise innately in the brain or if they require visual experience. Using a model neural network that captures properties of the ventral stream of the visual cortex, the research team found that face-selectivity can emerge spontaneously from random feedforward wirings in untrained deep neural networks. The team showed that the character of this innate face-selectivity is comparable to that observed with face-selective neurons in the brain, and that this spontaneous neuronal tuning for faces enables the network to perform face detection tasks. These results imply a possible scenario in which the random feedforward connections that develop in early, untrained networks may be sufficient for initializing primitive visual cognitive functions. Professor Paik said, “Our findings suggest that innate cognitive functions can emerge spontaneously from the statistical complexity embedded in the hierarchical feedforward projection circuitry, even in the complete absence of learning”. He continued, “Our results provide a broad conceptual advance as well as advanced insight into the mechanisms underlying the development of innate functions in both biological and artificial neural networks, which may unravel the mystery of the generation and evolution of intelligence.” This work was supported by the National Research Foundation of Korea (NRF) and by the KAIST singularity research project. -PublicationSeungdae Baek, Min Song, Jaeson Jang, Gwangsu Kim, and Se-Bum Baik, “Face detection in untrained deep neural network,” Nature Communications 12, 7328 on Dec.16, 2021 (https://doi.org/10.1038/s41467-021-27606-9) -ProfileProfessor Se-Bum PaikVisual System and Neural Network LaboratoryProgram of Brain and Cognitive EngineeringDepartment of Bio and Brain EngineeringCollege of EngineeringKAIST
2021.12.21
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KAIST Entrepreneurial Partnership to Accelerate Startups and Venture Ecosystem
KAIST will launch the KAIST Entrepreneurial Partnership (KEP) program, which connects faculty members who own technology with those who want to launch startup. The program encourages open innovation startups using strategies tailored to market-client demand requirements. This is also one of efforts to help realize ‘one startup per lab,’ initiated by President Kwang Hyung Lee’s new innovation strategy. KEP also aims to introduce the best technologies developing at KAIST to startups and to raise the success rate of technology commercialization. The program will match KAIST faculty and student entrepreneur candidates with parties enrolled in the new Entrepreneur in Residence and Entrepreneurial Partner programs. Each team will be given a six-month test period with funding support. KAIST will invite entrepreneurial experts from both technology and management fields to support the program participants. Around 30 experts with experience in developing new businesses, startups, and investments in large corporations or venture companies will be recruited as entrepreneurial partners. They will offer support for research and business development (R&BD), technology marketing, attracting venture investment from corporations, mergers and acquisitions, and business openings. A survey showed that KAIST members who are interested in starting a business are experiencing difficulties finding an entrepreneurial expert (72.2%), with the complicated startup approval procedures (33.3%), and their lack of knowledge on entrepreneurship and funding (27.8%). The KEP program hopes to encourage KAIST faculty members and students who have well-developed business ideas and the appropriate technology but lack the capabilities to realize and develop them into a business. Associate Vice President of Startups Young-Tae Kim said, “We will develop KEP into KAIST’s distinct entrepreneurial support system and produce exemplary outcomes of faculty and student startups. We will spread the startup DNA and lead the building of a virtuous cycle between entrepreneurship and the venture ecosystem.”
2021.10.14
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Defining the Hund Physics Landscape of Two-Orbital Systems
Researchers identify exotic metals in unexpected quantum systems Electrons are ubiquitous among atoms, subatomic tokens of energy that can independently change how a system behaves—but they also can change each other. An international research collaboration found that collectively measuring electrons revealed unique and unanticipated findings. The researchers published their results on May 17 in Physical Review Letters. “It is not feasible to obtain the solution just by tracing the behavior of each individual electron,” said paper author Myung Joon Han, professor of physics at KAIST. “Instead, one should describe or track all the entangled electrons at once. This requires a clever way of treating this entanglement.” Professor Han and the researchers used a recently developed “many-particle” theory to account for the entangled nature of electrons in solids, which approximates how electrons locally interact with one another to predict their global activity. Through this approach, the researchers examined systems with two orbitals — the space in which electrons can inhabit. They found that the electrons locked into parallel arrangements within atom sites in solids. This phenomenon, known as Hund’s coupling, results in a Hund’s metal. This metallic phase, which can give rise to such properties as superconductivity, was thought only to exist in three-orbital systems. “Our finding overturns a conventional viewpoint that at least three orbitals are needed for Hund’s metallicity to emerge,” Professor Han said, noting that two-orbital systems have not been a focus of attention for many physicists. “In addition to this finding of a Hund’s metal, we identified various metallic regimes that can naturally occur in generic, correlated electron materials.” The researchers found four different correlated metals. One stems from the proximity to a Mott insulator, a state of a solid material that should be conductive but actually prevents conduction due to how the electrons interact. The other three metals form as electrons align their magnetic moments — or phases of producing a magnetic field — at various distances from the Mott insulator. Beyond identifying the metal phases, the researchers also suggested classification criteria to define each metal phase in other systems. “This research will help scientists better characterize and understand the deeper nature of so-called ‘strongly correlated materials,’ in which the standard theory of solids breaks down due to the presence of strong Coulomb interactions between electrons,” Professor Han said, referring to the force with which the electrons attract or repel each other. These interactions are not typically present in solid materials but appear in materials with metallic phases. The revelation of metals in two-orbital systems and the ability to determine whole system electron behavior could lead to even more discoveries, according to Professor Han. “This will ultimately enable us to manipulate and control a variety of electron correlation phenomena,” Professor Han said. Co-authors include Siheon Ryee from KAIST and Sangkook Choi from the Condensed Matter Physics and Materials Science Department, Brookhaven National Laboratory in the United States. Korea’s National Research Foundation and the U.S. Department of Energy’s (DOE) Office of Science, Basic Energy Sciences, supported this work. -PublicationSiheon Ryee, Myung Joon Han, and SangKook Choi, 2021.Hund Physics Landscape of Two-Orbital Systems, Physical Review Letters, DOI: 10.1103/PhysRevLett.126.206401 -ProfileProfessor Myung Joon HanDepartment of PhysicsCollege of Natural ScienceKAIST
2021.06.17
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KAIST Technology Value Tops in Commercialization Market
KAIST became the first Korean university to achieve 10.183 billion KRW in annual technology royalties, and was also selected as an ‘Institution of Outstanding Patent Quality Management’ and an ‘Institution of Outstanding Public Patent Technology Transfer’ for 2020. KAIST earns its technology royalties through 56 technology transfer contracts. Following KAIST in the rankings were Seoul National University (SNU) in second place with 8.8 billion KRW from 87 contracts and Korea University (KU) in the third with 5.4 billion KRW from 133 contracts. The data shows the high value of KAIST-created technology in the market. The Korean Intellectual Property Office (KIPO) started to recognize the Institution of Outstanding Patent Quality Management this year to encourage profit-driven patent management at universities and public research institutes, and KAIST was selected as one of the four first recipients of this distinction. In addition, KAIST was selected as an Institution of Outstanding Public Patent Technology Transfer, a title given by KIPO to three universities and public research institutes this year with outstanding achievements in technology transfers and commercialization to encourage patent utilization. Director of the KAIST Institute of Technology Value Creation (ITVC) Professor Kyung-cheol Choi said that KAIST’s achievement in annual technology royalties and technology transfers and commercialization were prime examples of accelerating competitiveness in intellectual property through innovative R&D investment. In April, KAIST expanded and reorganized its Industry-Academia Collaboration Team into the ITVC to support technology transfers and commercialization. Specialized organizations such as the Intellectual Property and Technology Transfer Center and Industrial Liaison Center have been established under the ITVC, and industry experts have been recruited as special professors focusing on industry-academia collaborations to enhance its specialized functions. KAIST also operates an enterprise membership system and technology consulting system, aimed at sharing its outstanding intellectual property within domestic industries. In 2019, it secured a technology transfer commercialization fund of 1.2 billion KRW available for three years under KIPO’s Intellectual Property Profit Reinvestment Support Program (formerly the Korean Patent Gap Fund Creation Project). This program was introduced to bridge the gap between the technology developed in universities and the level of technology required by industry. Under the program, bold investments are made in early-stage technologies at the research paper or experiment phase. The program encourages enterprises to take active steps for the transfer of technologies by demonstrating their commercial potential through prototype production, testing and certification, and standard patent filing. KAIST is currently funding approximately 20 new technologies under this program as of July 2020. KAIST’s outstanding intellectual property management has also received international recognition, with its selection as Asia’s leading institution in university R&D intellectual property at the Intellectual Property Business Congress (IPBC) Asia 2019 held in Tokyo, Japan last October. (END)
2020.08.18
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Professor Sue-Hyun Lee Listed Among WEF 2020 Young Scientists
Professor Sue-Hyun Lee from the Department of Bio and Brain Engineering joined the World Economic Forum (WEF)’s Young Scientists Community on May 26. The class of 2020 comprises 25 leading researchers from 14 countries across the world who are at the forefront of scientific problem-solving and social change. Professor Lee was the only Korean on this year’s roster. The WEF created the Young Scientists Community in 2008 to engage leaders from the public and private sectors with science and the role it plays in society. The WEF selects rising-star academics, 40 and under, from various fields every year, and helps them become stronger ambassadors for science, especially in tackling pressing global challenges including cybersecurity, climate change, poverty, and pandemics. Professor Lee is researching how memories are encoded, recalled, and updated, and how emotional processes affect human memory, in order to ultimately direct the development of therapeutic methods to treat mental disorders. She has made significant contributions to resolving ongoing debates over the maintenance and changes of memory traces in the brain. In recognition of her research excellence, leadership, and commitment to serving society, the President and the Dean of the College of Engineering at KAIST nominated Professor Lee to the WEF’s Class of 2020 Young Scientists Selection Committee. The Committee also acknowledged Professor Lee’s achievements and potential for expanding the boundaries of knowledge and practical applications of science, and accepted her into the Community. During her three-year membership in the Community, Professor Lee will be committed to participating in WEF-initiated activities and events related to promising therapeutic interventions for mental disorders and future directions of artificial intelligence. Seven of this year’s WEF Young Scientists are from Asia, including Professor Lee, while eight are based in Europe. Six study in the Americas, two work in South Africa, and the remaining two in the Middle East. Fourteen, more than half, of the newly announced 25 Young Scientists are women. (END)
2020.05.26
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Cyber MOU Signing with Zhejiang University
KAIST signed an MOU with Zhejiang University (ZJU) in China on March 25. This MOU signing ceremony took place via video conference due to the outbreak of COVID-19. The collaboration with ZJU had already started with the signing of an MOU for cooperation in technology commercialization last December. Possible cooperation initiatives included facilitating joint start-up businesses, patent portfolios, and technology marketing. With this general agreement signing, it is expected that the two institutes will expand mutual exchanges and collaborations at the institutional level for education and research. President Sung-Chul Shin said, “We will work together to devise measures for the systematic advancement of cooperation in various directions, including education, research, and the commercialization of technologies.” ZJU, a member of the C9 League known as China’s Ivy League, was established in 1897 and is located in the city of Hangzhou. Its population across 37 colleges and schools comprises 54,641 students and 3,741 faculty members. The university was ranked 6th in Asia and 54th in the world in the 2020 QS Rankings. (END)
2020.03.30
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