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Metaverse Factory Center to Improve SME’s Competitiveness
The center is expected to enhance the manufacturing competitiveness of SMEs and root industry KAIST opened the ‘Metaverse Factory Experience Center for Manufacturing AI’ on November 1 at the KAIST Bigdata Center for Manufacturing AI. The AI-powered manufacturing metaverse factory will provide real-life experiences for the analysis and application of manufacturing data. Funded by the Ministry of SMEs and Startups, the center is a collaboration with Digiforet, which donated the software system to KAIST. The center allows users to experience the collection, analysis, and utilization process of manufacturing data equivalent to that of real manufacturing sites. Users can connect to the service from anywhere in the world using AR/VR/XR equipment and a metaverse solution, which allows small and middle-sized domestic manufacturing companies to overcome the challenges of entering and selling their production lines overseas in the post-COVID-19 era. The platform is an opportunity for such companies to introduce and export their excellent manufacturing techniques. With the same manufacturing and AI processes of real production sites, the injection molding metaverse factory for plastic screw production runs simulations of the products they will make. Based on the data collection parameters (temperature, pressure, speed, location, time, etc.) built into the Korea AI Manufacturing Platform, an AI-powered SME manufacturing platform, the metaverse factory can detect causes of defects, provide analysis, and guide improvements in productivity and product quality. Starting with the injection molding equipment metaverse factory, the platform aims to expand into plating, welding, molding, casting, forging, and annealing, and become a root industry to contribute greatly to enhancing the manufacturing competitiveness of Korea’s small and middle-sized root industries. Il-Joong Kim, head of the KAIST Manufacturing AI Bigdata Center where the metaverse factory is located, said, “To successfully incorporate manufacturing AI into production sites, it is indispensable that various AI algorithms are tested to optimize decisions. The platform allows users to collect manufacturing data and to experience and test AI analysis simultaneously without interrupting the production process, making it highly effective.” KAIST President Kwang Hyung Lee said, “We will support the close academic-industrial cooperation with Digiforet such as this collaborative for improving SMEs’ competitiveness.” Digiforet CEO Sunghoon Park, who donated a whole HW/SW interface for the construction of the Metaverse Factory Experience Center for Manufacturing AI, said, “I will do my best to realize the best “Metaverse Factory for Manufacturing AI” in the world by combining the AI and bigdata accumulated at KAIST and Digiforet’s XR metaverse technology.”
Hubo Professor Jun-Ho Oh Donates Startup Shares Worth 5 Billion KRW
Rainbow Robotics stock used to endow the development fund Emeritus Professor Jun-Ho Oh, who developed the 2015 DARPA Challenge winning humanoid robot DRC-Hubo, donated 5 billion KRW on October 25 during a ceremony held at the KAIST campus in Daejeon. Professor Oh donated his 20% share (400 shares) of his startup Rainbow Robotics, which was established in 2011. Rainbow Robotics was listed on the KOSDAQ this February. The 400 shares were converted to 200,000 shares with a value of approximately 5 billion KRW when listed this year. KAIST sold the stocks and endowed the Jun-Ho Oh Fund, which will be used for the development of the university. He was the 39th faculty member who launched a startup with technology from his lab and became the biggest faculty entrepreneur donor. “I have received huge support and funding for my research. Fortunately, the research had a good result and led to the startup. Now I am very delighted to pay back the university. I feel that I have played a part in building the school’s startup ecosystem and creating a virtuous circle,” said Professor Oh during the ceremony. KAIST President Kwang Hyung Lee declared, “Professor Oh has been a very impressive exemplary model for our aspiring faculty and student tech startups. We will spare no effort to support startups at KAIST.” Professor Oh, who retired from the Department of Mechanical Engineering last year, now serves as the CTO at Rainbow Robotics. The company is developing humanoid bipedal robots and collaborative robots, and advancing robot technology including parts for astronomical observations. Professor Hae-Won Park and Professor Je Min Hwangbo, who are now responsible for the Hubo Lab, also joined the ceremony along with employees of Rainbow Robotics.
Two Researchers Designated as SUHF Fellows
Professor Taeyun Ku from the Graduate School of Medical Science and Engineering and Professor Hanseul Yang from the Department of Biological Sciences were nominated as 2021 fellows of the Suh Kyungbae Foundation (SUHF). SUHF selected three young promising scientists from 53 researchers who are less than five years into their careers. A panel of judges comprised of scholars from home and abroad made the final selection based on the candidates’ innovativeness and power to influence. Professor You-Bong Hyun from Seoul National University also won the fellowship. Professor Ku’s main topic is opto-connectomics. He will study ways to visualize the complex brain network using innovative technology that transforms neurons into optical elements. Professor Yang will research the possibility of helping patients recover from skin diseases or injuries without scars by studying spiny mouse genes. SUHF was established by Amorepacific Group Chairman Suh Kyungbae in 2016 with 300 billion KRW of his private funds. Under the vision of ‘contributing to humanity by supporting innovative discoveries of bioscience researchers,’ the foundation supports promising Korean scientists who pioneer new fields of research in biological sciences. From 2017 to this year, SUHF has selected 20 promising scientists in the field of biological sciences. Selected scientists are provided with up to KRW 500 million each year for five years. The foundation has provided a total of KRW 48.5 billion in research funds to date.
MCM Utilized at Residential Treatment Center in Gyeonggi
The Mobile Clinic Module (MCM) developed by the KAIST Action for Respiratory Epidemics was installed at special residential treatment center in Gyeonggi Province on September 13. The MCM is an isolate negative pressure unit fitted with high-quality medical equipment, developed by Professor Taek-Jin Nam of the Department of Industrial Design under the KAIST New Deal R&D Initiative. This is also a part of the Korean Disease Control Package Development Project from last July. In January, a ward with four beds for critical care was installed at the Korea Institute for Radiological & Medical Sciences in Seoul for a trial operation, and two mild cases were treated there. It was also implemented as an isolated negative pressure unit in the Daejeon Konyang University Hospital emergency room in June, and has treated 138 cases since. The special residential treatment center installed in the Gyeonggi Provincial Academy gymnasium, which consists of 28 beds in 14 rooms (double occupancy) and a multipurpose room (for X-rays and treatment), is to remain open through October 10. Unlike existing treatment centers that have quarantined COVID-19 patients for two weeks, the Gyeonggi MCM will act as a self-treatment-associated short-term treatment center. While in self-treatment, patients showing symptoms requiring special attention will be moved to the MCM, followed by short-term hospitalization of 1-3 days for observation before further measures are taken. Patients can be treated using the MCM’s own treatment capacities, including in-person and oxygen treatment, X-rays, and IVs. There are individual bathrooms in each room, and the pressure, ventilation, and the automatic opening and closing of the entrance can be centrally monitored and controlled. Patients showing symptoms during treatment will be moved to a specially designated hospital for critical care, and will return to the self-treatment center if no further abnormalities are reported. The Gyeonggi Provincial Medical Center’s Ansung Hospital will take charge of operating the special treatment center. Each day, one or two doctors, three nurses, two nursing assistants, one administrative staff member, two or three disinfection specialists, and a medical imaging engineer will work in three shifts. There will also be about 20 additional specially designated staff members including KAIST researchers, firefighters, and police officers. The MCM was internationally recognized as an excellent medical facility not only for its functionality, economic feasibility, and utility, but also for its unique design and aesthetics. It received two Best of Best awards at the Red Dot Award in product design and Communication Design in user interface. By running this special treatment center, KAIST will conduct research on how to build an optimized model for efficient negative pressure medical units. This research is expected to lead to advances in waste water treatment systems, mobile bathrooms optimized for infectious cases, and MCM user interfaces for electronic devices, etc. Professor Taek-Jin Nam, the general director of the project and design, said “if there is a gymnasium available, we can convert it into a special treatment center fitted with a waste water treatment system, and pressure equipment in two weeks even without additional infrastructure.” The head of the KAIST New Deal R&D Initiative Choongsik Bae said, “our MCM research started in July of last year, and in just over a year, it has become a successful and innovative case that has undergone trials and become commercialized in a short period of time.” He added, “In response to COVID-19, KAIST is conducting research and empirical studies, not just in relation to the MCM, but in other areas of disease control as well.” Based on the excellent disease control technologies developed by KAIST research teams, the KAIST Action for Respiratory Epidemics is conducting technology transfers and industrialization, and is developing a Korean disease control package model
A Mechanism Underlying Most Common Cause of Epileptic Seizures Revealed
An interdisciplinary study shows that neurons carrying somatic mutations in MTOR can lead to focal epileptogenesis via non-cell-autonomous hyperexcitability of nearby nonmutated neurons During fetal development, cells should migrate to the outer edge of the brain to form critical connections for information transfer and regulation in the body. When even a few cells fail to move to the correct location, the neurons become disorganized and this results in focal cortical dysplasia. This condition is the most common cause of seizures that cannot be controlled with medication in children and the second most common cause in adults. Now, an interdisciplinary team studying neurogenetics, neural networks, and neurophysiology at KAIST has revealed how dysfunctions in even a small percentage of cells can cause disorder across the entire brain. They published their results on June 28 in Annals of Neurology. The work builds on a previous finding, also by a KAIST scientists, who found that focal cortical dysplasia was caused by mutations in the cells involved in mTOR, a pathway that regulates signaling between neurons in the brain. “Only 1 to 2% of neurons carrying mutations in the mTOR signaling pathway that regulates cell signaling in the brain have been found to include seizures in animal models of focal cortical dysplasia,” said Professor Jong-Woo Sohn from the Department of Biological Sciences. “The main challenge of this study was to explain how nearby non-mutated neurons are hyperexcitable.” Initially, the researchers hypothesized that the mutated cells affected the number of excitatory and inhibitory synapses in all neurons, mutated or not. These neural gates can trigger or halt activity, respectively, in other neurons. Seizures are a result of extreme activity, called hyperexcitability. If the mutated cells upend the balance and result in more excitatory cells, the researchers thought, it made sense that the cells would be more susceptible to hyperexcitability and, as a result, seizures. “Contrary to our expectations, the synaptic input balance was not changed in either the mutated or non-mutated neurons,” said Professor Jeong Ho Lee from the Graduate School of Medical Science and Engineering. “We turned our attention to a protein overproduced by mutated neurons.” The protein is adenosine kinase, which lowers the concentration of adenosine. This naturally occurring compound is an anticonvulsant and works to relax vessels. In mice engineered to have focal cortical dysplasia, the researchers injected adenosine to replace the levels lowered by the protein. It worked and the neurons became less excitable. “We demonstrated that augmentation of adenosine signaling could attenuate the excitability of non-mutated neurons,” said Professor Se-Bum Paik from the Department of Bio and Brain Engineering. The effect on the non-mutated neurons was the surprising part, according to Paik. “The seizure-triggering hyperexcitability originated not in the mutation-carrying neurons, but instead in the nearby non-mutated neurons,” he said. The mutated neurons excreted more adenosine kinase, reducing the adenosine levels in the local environment of all the cells. With less adenosine, the non-mutated neurons became hyperexcitable, leading to seizures. “While we need further investigate into the relationship between the concentration of adenosine and the increased excitation of nearby neurons, our results support the medical use of drugs to activate adenosine signaling as a possible treatment pathway for focal cortical dysplasia,” Professor Lee said. The Suh Kyungbae Foundation, the Korea Health Technology Research and Development Project, the Ministry of Health & Welfare, and the National Research Foundation in Korea funded this work. -Publication:Koh, H.Y., Jang, J., Ju, S.H., Kim, R., Cho, G.-B., Kim, D.S., Sohn, J.-W., Paik, S.-B. and Lee, J.H. (2021), ‘Non–Cell Autonomous Epileptogenesis in Focal Cortical Dysplasia’ Annals of Neurology, 90: 285 299. (https://doi.org/10.1002/ana.26149) -ProfileProfessor Jeong Ho Lee Translational Neurogenetics Labhttps://tnl.kaist.ac.kr/ Graduate School of Medical Science and Engineering KAIST Professor Se-Bum Paik Visual System and Neural Network Laboratory http://vs.kaist.ac.kr/ Department of Bio and Brain EngineeringKAIST Professor Jong-Woo Sohn Laboratory for Neurophysiology, https://sites.google.com/site/sohnlab2014/home Department of Biological SciencesKAIST Dr. Hyun Yong Koh Translational Neurogenetics LabGraduate School of Medical Science and EngineeringKAIST Dr. Jaeson Jang Ph.D.Visual System and Neural Network LaboratoryDepartment of Bio and Brain Engineering KAIST Sang Hyeon Ju M.D.Laboratory for NeurophysiologyDepartment of Biological SciencesKAIST
KAIST KPC4IR Presents the AI Global Guide for Healthcare
The benchmark for the responsible usage of AI technology in the healthcare sector will promote clarity and high standards for technological applications The KAIST Korea Policy Center for the Fourth Industrial Revolution (KPC4IR) published 'Using AI to Support Healthcare Decisions: A Guide for Society.' This global guide is designed to serve as a benchmark for the responsible usage of AI technologies, and will promote clarity and high standards for technological applications in the healthcare sector. The guide details what should be considered when making clinical decisions to help reduce the chances of the AI giving false or misleading results. The KPC4IR presented the guide in collaboration with the Lloyd’s Register Foundation Institute for the Public Understanding of Risk at the National University of Singapore (NUS IPUR) and Sense about Science, a non-profit organization in the UK specialized in science communication, during the 2021 SIG-KDD (Special Interest Group on Knowledge Discovery and Data Mining) Conference on August 15. AI technology is being widely used in the healthcare sector and has already proved its accuracy and efficiency in diagnosing and predicting diseases. Despite its huge impact on our daily lives in every sector of society, AI technology has some drawbacks and comes with risks, especially due to biased algorithms. “We focused on the ‘reliability’ of AI applications in the healthcare sector to make all data well represented, in good quality. The technology will eventually innovate to better serve the people’s new demand, especially critical demands for safety and precision in healthcare services. This global guide will help both developers and people’s understanding of the appropriate technology applications,” says Director So Young Kim at the KPC4IR. The guide, for instance, says that to scrutinize quality and reliability, the source of the data must be clearly known; the data must have been collected or selected for the purpose it’s being used for; the limitations and assumptions for that purpose have been clearly stated; the biases have been addressed; and it has been properly tested in the real world. It also reflects the importance of the representativeness of data that will affect the accuracy of the AI applications. “By being transparent and demonstrating the steps taken to check that the AI is reliable, researchers and developers can help give people confidence about providing their data,” the guide states. For this guide, the KPC4IR and its collaborators collected data after working with numerous experts from the Graduate School of AI at KAIST, the Science and Technology Policy Institute in Korea, Asan Medical Center in Seoul, Seoul National University Bundang Hospital, and AI solution companies.
KPC4IR Helping to Create Global Standards for Virtual Transactions
KPC4IR will join the task force for the Global Implementation of Travel Rule Standards The KAIST Policy Center for the Fourth Industrial Revolution (KPC4IR) will participate in a global initiative to create global standards for virtual asset transactions. As a member of the GI-TRUST (Global Implementation of Travel Rule Standards) task force, the KPC4IR will develop technical standards and relevant policies that support the global implementation of the travel rule for virtual assets in compliance with the recommendations of the Financial Action Task Force’s (FATF). The FATF is an intergovernmental organization founded in 1989 by the G7 to develop policies to combat money laundering. In June 2019, the FATF extended its Recommendation 16, commonly known as the “travel rule,” to virtual asset services providers (VASPs), requiring both financial institutions and VASPs to aggregate information on the senders and recipients of wire transfers and exchange this information between parties to create a suitable audit trail. According to the FATF’s recommendation and the G20’s support, jurisdictions, especially G20 member countries, have now applied the travel rule to their respective local laws. Korea also amended the Act on Reporting and Using Specified Financial Transaction Information in March 2020 to include virtual assets in their regulatory scope by March 2022. The GI-TRUST task force will collaborate with global and local organizations developing travel rule technologies and offer a neutral assessment of proposed solutions. Their activities are aimed at standardizing related authentication protocols and security technologies that help VASPs comply with the travel rule. The task force will also aid in the pilot testing of travel rule solutions for certain VASPs in Korea. Afterwards, the task force will report on the performance and reliability of the tested travel rule solutions for actual virtual asset transactions, in compliance with the FATF’s guidance. Besides the KPC4IR, the GI-TRUST task force includes the Global Blockchain Business Council (GBBC), International Digital Asset Exchange Association (IDAXA), and Korea Blockchain Association (KBCA). Director of the KPC4IR Professor So Young Kim will co-chair the task force. Professor Kim said their approach should be prudential in dealing with the regulations that rely on secure real-name data on top of the opposing governance style of pseudonymization, distribution, and recombination. She explained, “KAIST has designed the co-evolution of technologies and institutions in conjunction with the global leaders’ groups such as the World Economic Forum and the EC Joint Research Center.” She expects KAIST’s interdisciplinary, global cooperation to untie the entangled problem between regulations and technologies that obstruct future pathways.
VP Sang Yup Lee Honored with the Pony Chung Innovation Award
Vice President for Research Sang Yup Lee became the recipient of the Innovation Award by the Pony Chung Foundation that was established to honor the late Se-yung Chung, the former chairman of Hyundai Development Company. He will receive 200 million KRW in prize money. Chairman Chung developed Korea’s first domestically manufactured automobile, ‘Pony,’ in the mid-1970s that became the cornerstone of Korea’s auto industry today. Distinguished Professor Lee, from the Department of Chemical and Biomolecular Engineering, is a pioneering scholar in the field of systems metabolic engineering who developed various micro-organisms for producing a wide range of fuels, chemicals, materials, and natural compounds. He recently was elected as a foreign member of the Royal Society in the UK and is the first Korean ever elected into the National Academy of Inventors (NAI) in the US as well as one of 13 scholars elected as an International Member of both the National Academy of Sciences (NAS) and the National Academy of Engineering (NAE) in the US.
Professor Jung Receives the Hansong Science Award
Professor Yousung Jung of the Department of Chemical and Biomolecular Engineering has been selected as the recipient of the 5th Hansong Science Award in Chemistry. The award recognizes young and mid-career scholars who made outstanding achievement in physics, chemistry, and life sciences. Recipients receive 50 million KRW in prize money. Professor Jung was recognized for finding a new way to predict synthesis potentials when designing data-based materials and molecules through AI-powered inverse technology. Conventionally, new material discovery mainly relied on a method where the new materials were proposed by an expert’s intuition or experimental trial, then synthesized to measure the properties of the material before it was used. However, this method took a lot of time, which resulted in an inefficient discovery process. Professor Jung’s AI reverse design technology is reported to be more efficient for discovering new materials by finding crystal structures with desired properties using data and AI algorithms. "AI reverse design technology can accelerate the development of new materials and new drugs," Professor Jung said. "It can be used as an algorithm for future autonomous laboratories implemented by robots, algorithms, and data without human intervention," he added.
Hydrogel-Based Flexible Brain-Machine Interface
The interface is easy to insert into the body when dry, but behaves ‘stealthily’ inside the brain when wet Professor Seongjun Park’s research team and collaborators revealed a newly developed hydrogel-based flexible brain-machine interface. To study the structure of the brain or to identify and treat neurological diseases, it is crucial to develop an interface that can stimulate the brain and detect its signals in real time. However, existing neural interfaces are mechanically and chemically different from real brain tissue. This causes foreign body response and forms an insulating layer (glial scar) around the interface, which shortens its lifespan. To solve this problem, the research team developed a ‘brain-mimicking interface’ by inserting a custom-made multifunctional fiber bundle into the hydrogel body. The device is composed not only of an optical fiber that controls specific nerve cells with light in order to perform optogenetic procedures, but it also has an electrode bundle to read brain signals and a microfluidic channel to deliver drugs to the brain. The interface is easy to insert into the body when dry, as hydrogels become solid. But once in the body, the hydrogel will quickly absorb body fluids and resemble the properties of its surrounding tissues, thereby minimizing foreign body response. The research team applied the device on animal models, and showed that it was possible to detect neural signals for up to six months, which is far beyond what had been previously recorded. It was also possible to conduct long-term optogenetic and behavioral experiments on freely moving mice with a significant reduction in foreign body responses such as glial and immunological activation compared to existing devices. “This research is significant in that it was the first to utilize a hydrogel as part of a multifunctional neural interface probe, which increased its lifespan dramatically,” said Professor Park. “With our discovery, we look forward to advancements in research on neurological disorders like Alzheimer’s or Parkinson’s disease that require long-term observation.” The research was published in Nature Communications on June 8, 2021. (Title: Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity) The study was conducted jointly with an MIT research team composed of Professor Polina Anikeeva, Professor Xuanhe Zhao, and Dr. Hyunwoo Yook. This research was supported by the National Research Foundation (NRF) grant for emerging research, Korea Medical Device Development Fund, KK-JRC Smart Project, KAIST Global Initiative Program, and Post-AI Project. -PublicationPark, S., Yuk, H., Zhao, R. et al. Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity. Nat Commun 12, 3435 (2021). https://doi.org/10.1038/s41467-021-23802-9 -ProfileProfessor Seongjun ParkBio and Neural Interfaces LaboratoryDepartment of Bio and Brain EngineeringKAIST
Repurposed Drugs Present New Strategy for Treating COVID-19
Virtual screening of 6,218 drugs and cell-based assays identifies best therapeutic medication candidates A joint research group from KAIST and Institut Pasteur Korea has identified repurposed drugs for COVID-19 treatment through virtual screening and cell-based assays. The research team suggested the strategy for virtual screening with greatly reduced false positives by incorporating pre-docking filtering based on shape similarity and post-docking filtering based on interaction similarity. This strategy will help develop therapeutic medications for COVID-19 and other antiviral diseases more rapidly. This study was reported at the Proceedings of the National Academy of Sciences of the United States of America (PNAS). Researchers screened 6,218 drugs from a collection of FDA-approved drugs or those under clinical trial and identified 38 potential repurposed drugs for COVID-19 with this strategy. Among them, seven compounds inhibited SARS-CoV-2 replication in Vero cells. Three of these drugs, emodin, omipalisib, and tipifarnib, showed anti-SARS-CoV-2 activity in human lung cells, Calu-3. Drug repurposing is a practical strategy for developing antiviral drugs in a short period of time, especially during a global pandemic. In many instances, drug repurposing starts with the virtual screening of approved drugs. However, the actual hit rate of virtual screening is low and most of the predicted drug candidates are false positives. The research group developed effective filtering algorithms before and after the docking simulations to improve the hit rates. In the pre-docking filtering process, compounds with similar shapes to the known active compounds for each target protein were selected and used for docking simulations. In the post-docking filtering process, the chemicals identified through their docking simulations were evaluated considering the docking energy and the similarity of the protein-ligand interactions with the known active compounds. The experimental results showed that the virtual screening strategy reached a high hit rate of 18.4%, leading to the identification of seven potential drugs out of the 38 drugs initially selected. “We plan to conduct further preclinical trials for optimizing drug concentrations as one of the three candidates didn’t resolve the toxicity issues in preclinical trials,” said Woo Dae Jang, one of the researchers from KAIST. “The most important part of this research is that we developed a platform technology that can rapidly identify novel compounds for COVID-19 treatment. If we use this technology, we will be able to quickly respond to new infectious diseases as well as variants of the coronavirus,” said Distinguished Professor Sang Yup Lee. This work was supported by the KAIST Mobile Clinic Module Project funded by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF). The National Culture Collection for Pathogens in Korea provided the SARS-CoV-2 (NCCP43326). -PublicationWoo Dae Jang, Sangeun Jeon, Seungtaek Kim, and Sang Yup Lee. Drugs repurposed for COVID-19 by virtual screening of 6,218 drugs and cell-based assay. Proc. Natl. Acad. Sci. U.S.A. (https://doi/org/10.1073/pnas.2024302118) -ProfileDistinguished Professor Sang Yup LeeMetabolic &Biomolecular Engineering National Research Laboratoryhttp://mbel.kaist.ac.kr Department of Chemical and Biomolecular EngineeringKAIST
Prof. Sang Wan Lee Selected for 2021 IBM Academic Award
Professor Sang Wan Lee from the Department of Bio and Brain Engineering was selected as the recipient of the 2021 IBM Global University Program Academic Award. The award recognizes individual faculty members whose emerging science and technology contains significant interest for universities and IBM. Professor Lee, whose research focuses on artificial intelligence and computational neuroscience, won the award for his research proposal titled A Neuroscience-Inspired Approach for Metacognitive Reinforcement Learning. IBM provides a gift of $40,000 to the recipient’s institution in recognition of the selection of the project but not as a contract for services. Professor Lee’s project aims to exploit the unique characteristics of human reinforcement learning. Specifically, he plans to examines the hypothesis that metacognition, a human’s ability to estimate their uncertainty level, serves to guide sample-efficient and near-optimal exploration, making it possible to achieve an optimal balance between model-based and model-free reinforcement learning. He was also selected as the winner of the Google Research Award in 2016 and has been working with DeepMind and University College London to conduct basic research on decision-making brain science to establish a theory on frontal lobe meta-enhance learning. "We plan to conduct joint research for utilizing brain-based artificial intelligence technology and frontal lobe meta-enhanced learning technology modeling in collaboration with an international research team including IBM, DeepMind, MIT, and Oxford,” Professor Lee said.
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