Global
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KPC4IR Publishes Global Standards Mapping Initiative 2.0
The report highlights South Korea as an early adopter of blockchain in policy and business
The KAIST Policy Center for the 4IR (KPC4IR), one of the nine working groups of the Global Blockchain Business Council (GBBC), published the Global Standards Mapping Initiative (GSMI) 2.0, highlighting Korea as an early adopter of blockchain. The report also offers an overview of how blockchain was adopted through an analysis of policy and business cases of South Korea.
In partnership with 131 institutions, GSMI 2.0 maps, catalogues, and analyzes data from 187 jurisdictions, 479 industry consortia, 38 technical standards, and 389 university courses and degree programs to provide a holistic view of the industry’s global activity.
Among the nine working groups, KAIST is the sole investigator for researching South Korea’s adoption of blockchain for policy and business. It says that in terms of policy and regulations for blockchain as a virtual asset, South Korea amended the Act on Reporting and Using Specific Financial Transaction Information to comply with the Financial Action Task Force’s recommendations.
The report also reviewed South Korea’s blockchain R&D. Seventeen ministries have funded 417 projects to cultivate blockchain inventions since 2015. Significantly, the Ministry of Science and ICT’s Blockchain Convergence Technology Development Program supported 50 projects between 2018 and 2021. Their R&D focused on virtual assets during the initial stage in 2015 and soon shifted its application to various domains, including identification and logistics.
The report noted that the Korea Customs Service was one of the first agencies in the world to introduce blockchain into customs clearance. Through collaborations with the private sector, the Korean government has also created the world’s first blockchain-based vaccination certification services and extended it to a globally integrated decentralized identity system.
Finally, the report states that these South Korean cases highlight three ambiguities in blockchain policies. First, blockchain involves both financial and industrial features. Thus, it needs a new regulatory framework that embraces the two features together.
Second, integrating services on a blockchain platform will bring forth seamless automation of industries across the manufacturing, financial, and public sectors. South Korea, which already has well-proven manufacturing capabilities, is in need of a comprehensive strategy to encompass multiple services on one platform.
Third, the two cases of the government’s adoption of blockchain suggest that innovations in blockchain can be facilitated through effective cooperation among government ministries and agencies regarding particular businesses in the private sector. Consequently, the government’s policy is not simply to invest in virtual assets but also to develop a virtual-physical world woven by blockchain. The new environment demands that South Korea transform its policy stances on blockchain, from specialization to comprehensiveness and cooperation.
Professor So Young Kim who heads the center said, “This report shows the main lessons from South Korea for other countries adopting blockchain. We will continue to work closely with our partners including the World Economic Forum to investigate many other global issues.”
2021.12.21 View 4823 -
Deep Learning Framework to Enable Material Design in Unseen Domain
Researchers propose a deep neural network-based forward design space exploration using active transfer learning and data augmentation
A new study proposed a deep neural network-based forward design approach that enables an efficient search for superior materials far beyond the domain of the initial training set. This approach compensates for the weak predictive power of neural networks on an unseen domain through gradual updates of the neural network with active transfer learning and data augmentation methods.
Professor Seungwha Ryu believes that this study will help address a variety of optimization problems that have an astronomical number of possible design configurations. For the grid composite optimization problem, the proposed framework was able to provide excellent designs close to the global optima, even with the addition of a very small dataset corresponding to less than 0.5% of the initial training data-set size. This study was reported in npj Computational Materials last month.
“We wanted to mitigate the limitation of the neural network, weak predictive power beyond the training set domain for the material or structure design,” said Professor Ryu from the Department of Mechanical Engineering.
Neural network-based generative models have been actively investigated as an inverse design method for finding novel materials in a vast design space. However, the applicability of conventional generative models is limited because they cannot access data outside the range of training sets. Advanced generative models that were devised to overcome this limitation also suffer from weak predictive power for the unseen domain.
Professor Ryu’s team, in collaboration with researchers from Professor Grace Gu’s group at UC Berkeley, devised a design method that simultaneously expands the domain using the strong predictive power of a deep neural network and searches for the optimal design by repetitively performing three key steps.
First, it searches for few candidates with improved properties located close to the training set via genetic algorithms, by mixing superior designs within the training set. Then, it checks to see if the candidates really have improved properties, and expands the training set by duplicating the validated designs via a data augmentation method. Finally, they can expand the reliable prediction domain by updating the neural network with the new superior designs via transfer learning. Because the expansion proceeds along relatively narrow but correct routes toward the optimal design (depicted in the schematic of Fig. 1), the framework enables an efficient search.
As a data-hungry method, a deep neural network model tends to have reliable predictive power only within and near the domain of the training set. When the optimal configuration of materials and structures lies far beyond the initial training set, which frequently is the case, neural network-based design methods suffer from weak predictive power and become inefficient.
Researchers expect that the framework will be applicable for a wide range of optimization problems in other science and engineering disciplines with astronomically large design space, because it provides an efficient way of gradually expanding the reliable prediction domain toward the target design while avoiding the risk of being stuck in local minima. Especially, being a less-data-hungry method, design problems in which data generation is time-consuming and expensive will benefit most from this new framework.
The research team is currently applying the optimization framework for the design task of metamaterial structures, segmented thermoelectric generators, and optimal sensor distributions. “From these sets of on-going studies, we expect to better recognize the pros and cons, and the potential of the suggested algorithm. Ultimately, we want to devise more efficient machine learning-based design approaches,” explained Professor Ryu.This study was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research Project.
-Publication
Yongtae Kim, Youngsoo, Charles Yang, Kundo Park, Grace X. Gu, and Seunghwa Ryu, “Deep learning framework for material design space exploration using active transfer learning and data augmentation,” npj Computational Materials (https://doi.org/10.1038/s41524-021-00609-2)
-Profile
Professor Seunghwa Ryu
Mechanics & Materials Modeling Lab
Department of Mechanical Engineering
KAIST
2021.09.29 View 9389 -
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.
2021.07.30 View 7082 -
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.
2021.06.25 View 9224 -
KPC4IR Leads the Global Blockchain Standards Via Korea Innovation Studies
The Korea Policy Center for the Fourth Industrial Revolution (KPC4IR) at KAIST will play a leading role in the Global Standards Mapping Initiative (GSMI) 2.0 as the Chair of Working Group on South Korea at the Global Blockchain Business Council (GBBC). The GBBC, a Swiss-based non-profit consortium, established the GSMI to map blockchain technology ecosystem, established the GSMI to map blockchain and digital asset standards and regulation globally. The initial release of the GSMI mapped data and outputs from ons, 185 jurisdictions, nearly 400 industry groups, and over 30 technical standard-setting entities.
The GSMI Working Group on South Korea is the only group that will investigate the country-level innovation of blockchain and digital asset alongside six Korean blockchain associations: The GSMI Working Group on South Korea is the only group that will investigate the country-level innovation of blockchain and digital asset alongside six Korean blockchain associations: the Korea Blockchain Association, the Korea Society of Blockchain, Blockchain & Law, the Open Blockchain and DID Association, the Korea Blockchain Startup Association, and the Korea Blockchain Industry Promotion Association. Individual members also joined from the Inter-American Development Bank, Blockchain Labs, and GOPAX.
The GSMI Working Group on South Korea, chaired by KAIST, will leverage their experience in blockchain adoption to assist in setting global standards for the ecosystem. The Group will also highlight how South Korea can be a testbed for ITC adoption and open the door to a blockchain-ready world.
GSMI 2.0 is spearheaded by nine working groups chaired by institutions, such as the World Economic Forum and the GBBC, Ernst & Young, HM Revenue and Customs, Accenture, and Hyperledger - Linux Foundation. Each of the Working Groups will be supported by sixteen fellows from eight fellow program partners. KAIST student Yujin Bang is the South Korea Working Group fellow. The GBBC and the WEF already published the first volume of the GSMI in October 2020 in collaboration with world-leading institutions, including KAIST, MIT Media Lab, and Accenture.
Director of the KPC4IR Professor So Young Kim said, “The designation of KAIST is the result of continued collaborations with the WEF. The participation of this working group will help Korea’s global leadership with blockchain standards.”
2021.05.18 View 6190 -
KAIST Listed as Top 100 Global Innovator by Clarivate
KAIST was named as one of the Top 100 Global Innovators 2021 by Clarivate. Among the top 100, 42 US corporations, including Amazon, Apple, Google, and Facebook, and 29 Japanese corporations made the list. The list included four Korean corporations Samsung Electronics, LG Electronics, LS Electronics, and SK Telecommunications. KAIST, the only university listed as a global innovator, regained its place in the Top 100 Global Innovators this year after last being named in 2013. Industrywide, the electronics and semiconductor sectors took the majority of the top global innovators spots with 21 and 12 corporations respectively.
President Kwang Hyung Lee received the trophy from Clarivate Korea Regional Director Seongsik Ahn on May 12 at KAIST’s main campus. President Lee said, “We are glad that our continued innovation efforts are receiving worldwide recognition and will continue to strive for sustainable growth as a university that creates global value and impact.”
Every year since 2012, the Top 100 Global Innovators has identified companies and institutions at the pinnacle of the global innovation landscape by measuring the ideation culture that produces patents and puts them at the forefront. Clarivate tracks innovation based on four factors: 1. volume of patents 2. influence 3. Success and 4. globalization using patents, patents indices, and citation index solutions.
For measuring the patent volume, the Top 100 candidate must meet a threshold of 100 granted patents received in the past five years and more than 500 in the Derwent World Patents Index over any time period. Clarivate assesses the level of influence of the patented ideas by reviewing the number of external citations their inventions received over the past five years. For measuring success, they look at how successful each candidate has been getting their applications for patent protection approved by patent offices around the world over past five years. Globalization measures the investment levels of each candidate in their patent applications, a metric designed to assess both the importance of invention to the companies as well as the footprint of commercialization.
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2021.05.12 View 4617 -
Observing Individual Atoms in 3D Nanomaterials and Their Surfaces
Atoms are the basic building blocks for all materials. To tailor functional properties, it is essential to accurately determine their atomic structures. KAIST researchers observed the 3D atomic structure of a nanoparticle at the atom level via neural network-assisted atomic electron tomography.
Using a platinum nanoparticle as a model system, a research team led by Professor Yongsoo Yang demonstrated that an atomicity-based deep learning approach can reliably identify the 3D surface atomic structure with a precision of 15 picometers (only about 1/3 of a hydrogen atom’s radius). The atomic displacement, strain, and facet analysis revealed that the surface atomic structure and strain are related to both the shape of the nanoparticle and the particle-substrate interface.
Combined with quantum mechanical calculations such as density functional theory, the ability to precisely identify surface atomic structure will serve as a powerful key for understanding catalytic performance and oxidation effect.
“We solved the problem of determining the 3D surface atomic structure of nanomaterials in a reliable manner. It has been difficult to accurately measure the surface atomic structures due to the ‘missing wedge problem’ in electron tomography, which arises from geometrical limitations, allowing only part of a full tomographic angular range to be measured. We resolved the problem using a deep learning-based approach,” explained Professor Yang.
The missing wedge problem results in elongation and ringing artifacts, negatively affecting the accuracy of the atomic structure determined from the tomogram, especially for identifying the surface structures. The missing wedge problem has been the main roadblock for the precise determination of the 3D surface atomic structures of nanomaterials.
The team used atomic electron tomography (AET), which is basically a very high-resolution CT scan for nanomaterials using transmission electron microscopes. AET allows individual atom level 3D atomic structural determination.
“The main idea behind this deep learning-based approach is atomicity—the fact that all matter is composed of atoms. This means that true atomic resolution electron tomogram should only contain sharp 3D atomic potentials convolved with the electron beam profile,” said Professor Yang.
“A deep neural network can be trained using simulated tomograms that suffer from missing wedges as inputs, and the ground truth 3D atomic volumes as targets. The trained deep learning network effectively augments the imperfect tomograms and removes the artifacts resulting from the missing wedge problem.”
The precision of 3D atomic structure can be enhanced by nearly 70% by applying the deep learning-based augmentation. The accuracy of surface atom identification was also significantly improved.
Structure-property relationships of functional nanomaterials, especially the ones that strongly depend on the surface structures, such as catalytic properties for fuel-cell applications, can now be revealed at one of the most fundamental scales: the atomic scale.
Professor Yang concluded, “We would like to fully map out the 3D atomic structure with higher precision and better elemental specificity. And not being limited to atomic structures, we aim to measure the physical, chemical, and functional properties of nanomaterials at the 3D atomic scale by further advancing electron tomography techniques.”
This research, reported at Nature Communications, was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research M3I3 Project.
-Publication
Juhyeok Lee, Chaehwa Jeong & Yongsoo Yang
“Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography”
Nature Communications
-Profile
Professor Yongsoo Yang
Department of Physics
Multi-Dimensional Atomic Imaging Lab (MDAIL)
http://mdail.kaist.ac.kr
KAIST
2021.05.12 View 9591 -
Streamlining the Process of Materials Discovery
The materials platform M3I3 reduces the time for materials discovery by reverse engineering future materials using multiscale/multimodal imaging and machine learning of the processing-structure-properties relationship
Developing new materials and novel processes has continued to change the world. The M3I3 Initiative at KAIST has led to new insights into advancing materials development by implementing breakthroughs in materials imaging that have created a paradigm shift in the discovery of materials. The Initiative features the multiscale modeling and imaging of structure and property relationships and materials hierarchies combined with the latest material-processing data.
The research team led by Professor Seungbum Hong analyzed the materials research projects reported by leading global institutes and research groups, and derived a quantitative model using machine learning with a scientific interpretation. This process embodies the research goal of the M3I3: Materials and Molecular Modeling, Imaging, Informatics and Integration.
The researchers discussed the role of multiscale materials and molecular imaging combined with machine learning and also presented a future outlook for developments and the major challenges of M3I3. By building this model, the research team envisions creating desired sets of properties for materials and obtaining the optimum processing recipes to synthesize them.
“The development of various microscopy and diffraction tools with the ability to map the structure, property, and performance of materials at multiscale levels and in real time enabled us to think that materials imaging could radically accelerate materials discovery and development,” says Professor Hong.
“We plan to build an M3I3 repository of searchable structural and property maps using FAIR (Findable, Accessible, Interoperable, and Reusable) principles to standardize best practices as well as streamline the training of early career researchers.”
One of the examples that shows the power of structure-property imaging at the nanoscale is the development of future materials for emerging nonvolatile memory devices. Specifically, the research team focused on microscopy using photons, electrons, and physical probes on the multiscale structural hierarchy, as well as structure-property relationships to enhance the performance of memory devices.
“M3I3 is an algorithm for performing the reverse engineering of future materials. Reverse engineering starts by analyzing the structure and composition of cutting-edge materials or products. Once the research team determines the performance of our targeted future materials, we need to know the candidate structures and compositions for producing the future materials.”
The research team has built a data-driven experimental design based on traditional NCM (nickel, cobalt, and manganese) cathode materials. With this, the research team expanded their future direction for achieving even higher discharge capacity, which can be realized via Li-rich cathodes.
However, one of the major challenges was the limitation of available data that describes the Li-rich cathode properties. To mitigate this problem, the researchers proposed two solutions: First, they should build a machine-learning-guided data generator for data augmentation. Second, they would use a machine-learning method based on ‘transfer learning.’ Since the NCM cathode database shares a common feature with a Li-rich cathode, one could consider repurposing the NCM trained model for assisting the Li-rich prediction. With the pretrained model and transfer learning, the team expects to achieve outstanding predictions for Li-rich cathodes even with the small data set.
With advances in experimental imaging and the availability of well-resolved information and big data, along with significant advances in high-performance computing and a worldwide thrust toward a general, collaborative, integrative, and on-demand research platform, there is a clear confluence in the required capabilities of advancing the M3I3 Initiative.
Professor Hong said, “Once we succeed in using the inverse “property−structure−processing” solver to develop cathode, anode, electrolyte, and membrane materials for high energy density Li-ion batteries, we will expand our scope of materials to battery/fuel cells, aerospace, automobiles, food, medicine, and cosmetic materials.”
The review was published in ACS Nano in March. This study was conducted through collaborations with Dr. Chi Hao Liow, Professor Jong Min Yuk, Professor Hye Ryung Byon, Professor Yongsoo Yang, Professor EunAe Cho, Professor Pyuck-Pa Choi, and Professor Hyuck Mo Lee at KAIST, Professor Joshua C. Agar at Lehigh University, Dr. Sergei V. Kalinin at Oak Ridge National Laboratory, Professor Peter W. Voorhees at Northwestern University, and Professor Peter Littlewood at the University of Chicago (Article title: Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration).This work was supported by the KAIST Global Singularity Research Program for 2019 and 2020.
Publication:
“Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics and Integration,” S. Hong, C. H. Liow, J. M. Yuk, H. R. Byon, Y. Yang, E. Cho, J. Yeom, G. Park, H. Kang, S. Kim, Y. Shim, M. Na, C. Jeong, G. Hwang, H. Kim, H. Kim, S. Eom, S. Cho, H. Jun, Y. Lee, A. Baucour, K. Bang, M. Kim, S. Yun, J. Ryu, Y. Han, A. Jetybayeva, P.-P. Choi, J. C. Agar, S. V. Kalinin, P. W. Voorhees, P. Littlewood, and H. M. Lee, ACS Nano 15, 3, 3971–3995 (2021) https://doi.org/10.1021/acsnano.1c00211
Profile:
Seungbum Hong, PhD
Associate Professor
seungbum@kaist.ac.kr
http://mii.kaist.ac.kr
Department of Materials Science and Engineering
KAIST
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2021.04.05 View 11155 -
‘WalkON Suit 4’ Releases Paraplegics from Wheelchairs
- KAIST Athletes in ‘WalkON Suit 4’ Dominated the Cybathlon 2020 Global Edition. -
Paraplegic athletes Byeong-Uk Kim and Joohyun Lee from KAIST’s Team Angel Robotics won a gold and a bronze medal respectively at the Cybathlon 2020 Global Edition last week. ‘WalkON Suit 4,’ a wearable robot developed by the Professor Kyoungchul Kong’s team from the Department of Mechanical Engineering topped the standings at the event with double medal success.
Kim, the former bronze medallist, clinched his gold medal by finishing all six tasks in 3 minutes and 47 seconds, whereas Lee came in third with a time of 5 minutes and 51 seconds. TWIICE, a Swiss team, lagged 53 seconds behind Kim’s winning time to be the runner-up.
Cybathlon is a global championship, organized by ETH Zurich, which brings together people with physical disabilities to compete using state-of-the-art assistive technologies to perform everyday tasks. The first championship was held in 2016 in Zurich, Switzerland.
Due to the COVID-19 pandemic, the second championship was postponed twice and held in a new format in a decentralized setting. A total of 51 teams from 20 countries across the world performed the events in their home bases in different time zones instead of traveling to Zurich. Under the supervision of a referee and timekeeper, all races were filmed and then reviewed by judges.
KAIST’s Team Angel Robotics participated in the Powered Exoskeleton Race category, where nine pilots representing five nations including Korea, Switzerland, the US, Russia, and France competed against each other.
The team installed their own arena and raced at the KAIST Main Campus in Daejeon according to the framework, tasks, and rules defined by the competition committee. The two paraplegic pilots were each equipped with exoskeletal devices, the WalkON Suit 4, and undertook six tasks related to daily activities.
The WalkON Suit 4 recorded the fastest walking speed for a complete paraplegic ever reported. For a continuous walk, it achieved a maximum speed of 40 meters per minute. This is comparable to the average walking pace of a non-disabled person, which is around two to four kilometers per hour.
The research team raised the functionality of the robot by adding technology that can observe the user’s level of anxiety and external factors like the state of the walking surface, so it can control itself intelligently. The assistive functions a robot should provide vary greatly with the environment, and the WalkON Suit 4 made it possible to analyze the pace of the user within 30 steps and provide a personally optimized walking pattern, enabling a high walking speed.
The six tasks that Kim and Lee had to complete were:1) sitting and standing back up, 2) navigating around obstacles while avoiding collisions, 3) stepping over obstacles on the ground, 4) going up and down stairs, 5) walking across a tilted path, and 6) climbing a steep slope, opening and closing a door, and descending a steep slope.
Points were given based on the accuracy of each completed task, and the final scores were calculated by adding all of the points that were gained in each attempt, which lasted 10 minutes. Each pilot was given three opportunities and used his/her highest score. Should pilots have the same final score, the pilot who completed the race in the shortest amount of time would win.
Kim said in his victory speech that he was so thrilled to see all his and fellow researchers’ years of hard work paying off. “This will be a good opportunity to show how outstanding Korean wearable robot technologies are,” he added.
Lee, who participated in the competition for the first time, said, “By showing that I can overcome my physical disabilities with robot technology, I’d like to send out a message of hope to everyone who is tired because of COVID-19”.
Professor Kong’s team collaborated in technology development and pilot training with their colleagues from Angel Robotics Co., Ltd., Severance Rehabilitation Hospital, Yeungnam University, Stalks, and the Institute of Rehabilitation Technology.
Footage from the competition is available at the Cybathlon’s official website.
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2020.11.20 View 7597 -
PhD Graduate Mekuria Teklemariam Inspired to Better Serve Ethiopia
Ethiopia’s Former Minister of Urban Development and Housing Mekuria Teklemariam became a KAIST alumnus, earning his PhD in the Global IT Technology Program (ITTP) last month. Dr. Telkemariam completed his degree summa cum laude in business administration in four years. He is the highest-ranking official among the ITTP Program recipients.
Dr. Teklemarian cited the ‘Saemaul Undong,’ also known as the New Community Movement as well as the strong infrastructure of IT industry as part of the driving forces behind Korea’s rapid economic success and this inspired him to choose KAIST as his academic destination.
The Global ITTP was launched in 2006 to educate elite public officials from diverse countries on information and communication technology. This program has played a vital role in transferring Korea’s advanced information and communications technology to many countries whose industries are in the budding stages.
Approximately 200 officials from over 50 countries have enrolled in the ITTP program, and the program has expanded to cover diverse areas of ICT and grown into a global network of ICT leaders abroad. The 2020 Class graduated five PhDs and five master’s degree holders.
Dr. Teklemariam plans to benchmark Korea to aid the development of Ethiopia when he returns home. “Korea is a country that has made remarkable progress in all areas including politics and economics in the last few decades, emerged from one of the poorest countries in the 1960s to be among the largest economies in the world today,” Dr. Telkemariam said.
“So I wanted to study what transformed Korea to make such a miraculous transformation academically for my country’s own development too,” he added, explaining his motivation to study in Korea. He also cited diverse IT education programs for the elderly as a Korean policy he would like to see applied in his country.
The 50-year-old former minister and incumbent urban affairs advisor to the prime minister of Ethiopia was elected to the country's parliament a decade ago, becoming the youngest member in Ethiopian history. He has led the economic development of Ethiopia in the areas of smart city development, land management, and housing development policies.
While studying at KAIST, Dr. Telkemariam became the two-time winner of the Outstanding Collaborative Research Award presented by the KAIST Institute for IT Convergence through collaborative research with the National IT Industry Promotion Agency (NIPA) and the Science and Technology Policy Institute (STEPI).
In addition, his graduation thesis, "Differentiating mobile broadband policies across diffusion stages: A panel data analysis" was published in Telecommunications Policy.
President Sung-Chul Shin met with him during a luncheon meeting before he returned to home. During the meeting Dr. Telkemariam said, “I was impressed by the Korean people, who not only work hard to do their part wherever they are, but also put whatever they say into practice. I will apply and practice what I have learned from Korea and KAIST to Ethiopia.” President Shin responded, “We shall seek to find ways to cooperate that can be practically used to expand exchanges between the two countries.”
2020.09.21 View 6523 -
Life After COVID-19: Big Questions on Medical and Bio-Engineering
KAIST GSI forum explores big questions in the medical and bio-engineering revolution caused by the COVID-19 in fight against infectious diseases and life quality
On September 9, the Global Strategy Institute at KAIST will delve into innovative future strategies for the medical and bio-engineering sectors that have been disrupted by COVID-19. The forum will live stream via YouTube, KTV, and Naver TV from 9:00 am Korean time.
The online forum features a speaker lineup of world-renowned scholars who will discuss an array of bio-engineering technologies that will improve our quality of life and even extend our life span. This is the GSI’s third online forum since the first one in April that covered the socio-economic implications of the global pandemic and the second one in June focusing on the education sector.
In hosting the third round of the GSI Forum series, KAIST President Sung-Chul Shin stressed the power of science and technology saying, “In this world full of uncertainties, one thing for sure is that only the advancement of science and technology will deliver us from this crisis.” Korean Prime Minister Sye-Kyun Chung will also deliver a speech explaining the government’s response to COVID-19 and vaccine development strategies.
The President of the National Academy of Medicine in the US will share ideal policies to back up the bio-engineering and medical sectors and Futurist Thomas Frey from the Davinci Institute will present his distinct perspectives on our future lives after COVID-19. His thought-provoking insights on advancements in the bioengineering sector will examine whether humanity can put an end to infectious diseases and find new ways to lengthen our lives.
Two distinguished professors in the field of genetic engineering technology will share their latest breakthroughs. Professor George McDonald Church from Harvard Medical School who developed genome sequencing will deliver a keynote speech on how the advancement of gene editing and genome technology will overcome diseases and contribute to extending human life spans.
Professor Kwang-Soo Kim, a KAIST alumnus from Harvard Medical School who recently reported new discoveries for Parkinson’s disease treatment by reprogramming a patient’s own skin cells to replace cells in the brain, will introduce the latest clinical cell treatment technologies based on personalized therapeutics.
Senior Vice President and Chief Product Officer of Illumina Susan Tousi, a leading genome sequencing solution provider, will describe genome analysis technology and explore the potential for disease prevention.
KAIST medical scientist Jeong Ho Lee, who was the first to identify the causes of intractable epilepsies and has identified the genes responsible for several developmental brain disorders. Professor Jin-Hyung Lee from Stanford University and Dr. David B. Resnik from the National Institute of Environmental Health Science will also join the speaker lineup to discuss genetics-based personalized solutions to extend human life spans.
The forum will also invite about 50 young scientists and medical researchers from around the world to participate in an online panel session. They will engage in a Q&A session and a discussion with the speakers.
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2020.09.04 View 8754 -
Singularity Professors Represent the Future of Research at KAIST
KAIST will launch a Singularity Professor track, which gives more freedom to researchers for pursuing their research goal. This more flexible and creative research environment institutionally supports researchers as they dive deeper into their research for a longer period of time without any strings attached.
The track was established in an effort to ensure more competitive researchers who can lead the way for new advances in science and technology. This innovative research initiative is part of KAIST’s expansive effort to envision and position itself to build global research competitiveness in the wake of its 50th anniversary in 2021 and beyond.
From this year, KAIST will select two to three research faculty for this special track with full-scale funding for 10 years. Singularity Professors will have their annual performance evaluations waived for 10 years. Instead, their research will be reviewed in their fifth year. The professors in this track will not participate in government-funded R&D projects and be fully funded by KAIST’s endowment.
In addition to those newly hired into this track, Singularity Professorships are opens to existing faculty members. The selection criteria are very simple but highly demanding: one who can pivot an existing academic paradigm or invent a new discipline by presenting a novel scientific theory.
KAIST recently hosted a briefing session for current faculty members and encouraged them to apply for the new track. As part of the selection criteria, the research topic’s innovativeness, feasibility, and appropriateness will be major factors for this track. Employment under this track will continue for up to 20 years. After receiving an evaluation of Very Satisfactory at the end of first ten-year contract, another ten years will be added.
President Sung-Chul Shin, who has pushed for this system since he took office in 2017, said during the briefing session, “It takes quite a long time to bear fruit in academics, especially in science. I am very delighted that KAIST is paving the way for building a longer-term research environment which allows full and longer commitments for research that the faculty is excited to try. That’s the first step to sow the seeds for bearing fruit in academics, especially in science.”
This is a paradigm shift to embrace transformation in a new era. The new institutional strategy supports the change from a fast follower to a first mover during these technologically turbulent times. Under its Global Singularity Research Projects initiative, KAIST already selected focus research topics in the most challenging as well as most creative fields of neuro-rehabilitation, new materials, and molecular optogenetics.
“Especially in the post-COVID era, we have a very clear mission for the world. Our knowledge should translate into global value that can benefit those suffering from this pandemic, and mitigate the inequity coming from the digital discrepancies,” President Shin added.
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2020.07.21 View 7427