Artificial+Intelligence
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KAIST researchers developed a novel ultra-low power memory for neuromorphic computing
A team of Korean researchers is making headlines by developing a new memory device that can be used to replace existing memory or used in implementing neuromorphic computing for next-generation artificial intelligence hardware for its low processing costs and its ultra-low power consumption.
KAIST (President Kwang-Hyung Lee) announced on April 4th that Professor Shinhyun Choi's research team in the School of Electrical Engineering has developed a next-generation phase change memory* device featuring ultra-low-power consumption that can replace DRAM and NAND flash memory.
☞ Phase change memory: A memory device that stores and/or processes information by changing the crystalline states of materials to be amorphous or crystalline using heat, thereby changing its resistance state.
Existing phase change memory has the problems such as expensive fabrication process for making highly scaled device and requiring substantial amount of power for operation. To solve these problems, Professor Choi’s research team developed an ultra-low power phase change memory device by electrically forming a very small nanometer (nm) scale phase changeable filament without expensive fabrication processes. This new development has the groundbreaking advantage of not only having a very low processing cost but also of enabling operating with ultra-low power consumption.
DRAM, one of the most popularly used memory, is very fast, but has volatile characteristics in which data disappears when the power is turned off. NAND flash memory, a storage device, has relatively slow read/write speeds, but it has non-volatile characteristic that enables it to preserve the data even when the power is cut off.
Phase change memory, on the other hand, combines the advantages of both DRAM and NAND flash memory, offering high speed and non-volatile characteristics. For this reason, phase change memory is being highlighted as the next-generation memory that can replace existing memory, and is being actively researched as a memory technology or neuromorphic computing technology that mimics the human brain.
However, conventional phase change memory devices require a substantial amount of power to operate, making it difficult to make practical large-capacity memory products or realize a neuromorphic computing system. In order to maximize the thermal efficiency for memory device operation, previous research efforts focused on reducing the power consumption by shrinking the physical size of the device through the use of the state-of-the-art lithography technologies, but they were met with limitations in terms of practicality as the degree of improvement in power consumption was minimal whereas the cost and the difficulty of fabrication increased with each improvement.
In order to solve the power consumption problem of phase change memory, Professor Shinhyun Choi’s research team created a method to electrically form phase change materials in extremely small area, successfully implementing an ultra-low-power phase change memory device that consumes 15 times less power than a conventional phase change memory device fabricated with the expensive lithography tool.
< Figure 1. Illustrations of the ultra-low power phase change memory device developed through this study and the comparison of power consumption by the newly developed phase change memory device compared to conventional phase change memory devices. >
Professor Shinhyun Choi expressed strong confidence in how this research will span out in the future in the new field of research saying, "The phase change memory device we have developed is significant as it offers a novel approach to solve the lingering problems in producing a memory device at a greatly improved manufacturing cost and energy efficiency. We expect the results of our study to become the foundation of future electronic engineering, enabling various applications including high-density three-dimensional vertical memory and neuromorphic computing systems as it opened up the possibilities to choose from a variety of materials.” He went on to add, “I would like to thank the National Research Foundation of Korea and the National NanoFab Center for supporting this research.”
This study, in which See-On Park, a student of MS-PhD Integrated Program, and Seokman Hong, a doctoral student of the School of Electrical Engineering at KAIST, participated as first authors, was published on April 4 in the April issue of the renowned international academic journal Nature. (Paper title: Phase-Change Memory via a Phase-Changeable Self-Confined Nano-Filament)
This research was conducted with support from the Next-Generation Intelligent Semiconductor Technology Development Project, PIM AI Semiconductor Core Technology Development (Device) Project, Excellent Emerging Research Program of the National Research Foundation of Korea, and the Semiconductor Process-based Nanomedical Devices Development Project of the National NanoFab Center.
2024.04.04 View 5353 -
The World’s First Hacking-preventing Cryptographic Semiconductor Chip
With the dramatic increase in the amount of information exchanged between components or devices in the 5G/6G era, such as for the Internet of Things (IoT) and autonomous driving, hacking attacks are becoming more sophisticated. Consequently, enhancing security functions is essential for safely transmitting data between and among devices.
On February 29th, a KAIST research team led by Professors Yang-gyu Choi and Seung-tak Ryu from the School of Electrical Engineering announced the successful development of the world's first security cryptographic semiconductor.
The team has developed the Cryptoristor, a cryptographic transistor based on FinFET technology, produced through a 100% silicon-compatible process, for the first time in the world. Cryptoristor is a random number generator (RNG) with unparalleled characteristics, featuring a unique structure comprising a single transistor and a distinctive mechanism.
In all security environments, including artificial intelligence, the most crucial element is the RNG. In the most commonly used security chip, the Advanced Encryption Standard (AES), the RNG is a core component, occupying approximately 75% of the total chip area and more than 85% of its energy consumption. Hence, there is an urgent need for the development of low-power/ultra-small RNGs suitable for mobile or IoT devices.
Existing RNGs come with limitations as they lack compatibility with silicon CMOS processes and circuit-based RNGs occupy a large surface area.
In contrast, the team’s newly developed Cryptoristor, a cryptographic semiconductor based on a single-component structure, consumes and occupies less than .001 of the power and area compared to the current chips being used. Utilizing the inherent randomness of FinFETs, fabricated on a Silicon-on-Insulator (SOI) substrate with an insulating layer formed beneath the silicon, the team developed an RNG that unpredictably produces zeroes and ones.
< Figure 1. Conceptual diagram of the security cryptographic transistor device. >
Generally speaking, preventing hackers from predicting the encrypted algorithms during data exchanges through mobile devices is pivotal. Therefore, this method ensures unpredictability by generating random sequences of zeroes and ones that change every time.
Moreover, while the Cryptoristor-based RNG research is the world's first of its kind without any international implementation cases, it shares the same transistor structure as existing logic or memory components. This enables 100% production through rapid mass production processes using existing semiconductor facilities at a low cost.
Seung-il Kim, a PhD student who led the research, explained the significance of the study, stating, "As a cryptographic semiconductor, the ultra-small/low-power random number generator enhances security through its distinctive unpredictability, supporting safe hyperconnectivity with secure transmissions between chips or devices. Particularly, compared to previous research, it offers excellent advantages in terms of energy consumption, integration density, and cost, making it suitable for IoT device environments."
This research, with master’s student Hyung-jin Yoo as the co-author, was officially published in the online edition of Science Advances, a sister journal of Science, in February 2024 (research paper title: Cryptographic transistor for true random number generator with low power consumption).
This research received support from the Next-Generation Intelligent Semiconductor Technology Development Project and the Core Technology Development Project for the National Semiconductor Research Laboratory.
2024.03.07 View 5154 -
KAIST Team Develops an Insect-Mimicking Semiconductor to Detect Motion
The recent development of an “intelligent sensor” semiconductor that mimics the optic nerve of insects while operating at ultra-high speeds and low power offers extensive expandability into various innovative technologies. This technology is expected to be applied to various fields including transportation, safety, and security systems, contributing to both industry and society.
On February 19, a KAIST research team led by Professor Kyung Min Kim from the Department of Materials Science and Engineering (DMSE) announced the successful developed an intelligent motion detector by merging various memristor* devices to mimic the visual intelligence** of the optic nerve of insects.
*Memristor: a “memory resistor” whose state of resistance changes depending on the input signal
**Visual intelligence: the ability to interpret visual information and perform calculations within the optic nerve
With the recent advances in AI technology, vision systems are being improved by utilizing AI in various tasks such as image recognition, object detection, and motion analysis. However, existing vision systems typically recognize objects and their behaviour from the received image signals using complex algorithms. This method requires a significant amount of data traffic and higher power consumption, making it difficult to apply in mobile or IoT devices.
Meanwhile, insects are known to be able to effectively process visual information through an optic nerve circuit called the elementary motion detector, allowing them to detect objects and recognize their motion at an advanced level. However, mimicking this pathway using conventional silicon integrated circuit (CMOS) technology requires complex circuits, and its implementation into actual devices has thus been limited.
< Figure 1. Working principle of a biological elementary motion detection system. >
Professor Kyung Min Kim’s research team developed an intelligent motion detecting sensor that operates at a high level of efficiency and ultra-high speeds. The device has a simple structure consisting of only two types of memristors and a resistor developed by the team. The two different memristors each carry out a signal delay function and a signal integration and ignition function, respectively. Through them, the team could directly mimic the optic nerve of insects to analyze object movement.
< Figure 2. (Left) Optical image of the M-EMD device in the left panel (scale bar 200 μm) and SEM image of the device in the right panel (scale bar: 20 μm). (Middle) Responses of the M-EMD in positive direction. (Right) Responses of the M-EMD in negative direction. >
To demonstrate its potential for practical applications, the research team used the newly developed motion detector to design a neuromorphic computing system that can predict the path of a vehicle. The results showed that the device used 92.9% less energy compared to existing technology and predicted motion with more accuracy.
< Figure 3. Neuromorphic computing system configuration based on motion recognition devices >
Professor Kim said, “Insects make use of their very simple visual intelligence systems to detect the motion of objects at a surprising high speed. This research is significant in that we could mimic the functions of a nerve using a memristor device.” He added, “Edge AI devices, such as AI-topped mobile phones, are becoming increasingly important. This research can contribute to the integration of efficient vision systems for motion recognition, so we expect it to be applied to various fields such as autonomous vehicles, vehicle transportation systems, robotics, and machine vision.”
This research, conducted by co-first authors Hanchan Song and Min Gu Lee, both Ph.D. candidates at KAIST DMSE, was published in the online issue of Advanced Materials on January 29.
This research was supported by the Mid-Sized Research Project by the National Research Foundation of Korea, the Next-Generation Intelligent Semiconductor Technology Development Project, the PIM Artificial Intelligence Semiconductor Core Technology Development Project, the National Nano Fab Center, and the Leap Research Project by KAIST.
2024.02.29 View 4896 -
KAIST Demonstrates AI and sustainable technologies at CES 2024
On January 2, KAIST announced it will be participating in the Consumer Electronics Show (CES) 2024, held between January 9 and 12.
CES 2024 is one of the world’s largest tech conferences to take place in Las Vegas. Under the slogan “KAIST, the Global Value Creator” for its exhibition, KAIST has submitted technologies falling under one of following themes: “Expansion of Human Intelligence, Mobility, and Reality”, and “Pursuit of Human Security and Sustainable Development”.
24 startups and pre-startups whose technologies stand out in various fields including artificial intelligence (AI), mobility, virtual reality, healthcare and human security, and sustainable development, will welcome their visitors at an exclusive booth of 232 m2 prepared for KAIST at Eureka Park in Las Vegas.
12 businesses will participate in the first category, “Expansion of Human Intelligence, Mobility, and Reality”, including MicroPix, Panmnesia, DeepAuto, MGL, Reports, Narnia Labs, EL FACTORY, Korea Position Technology, AudAi, Planby Technologies, Movin, and Studio Lab.
In the “Pursuit of Human Security and Sustainable Development” category, 12 businesses including Aldaver, ADNC, Solve, Iris, Blue Device, Barreleye, TR, A2US, Greeners, Iron Boys, Shard Partners and Kingbot, will be introduced.
In particular, Aldaver is a startup that received the Korean Business Award 2023 as well as the presidential award at the Challenge K-Startup with its biomimetic material and printing technology. It has attracted 4.5 billion KRW of investment thus far.
Narnia Labs, with its AI design solution for manufacturing, won the grand prize for K-tech Startups 2022, and has so far attracted 3.5 billion KRW of investments.
Panmnesia is a startup that won the 2024 CES Innovation Award, recognized for their fab-less AI semiconductor technology. They attracted 16 billion KRW of investment through seed round alone.
Meanwhile, student startups will also be presented during the exhibition. Studio Lab received a CES 2024 Best of Innovation Award in the AI category. The team developed the software Seller Canvas, which automatically generates a page for product details when a user uploads an image of a product.
The central stage at the KAIST exhibition booth will be used to interview members of the participating startups between Jan 9 to 11, as well as a networking site for businesses and invited investors during KAIST NIGHT on the evening of 10th, between 5 and 7 PM.
Director Sung-Yool Choi of the KAIST Institute of Technology Value Creation said, “Through CES 2024, KAIST will overcome the limits of human intelligence, mobility, and space with the deep-tech based technologies developed by its startups, and will demonstrate its achievements for realizing its vision as a global value-creating university through the solutions for human security and sustainable development.”
2024.01.05 View 6766 -
North Korea and Beyond: AI-Powered Satellite Analysis Reveals the Unseen Economic Landscape of Underdeveloped Nations
- A joint research team in computer science, economics, and geography has developed an artificial intelligence (AI) technology to measure grid-level economic development within six-square-kilometer regions.
- This AI technology is applicable in regions with limited statistical data (e.g., North Korea), supporting international efforts to propose policies for economic growth and poverty reduction in underdeveloped countries.
- The research team plans to make this technology freely available for use to contribute to the United Nations' Sustainable Development Goals (SDGs).
The United Nations reports that more than 700 million people are in extreme poverty, earning less than two dollars a day. However, an accurate assessment of poverty remains a global challenge. For example, 53 countries have not conducted agricultural surveys in the past 15 years, and 17 countries have not published a population census. To fill this data gap, new technologies are being explored to estimate poverty using alternative sources such as street views, aerial photos, and satellite images.
The paper published in Nature Communications demonstrates how artificial intelligence (AI) can help analyze economic conditions from daytime satellite imagery. This new technology can even apply to the least developed countries - such as North Korea - that do not have reliable statistical data for typical machine learning training.
The researchers used Sentinel-2 satellite images from the European Space Agency (ESA) that are publicly available. They split these images into small six-square-kilometer grids. At this zoom level, visual information such as buildings, roads, and greenery can be used to quantify economic indicators. As a result, the team obtained the first ever fine-grained economic map of regions like North Korea. The same algorithm was applied to other underdeveloped countries in Asia: North Korea, Nepal, Laos, Myanmar, Bangladesh, and Cambodia (see Image 1).
The key feature of their research model is the "human-machine collaborative approach," which lets researchers combine human input with AI predictions for areas with scarce data. In this research, ten human experts compared satellite images and judged the economic conditions in the area, with the AI learning from this human data and giving economic scores to each image. The results showed that the Human-AI collaborative approach outperformed machine-only learning algorithms.
< Image 1. Nightlight satellite images of North Korea (Top-left: Background photo provided by NASA's Earth Observatory). South Korea appears brightly lit compared to North Korea, which is mostly dark except for Pyongyang. In contrast, the model developed by the research team uses daytime satellite imagery to predict more detailed economic predictions for North Korea (top-right) and five Asian countries (Bottom: Background photo from Google Earth). >
The research was led by an interdisciplinary team of computer scientists, economists, and a geographer from KAIST & IBS (Donghyun Ahn, Meeyoung Cha, Jihee Kim), Sogang University (Hyunjoo Yang), HKUST (Sangyoon Park), and NUS (Jeasurk Yang). Dr Charles Axelsson, Associate Editor at Nature Communications, handled this paper during the peer review process at the journal.
The research team found that the scores showed a strong correlation with traditional socio-economic metrics such as population density, employment, and number of businesses. This demonstrates the wide applicability and scalability of the approach, particularly in data-scarce countries. Furthermore, the model's strength lies in its ability to detect annual changes in economic conditions at a more detailed geospatial level without using any survey data (see Image 2).
< Image 2. Differences in satellite imagery and economic scores in North Korea between 2016 and 2019. Significant development was found in the Wonsan Kalma area (top), one of the tourist development zones, but no changes were observed in the Wiwon Industrial Development Zone (bottom). (Background photo: Sentinel-2 satellite imagery provided by the European Space Agency (ESA)). >
This model would be especially valuable for rapidly monitoring the progress of Sustainable Development Goals such as reducing poverty and promoting more equitable and sustainable growth on an international scale. The model can also be adapted to measure various social and environmental indicators. For example, it can be trained to identify regions with high vulnerability to climate change and disasters to provide timely guidance on disaster relief efforts.
As an example, the researchers explored how North Korea changed before and after the United Nations sanctions against the country. By applying the model to satellite images of North Korea both in 2016 and in 2019, the researchers discovered three key trends in the country's economic development between 2016 and 2019. First, economic growth in North Korea became more concentrated in Pyongyang and major cities, exacerbating the urban-rural divide. Second, satellite imagery revealed significant changes in areas designated for tourism and economic development, such as new building construction and other meaningful alterations. Third, traditional industrial and export development zones showed relatively minor changes.
Meeyoung Cha, a data scientist in the team explained, "This is an important interdisciplinary effort to address global challenges like poverty. We plan to apply our AI algorithm to other international issues, such as monitoring carbon emissions, disaster damage detection, and the impact of climate change."
An economist on the research team, Jihee Kim, commented that this approach would enable detailed examinations of economic conditions in the developing world at a low cost, reducing data disparities between developed and developing nations. She further emphasized that this is most essential because many public policies require economic measurements to achieve their goals, whether they are for growth, equality, or sustainability.
The research team has made the source code publicly available via GitHub and plans to continue improving the technology, applying it to new satellite images updated annually. The results of this study, with Ph.D. candidate Donghyun Ahn at KAIST and Ph.D. candidate Jeasurk Yang at NUS as joint first authors, were published in Nature Communications under the title "A human-machine collaborative approach measures economic development using satellite imagery."
< Photos of the main authors. 1. Donghyun Ahn, PhD candidate at KAIST School of Computing 2. Jeasurk Yang, PhD candidate at the Department of Geography of National University of Singapore 3. Meeyoung Cha, Professor of KAIST School of Computing and CI at IBS 4. Jihee Kim, Professor of KAIST School of Business and Technology Management 5. Sangyoon Park, Professor of the Division of Social Science at Hong Kong University of Science and Technology 6. Hyunjoo Yang, Professor of the Department of Economics at Sogang University >
2023.12.07 View 5599 -
KAIST-UCSD researchers build an enzyme discovering AI
- A joint research team led by Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering and Bernhard Palsson of UCSD developed ‘DeepECtransformer’, an artificial intelligence that can predict Enzyme Commission (EC) number of proteins.
- The AI is tasked to discover new enzymes that have not been discovered yet, which would allow prediction for a total of 5,360 types of Enzyme Commission (EC) numbers
- It is expected to be used in the development of microbial cell factories that produce environmentally friendly chemicals as a core technology for analyzing the metabolic network of a genome.
While E. coli is one of the most studied organisms, the function of 30% of proteins that make up E. coli has not yet been clearly revealed. For this, an artificial intelligence was used to discover 464 types of enzymes from the proteins that were unknown, and the researchers went on to verify the predictions of 3 types of proteins were successfully identified through in vitro enzyme assay.
KAIST (President Kwang-Hyung Lee) announced on the 24th that a joint research team comprised of Gi Bae Kim, Ji Yeon Kim, Dr. Jong An Lee and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST, and Dr. Charles J. Norsigian and Professor Bernhard O. Palsson of the Department of Bioengineering at UCSD has developed DeepECtransformer, an artificial intelligence that can predict the enzyme functions from the protein sequence, and has established a prediction system by utilizing the AI to quickly and accurately identify the enzyme function.
Enzymes are proteins that catalyze biological reactions, and identifying the function of each enzyme is essential to understanding the various chemical reactions that exist in living organisms and the metabolic characteristics of those organisms. Enzyme Commission (EC) number is an enzyme function classification system designed by the International Union of Biochemistry and Molecular Biology, and in order to understand the metabolic characteristics of various organisms, it is necessary to develop a technology that can quickly analyze enzymes and EC numbers of the enzymes present in the genome.
Various methodologies based on deep learning have been developed to analyze the features of biological sequences, including protein function prediction, but most of them have a problem of a black box, where the inference process of AI cannot be interpreted. Various prediction systems that utilize AI for enzyme function prediction have also been reported, but they do not solve this black box problem, or cannot interpret the reasoning process in fine-grained level (e.g., the level of amino acid residues in the enzyme sequence).
The joint team developed DeepECtransformer, an AI that utilizes deep learning and a protein homology analysis module to predict the enzyme function of a given protein sequence. To better understand the features of protein sequences, the transformer architecture, which is commonly used in natural language processing, was additionally used to extract important features about enzyme functions in the context of the entire protein sequence, which enabled the team to accurately predict the EC number of the enzyme. The developed DeepECtransformer can predict a total of 5360 EC numbers.
The joint team further analyzed the transformer architecture to understand the inference process of DeepECtransformer, and found that in the inference process, the AI utilizes information on catalytic active sites and/or the cofactor binding sites which are important for enzyme function. By analyzing the black box of DeepECtransformer, it was confirmed that the AI was able to identify the features that are important for enzyme function on its own during the learning process.
"By utilizing the prediction system we developed, we were able to predict the functions of enzymes that had not yet been identified and verify them experimentally," said Gi Bae Kim, the first author of the paper. "By using DeepECtransformer to identify previously unknown enzymes in living organisms, we will be able to more accurately analyze various facets involved in the metabolic processes of organisms, such as the enzymes needed to biosynthesize various useful compounds or the enzymes needed to biodegrade plastics." he added.
"DeepECtransformer, which quickly and accurately predicts enzyme functions, is a key technology in functional genomics, enabling us to analyze the function of entire enzymes at the systems level," said Professor Sang Yup Lee. He added, “We will be able to use it to develop eco-friendly microbial factories based on comprehensive genome-scale metabolic models, potentially minimizing missing information of metabolism.”
The joint team’s work on DeepECtransformer is described in the paper titled "Functional annotation of enzyme-encoding genes using deep learning with transformer layers" written by Gi Bae Kim, Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering of KAIST and their colleagues. The paper was published via peer-review on the 14th of November on “Nature Communications”.
This research was conducted with the support by “the Development of next-generation biorefinery platform technologies for leading bio-based chemicals industry project (2022M3J5A1056072)” and by “Development of platform technologies of microbial cell factories for the next-generation biorefineries project (2022M3J5A1056117)” from National Research Foundation supported by the Korean Ministry of Science and ICT (Project Leader: Distinguished Professor Sang Yup Lee, KAIST).
< Figure 1. The structure of DeepECtransformer's artificial neural network >
2023.11.24 View 3861 -
NYU-KAIST Global AI & Digital Governance Conference Held
< Photo 1. Opening of NYU-KAIST Global AI & Digital Governance Conference >
In attendance of the Minister of Science and ICT Jong-ho Lee, NYU President Linda G. Mills, and KAIST President Kwang Hyung Lee, KAIST co-hosted the NYU-KAIST Global AI & Digital Governance Conference at the Paulson Center of New York University (NYU) in New York City, USA on September 21st, 9:30 pm.
At the conference, KAIST and NYU discussed the direction and policies for ‘global AI and digital governance’ with participants of upto 300 people which includes scholars, professors, and students involved in the academic field of AI and digitalization from both Korea and the United States and other international backgrounds. This conference was a forum of an international discussion that sought new directions for AI and digital technology take in the future and gathered consensus on regulations.
Following a welcoming address by KAIST President, Kwang Hyung Lee and a congratulatory message from the Minister of Science and ICT, Jong-ho Lee, a panel discussion was held, moderated by Professor Matthew Liao, a graduate of Princeton and Oxford University, currently serving as a professor at NYU and the director at the Center for Bioethics of the NYU School of Global Public Health.
Six prominent scholars took part in the panel discussion. Prof. Kyung-hyun Cho of NYU Applied Mathematics and Data Science Center, a KAIST graduate who has joined the ranks of the world-class in AI language models and Professor Jong Chul Ye, the Director of Promotion Council for Digital Health at KAIST, who is leading innovative research in the field of medical AI working in collaboration with major hospitals at home and abroad was on the panel. Additionally, Professor Luciano Floridi, a founding member of the Yale University Center for Digital Ethics, Professor Shannon Vallor, the Baillie Gifford Professor in the Ethics of Data and Artificial Intelligence at the University of Edinburgh of the UK, Professor Stefaan Verhulst, a Co-Founder and the DIrector of GovLab‘s Data Program at NYU’s Tandon School of Engineering, and Professor Urs Gasser, who is in charge of public policy, governance and innovative technology at the Technical University of Munich, also participated.
Professor Matthew Liao from NYU led the discussion on various topics such as the ways to to regulate AI and digital technologies; the concerns about how deep learning technology being developed in medicinal purposes could be used in warfare; the scope of responsibilities Al scientists' responsibility should carry in ensuring the usage of AI are limited to benign purposes only; the effects of external regulation on the AI model developers and the research they pursue; and on the lessons that can be learned from the regulations in other fields.
During the panel discussion, there was an exchange of ideas about a system of standards that could harmonize digital development and regulatory and social ethics in today’s situation in which digital transformation accelerates technological development at a global level, there is a looming concern that while such advancements are bringing economic vitality it may create digital divides and probles like manipulation of public opinion. Professor Jong-cheol Ye of KAIST (Director of the Promotion Council for Digital Health), in particular, emphasized that it is important to find a point of balance that does not hinder the advancements rather than opting to enforcing strict regulations.
< Photo 2. Panel Discussion in Session at NYU-KAIST Global AI & Digital Governance Conference >
KAIST President Kwang Hyung Lee explained, “At the Digital Governance Forum we had last October, we focused on exploring new governance to solve digital challenges in the time of global digital transition, and this year’s main focus was on regulations.”
“This conference served as an opportunity of immense value as we came to understand that appropriate regulations can be a motivation to spur further developments rather than a hurdle when it comes to technological advancements, and that it is important for us to clearly understand artificial intelligence and consider what should and can be regulated when we are to set regulations on artificial intelligence,” he continued.
Earlier, KAIST signed a cooperation agreement with NYU to build a joint campus, June last year and held a plaque presentation ceremony for the KAIST NYU Joint Campus last September to promote joint research between the two universities. KAIST is currently conducting joint research with NYU in nine fields, including AI and digital research. The KAIST-NYU Joint Campus was conceived with the goal of building an innovative sandbox campus centering aroung science, technology, engineering, and mathematics (STEM) combining NYU's excellent humanities and arts as well as basic science and convergence research capabilities with KAIST's science and technology.
KAIST has contributed to the development of Korea's industry and economy through technological innovation aiding in the nation’s transformation into an innovative nation with scientific and technological prowess. KAIST will now pursue an anchor/base strategy to raise KAIST's awareness in New York through the NYU Joint Campus by establishing a KAIST campus within the campus of NYU, the heart of New York.
2023.09.22 View 7171 -
KAIST holds its first ‘KAIST Tech Fair’ in New York, USA
< Photo 1. 2023 KAIST Tech Fair in New York >
KAIST (President Kwang-Hyung Lee) announced on the 11th that it will hold the ‘2023 KAIST Tech Fair in New York’ at the Kimmel Center at New York University in Manhattan, USA, on the 22nd of this month. It is an event designed to be the starting point for KAIST to expand its startup ecosystem into the global stage, and it is to attract investments and secure global customers in New York by demonstrating the technological value of KAIST startup companies directly at location.
< Photo 2. President Kwang Hyung Lee at the 2023 KAIST Tech Fair in New York >
KAIST has been holding briefing sessions for technology transfer in Korea every year since 2018, and this year is the first time to hold a tech fair overseas for global companies.
KAIST Institute of Technology Value Creation (Director Sung-Yool Choi) has prepared for this event over the past six months with the Korea International Trade Association (hereinafter KITA, CEO Christopher Koo) to survey customer base and investment companies to conduct market analysis.
Among the companies founded with the technologies developed by the faculty and students of KAIST and their partners, 7 companies were selected to be matched with companies overseas that expressed interests in these technologies. Global multinational companies in the fields of IT, artificial intelligence, environment, logistics, distribution, and retail are participating as demand agencies and are testing the marketability of the start-up's technology as of September.
Daim Research, founded by Professor Young Jae Jang of the Department of Industrial and Systems Engineering, is a company specializing in smart factory automation solutions and is knocking on the door of the global market with a platform technology optimized for automated logistics systems.
< Photo 3. Presentation by Professor Young Jae Jang for DAIM Research >
It is a ‘collaborative intelligence’ solution that maximizes work productivity by having a number of robots used in industrial settings collaborate with one another. The strength of their solution is that logistics robots equipped with AI reinforced learning technology can respond to processes and environmental changes on their own, minimizing maintenance costs and the system can achieve excellent performance even with a small amount of data when it is combined with the digital twin technology the company has developed on its own.
A student startup, ‘Aniai’, is entering the US market, the home of hamburgers, with hamburger patty automation equipments and solutions. This is a robot kitchen startup founded by its CEO Gunpil Hwang, a graduate of KAIST’s School of Electrical Engineering which gathered together the experts in the fields of robot control, design, and artificial intelligence and cognitive technology to develop technology to automatically cook hamburger patties.
At the touch of a button, both sides of the patty are cooked simultaneously for consistent taste and quality according to the set condition. Since it can cook about 200 dishes in an hour, it is attracting attention as a technology that can not only solve manpower shortages but also accelerate the digital transformation of the restaurant industry.
Also, at the tech fair to be held at the Kimmel Center of New York University on the 22nd, the following startups who are currently under market verification in the U.S. will be participating: ▴'TheWaveTalk', which developed a water quality management system that can measure external substances and metal ions by transferring original technology from KAIST; ▴‘VIRNECT’, which helps workers improve their skills by remotely managing industrial sites using XR*; ▴‘Datumo’, a solution that helps process and analyze artificial intelligence big data, ▴‘VESSL AI’, the provider of a solution to eliminate the overhead** of machine learning systems; and ▴ ‘DolbomDream’, which developed an inflatable vest that helps the psychological stability of people with developmental disabilities.
* XR (eXtended Reality): Ultra-realistic technology that enhances immersion by utilizing augmented reality, virtual reality, and mixed reality technologies
** Overhead: Additional time required for stable processing of the program
In addition, two companies (Plasmapp and NotaAI) that are participating in the D-Unicorn program with the support of the Daejeon City and two companies (Enget and ILIAS Biologics) that are receiving support from the Scale Up Tips of the Ministry of SMEs and Startups, three companies (WiPowerOne, IDK Lab, and Artificial Photosynthesis Lab) that are continuing to realize the sustainable development goals for a total of 14 KAIST startups, will hold a corporate information session with about 100 invited guests from global companies and venture capital.
< Photo 4. Presentation for AP Lab >
Prior to this event, participating startups will be visiting the New York Economic Development Corporation and large law firms to receive advice on U.S. government support programs and on their attemps to enter the U.S. market. In addition, the participating companies plan to visit a startup support investment institution pursuing sustainable development goals and the Leslie eLab, New York University's one-stop startup support space, to lay the foundation for KAIST's leap forward in global technology commercialization.
< Photo 5. Sung-Yool Choi, the Director of KAIST Institute of Technology Value Creation (left) at the 2023 KAIST Tech Fair in New York with the key participants >
Sung-Yool Choi, the Director of KAIST Institute of Technology Value Creation, said, “KAIST prepared this event to realize its vision of being a leading university in creating global value.” He added, “We hope that our startups founded with KAIST technology would successfully completed market verification to be successful in securing global demands and in attracting investments for their endeavors.”
2023.09.11 View 11935 -
Professor Joseph J. Lim of KAIST receives the Best System Paper Award from RSS 2023, First in Korea
- Professor Joseph J. Lim from the Kim Jaechul Graduate School of AI at KAIST and his team receive an award for the most outstanding paper in the implementation of robot systems.
- Professor Lim works on AI-based perception, reasoning, and sequential decision-making to develop systems capable of intelligent decision-making, including robot learning
< Photo 1. RSS2023 Best System Paper Award Presentation >
The team of Professor Joseph J. Lim from the Kim Jaechul Graduate School of AI at KAIST has been honored with the 'Best System Paper Award' at "Robotics: Science and Systems (RSS) 2023".
The RSS conference is globally recognized as a leading event for showcasing the latest discoveries and advancements in the field of robotics. It is a venue where the greatest minds in robotics engineering and robot learning come together to share their research breakthroughs. The RSS Best System Paper Award is a prestigious honor granted to a paper that excels in presenting real-world robot system implementation and experimental results.
< Photo 2. Professor Joseph J. Lim of Kim Jaechul Graduate School of AI at KAIST >
The team led by Professor Lim, including two Master's students and an alumnus (soon to be appointed at Yonsei University), received the prestigious RSS Best System Paper Award, making it the first-ever achievement for a Korean and for a domestic institution.
< Photo 3. Certificate of the Best System Paper Award presented at RSS 2023 >
This award is especially meaningful considering the broader challenges in the field. Although recent progress in artificial intelligence and deep learning algorithms has resulted in numerous breakthroughs in robotics, most of these achievements have been confined to relatively simple and short tasks, like walking or pick-and-place. Moreover, tasks are typically performed in simulated environments rather than dealing with more complex, long-horizon real-world tasks such as factory operations or household chores. These limitations primarily stem from the considerable challenge of acquiring data required to develop and validate learning-based AI techniques, particularly in real-world complex tasks.
In light of these challenges, this paper introduced a benchmark that employs 3D printing to simplify the reproduction of furniture assembly tasks in real-world environments. Furthermore, it proposed a standard benchmark for the development and comparison of algorithms for complex and long-horizon tasks, supported by teleoperation data. Ultimately, the paper suggests a new research direction of addressing complex and long-horizon tasks and encourages diverse advancements in research by facilitating reproducible experiments in real-world environments.
Professor Lim underscored the growing potential for integrating robots into daily life, driven by an aging population and an increase in single-person households. As robots become part of everyday life, testing their performance in real-world scenarios becomes increasingly crucial. He hoped this research would serve as a cornerstone for future studies in this field.
The Master's students, Minho Heo and Doohyun Lee, from the Kim Jaechul Graduate School of AI at KAIST, also shared their aspirations to become global researchers in the domain of robot learning. Meanwhile, the alumnus of Professor Lim's research lab, Dr. Youngwoon Lee, is set to be appointed to the Graduate School of AI at Yonsei University and will continue pursuing research in robot learning.
Paper title: Furniture Bench: Reproducible Real-World Benchmark for Long-Horizon Complex Manipulation. Robotics: Science and Systems.
< Image. Conceptual Summary of the 3D Printing Technology >
2023.07.31 View 6625 -
KAIST gearing up to train physician-scientists and BT Professionals joining hands with Boston-based organizations
KAIST (President Kwang Hyung Lee) announced on the 29th that it has signed MOUs with Massachusetts General Hospital, a founding member of the Mass General Brigham health care system and a world-class research-oriented hospital, and Moderna, a biotechnology company that developed a COVID-19 vaccine at the Langham Hotel in Boston, MA, USA on the morning of April 28th (local time). The signing ceremony was attended by officials from each institution joined by others headed by Minister LEE Young of the Korean Ministry of SMEs and Startups (MSS), and Commissioner LEE Insil of the Korean Intellectual Property Office.
< Photo 1. Photo from the Signing of MOU between KAIST-Harvard University Massachusetts General Hospital and KAIST-Moderna >
Mass General is the first and largest teaching hospital of Harvard Medical School in Boston, USA, and it is one of the most innovative hospitals in the world being the alma mater of more than 13 Nobel Prize winners and the home of the Mass General Research Institute, the world’s largest hospital-based research program that utilizes an annual research budget of more than $1.3 billion.
KAIST signed a general agreement to explore research and academic exchange with Mass General in September of last year and this MOU is a part of its follow-ups.
Mass General works with Harvard and the Massachusetts Institute of Technology (MIT), as well as local hospitals, to support students learn the theories of medicine and engineering, and gain rich clinical research experience.
Through this MOU, KAIST will explore cooperation with an innovative ecosystem created through the convergence of medicine and engineering. In particular, KAIST’s goal is to develop a Korean-style training program and implement a differentiated educational program when establishing the science and technology-oriented medical school in the future by further strengthening the science and engineering part of the training including a curriculum on artificial intelligence (AI) and the likes there of.
Also, in order to foster innovative physician-scientists, KAIST plans to pursue cooperation to develop programs for exchange of academic and human resources including programs for student and research exchanges and a program for students of the science and technology-oriented medical school at KAIST to have a chance to take part in practical training at Mass General.
David F.M. Brown, MD, Mass General President, said, “The collaboration with KAIST has a wide range of potentials, including advice on training of physician-scientists, academic and human resource exchanges, and vitalization of joint research by faculty from both institutions. Through this agreement, we will be able to actively contribute to global cooperation and achieve mutual goals.”
Meanwhile, an MOU between KAIST and Moderna was also held on the same day. Its main focus is to foster medical experts in cooperation with KAIST Graduate School of Medical Science and Engineering (GSMSE), and plans to cooperate in various ways in the future, including collaborating for development of vaccine and new drugs, virus research, joint mRNA research, and facilitation of technology commercialization.
In over 10 years since its inception, Moderna has transformed from a research-stage company advancing programs in the field of messenger RNA (mRNA) to an enterprise with a diverse clinical portfolio of vaccines and therapeutics across seven modalities. The Company has 48 programs in development across 45 development candidates, of which 38 are currently in active clinical trials.
“We are grateful to have laid a foundation for collaboration to foster industry experts with the Korea Advanced Institute of Science and Technology, a leader of science and technology innovation in Korea,” said Arpa Garay, Chief Commercial Officer, Moderna. “Based on our leadership and expertise in developing innovative mRNA vaccines and therapeutics, we hope to contribute to educating and collaborating with professionals in the bio-health field of Korea.“
President Kwang Hyung Lee of KAIST, said, “We deem this occasion to be of grave significance to be able to work closely with Massachusetts General Hospital, one of the world's best research-oriented hospitals, and Moderna, one of the most influential biomedical companies.”
President Lee continued, "On the basis of the collaboration with the two institutions, we will be able to bring up qualified physician-scientists and global leaders of the biomedical business who will solve problems of human health and their progress will in turn, accelerate the national R&D efforts in general and diversify the industry."
2023.04.29 View 11718 -
KAIST develops 'MetaVRain' that realizes vivid 3D real-life images
KAIST (President Kwang Hyung Lee) is a high-speed, low-power artificial intelligence (AI: Artificial Intelligent) semiconductor* MetaVRain, which implements artificial intelligence-based 3D rendering that can render images close to real life on mobile devices.
* AI semiconductor: Semiconductor equipped with artificial intelligence processing functions such as recognition, reasoning, learning, and judgment, and implemented with optimized technology based on super intelligence, ultra-low power, and ultra-reliability
The artificial intelligence semiconductor developed by the research team makes the existing ray-tracing*-based 3D rendering driven by GPU into artificial intelligence-based 3D rendering on a newly manufactured AI semiconductor, making it a 3D video capture studio that requires enormous costs. is not needed, so the cost of 3D model production can be greatly reduced and the memory used can be reduced by more than 180 times. In particular, the existing 3D graphic editing and design, which used complex software such as Blender, is replaced with simple artificial intelligence learning, so the general public can easily apply and edit the desired style.
* Ray-tracing: Technology that obtains images close to real life by tracing the trajectory of all light rays that change according to the light source, shape and texture of the object
This research, in which doctoral student Donghyun Han participated as the first author, was presented at the International Solid-State Circuit Design Conference (ISSCC) held in San Francisco, USA from February 18th to 22nd by semiconductor researchers from all over the world.
(Paper Number 2.7, Paper Title: MetaVRain: A 133mW Real-time Hyper-realistic 3D NeRF Processor with 1D-2D Hybrid Neural Engines for Metaverse on Mobile Devices (Authors: Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, and Hoi-Jun Yoo))
Professor Yoo's team discovered inefficient operations that occur when implementing 3D rendering through artificial intelligence, and developed a new concept semiconductor that combines human visual recognition methods to reduce them. When a person remembers an object, he has the cognitive ability to immediately guess what the current object looks like based on the process of starting with a rough outline and gradually specifying its shape, and if it is an object he saw right before. In imitation of such a human cognitive process, the newly developed semiconductor adopts an operation method that grasps the rough shape of an object in advance through low-resolution voxels and minimizes the amount of computation required for current rendering based on the result of rendering in the past.
MetaVRain, developed by Professor Yu's team, achieved the world's best performance by developing a state-of-the-art CMOS chip as well as a hardware architecture that mimics the human visual recognition process. MetaVRain is optimized for artificial intelligence-based 3D rendering technology and achieves a rendering speed of up to 100 FPS or more, which is 911 times faster than conventional GPUs. In addition, as a result of the study, the energy efficiency, which represents the energy consumed per video screen processing, is 26,400 times higher than that of GPU, opening the possibility of artificial intelligence-based real-time rendering in VR/AR headsets and mobile devices.
To show an example of using MetaVRain, the research team developed a smart 3D rendering application system together, and showed an example of changing the style of a 3D model according to the user's preferred style. Since you only need to give artificial intelligence an image of the desired style and perform re-learning, you can easily change the style of the 3D model without the help of complicated software. In addition to the example of the application system implemented by Professor Yu's team, it is expected that various application examples will be possible, such as creating a realistic 3D avatar modeled after a user's face, creating 3D models of various structures, and changing the weather according to the film production environment. do.
Starting with MetaVRain, the research team expects that the field of 3D graphics will also begin to be replaced by artificial intelligence, and revealed that the combination of artificial intelligence and 3D graphics is a great technological innovation for the realization of the metaverse.
Professor Hoi-Jun Yoo of the Department of Electrical and Electronic Engineering at KAIST, who led the research, said, “Currently, 3D graphics are focused on depicting what an object looks like, not how people see it.” The significance of this study was revealed as a study that enabled efficient 3D graphics by borrowing the way people recognize and express objects by imitating them.” He also foresaw the future, saying, “The realization of the metaverse will be achieved through innovation in artificial intelligence technology and innovation in artificial intelligence semiconductors, as shown in this study.”
Figure 1. Description of the MetaVRain demo screen
Photo of Presentation at the International Solid-State Circuits Conference (ISSCC)
2023.03.13 View 5435 -
KAIST Holds 2023 Commencement Ceremony
< Photo 1. On the 17th, KAIST held the 2023 Commencement Ceremony for a total of 2,870 students, including 691 doctors. >
KAIST held its 2023 commencement ceremony at the Sports Complex of its main campus in Daejeon at 2 p.m. on February 27. It was the first commencement ceremony to invite all its graduates since the start of COVID-19 quarantine measures.
KAIST awarded a total of 2,870 degrees including 691 PhD degrees, 1,464 master’s degrees, and 715 bachelor’s degrees, which adds to the total of 74,999 degrees KAIST has conferred since its foundation in 1971, which includes 15,772 PhD, 38,360 master’s and 20,867 bachelor’s degrees.
This year’s Cum Laude, Gabin Ryu, from the Department of Mechanical Engineering received the Minister of Science and ICT Award. Seung-ju Lee from the School of Computing received the Chairman of the KAIST Board of Trustees Award, while Jantakan Nedsaengtip, an international student from Thailand received the KAIST Presidential Award, and Jaeyong Hwang from the Department of Physics and Junmo Lee from the Department of Industrial and Systems Engineering each received the President of the Alumni Association Award and the Chairman of the KAIST Development Foundation Award, respectively.
Minister Jong-ho Lee of the Ministry of Science and ICT awarded the recipients of the academic awards and delivered a congratulatory speech.
Yujin Cha from the Department of Bio and Brain Engineering, who received a PhD degree after 19 years since his entrance to KAIST as an undergraduate student in 2004 gave a speech on behalf of the graduates to move and inspire the graduates and the guests.
After Cha received a bachelor’s degree from the Department of Nuclear and Quantum Engineering, he entered a medical graduate school and became a radiation oncology specialist. But after experiencing the death of a young patient who suffered from osteosarcoma, he returned to his alma mater to become a scientist. As he believes that science and technology is the ultimate solution to the limitations of modern medicine, he started as a PhD student at the Department of Bio and Brain Engineering in 2018, hoping to find such solutions.
During his course, he identified the characteristics of the decision-making process of doctors during diagnosis, and developed a brain-inspired AI algorithm. It is an original and challenging study that attempted to develop a fundamental machine learning theory from the data he collected from 200 doctors of different specialties.
Cha said, “Humans and AI can cooperate by humans utilizing the unique learning abilities of AI to develop our expertise, while AIs can mimic us humans’ learning abilities to improve.” He added, “My ultimate goal is to develop technology to a level at which humans and machines influence each other and ‘coevolve’, and applying it not only to medicine, but in all areas.”
Cha, who is currently an assistant professor at the KAIST Biomedical Research Center, has also written Artificial Intelligence for Doctors in 2017 to help medical personnel use AI in clinical fields, and the book was selected as one of the 2018 Sejong Books in the academic category.
During his speech at this year’s commencement ceremony, he shared that “there are so many things in the world that are difficult to solve and many things to solve them with, but I believe the things that can really broaden the horizons of the world and find fundamental solutions to the problems at hand are science and technology.”
Meanwhile, singer-songwriter Sae Byul Park who studied at the KAIST Graduate School of Culture Technology will also receive her PhD degree.
Natural language processing (NLP) is a field in AI that teaches a computer to understand and analyze human language that is actively being studied. An example of NLP is ChatGTP, which recently received a lot of attention. For her research, Park analyzed music rather than language using NLP technology.
To analyze music, which is in the form of sound, using the methods for NLP, it is necessary to rebuild notes and beats into a form of words or sentences as in a language. For this, Park designed an algorithm called Mel2Word and applied it to her research.
She also suggested that by converting melodies into texts for analysis, one would be able to quantitatively express music as sentences or words with meaning and context rather than as simple sounds representing a certain note.
Park said, “music has always been considered as a product of subjective emotion, but this research provides a framework that can calculate and analyze music.”
Park’s study can later be developed into a tool to measure the similarities between musical work, as well as a piece’s originality, artistry and popularity, and it can be used as a clue to explore the fundamental principles of how humans respond to music from a cognitive science perspective.
Park began her Ph.D. program in 2014, while carrying on with her musical activities as well as public and university lectures alongside, and dealing with personally major events including marriage and childbirth during the course of years. She already met the requirements to receive her degree in 2019, but delayed her graduation in order to improve the level of completion of her research, and finally graduated with her current achievements after nine years.
Professor Juhan Nam, who supervised Park’s research, said, “Park, who has a bachelor’s degree in psychology, later learned to code for graduate school, and has complete high-quality research in the field of artificial intelligence.” He added, “Though it took a long time, her attitude of not giving up until the end as a researcher is also excellent.”
Sae Byul Park is currently lecturing courses entitled Culture Technology and Music Information Retrieval at the Underwood International College of Yonsei University.
Park said, “the 10 or so years I’ve spent at KAIST as a graduate student was a time I could learn and prosper not only academically but from all angles of life.” She added, “having received a doctorate degree is not the end, but a ‘commencement’. Therefore, I will start to root deeper from the seeds I sowed and work harder as a both a scholar and an artist.”
< Photo 2. From left) Yujin Cha (Valedictorian, Medical-Scientist Program Ph.D. graduate), Saebyeol Park (a singer-songwriter, Ph.D. graduate from the Graduate School of Culture and Technology), Junseok Moon and Inah Seo (the two highlighted CEO graduates from the Department of Management Engineering's master’s program) >
Young entrepreneurs who dream of solving social problems will also be wearing their graduation caps. Two such graduates are Jun-seok Moon and Inah Seo, receiving their master’s degrees in social entrepreneurship MBA from the KAIST College of Business.
Before entrance, Moon ran a café helping African refugees stand on their own feet. Then, he entered KAIST to later expand his business and learn social entrepreneurship in order to sustainably help refugees in the blind spots of human rights and welfare.
During his master’s course, Moon realized that he could achieve active carbon reduction by changing the coffee alone, and switched his business field and founded Equal Table. The amount of carbon an individual can reduce by refraining from using a single paper cup is 10g, while changing the coffee itself can reduce it by 300g.
1kg of coffee emits 15kg of carbon over the course of its production, distribution, processing, and consumption, but Moon produces nearly carbon-neutral coffee beans by having innovated the entire process. In particular, the company-to-company ESG business solution is Moon’s new start-up area. It provides companies with carbon-reduced coffee made by roasting raw beans from carbon-neutral certified farms with 100% renewable energy, and shows how much carbon has been reduced in its making. Equal Table will launch the service this month in collaboration with SK Telecom, its first partner.
Inah Seo, who also graduated with Moon, founded Conscious Wear to start a fashion business reducing environmental pollution. In order to realize her mission, she felt the need to gain the appropriate expertise in management, and enrolled for the social entrepreneurship MBA.
Out of the various fashion industries, Seo focused on the leather market, which is worth 80 trillion won. Due to thickness or contamination issues, only about 60% of animal skin fabric is used, and the rest is discarded. Heavy metals are used during such processes, which also directly affects the environment.
During the social entrepreneurship MBA course, Seo collaborated with SK Chemicals, which had links through the program, and launched eco-friendly leather bags. The bags used discarded leather that was recycled by grinding and reprocessing into a biomaterial called PO3G. It was the first case in which PO3G that is over 90% biodegradable was applied to regenerated leather. In other words, it can reduce environmental pollution in the processing and disposal stages, while also reducing carbon emissions and water usage by one-tenth compared to existing cowhide products.
The social entrepreneurship MBA course, from which Moon and Seo graduated, will run in integration with the Graduate School of Green Growth as an Impact MBA program starting this year. KAIST plans to steadily foster entrepreneurs who will lead meaningful changes in the environment and society as well as economic values through innovative technologies and ideas.
< Photo 3. NYU President Emeritus John Sexton (left), who received this year's honorary doctorate of science, poses with President Kwang Hyung Lee >
Meanwhile, during this day’s commencement ceremony, KAIST also presented President Emeritus John Sexton of New York University with an honorary doctorate in science. He was recognized for laying the foundation for the cooperation between KAIST and New York University, such as promoting joint campuses.
< Photo 4. At the commencement ceremony of KAIST held on the 17th, President Kwang Hyung Lee is encouraging the graduates with his commencement address. >
President Kwang Hyung Lee emphasized in his commencement speech that, “if you can draw up the future and work hard toward your goal, the future can become a work of art that you create with your own hands,” and added, “Never stop on the journey toward your dreams, and do not give up even when you are met with failure. Failure happens to everyone, all the time. The important thing is to know 'why you failed', and to use those elements of failure as the driving force for the next try.”
2023.02.20 View 15056