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KAIST Professor Jiyun Lee becomes the first Korean to receive the Thurlow Award from the American Institute of Navigation
< Distinguished Professor Jiyun Lee from the KAIST Department of Aerospace Engineering >
KAIST (President Kwang-Hyung Lee) announced on January 27th that Distinguished Professor Jiyun Lee from the KAIST Department of Aerospace Engineering had won the Colonel Thomas L. Thurlow Award from the American Institute of Navigation (ION) for her achievements in the field of satellite navigation.
The American Institute of Navigation (ION) announced Distinguished Professor Lee as the winner of the Thurlow Award at its annual awards ceremony held in conjunction with its international conference in Long Beach, California on January 25th. This is the first time a person of Korean descent has received the award.
The Thurlow Award was established in 1945 to honor Colonel Thomas L. Thurlow, who made significant contributions to the development of navigation equipment and the training of navigators. This award aims to recognize an individual who has made an outstanding contribution to the development of navigation and it is awarded to one person each year. Past recipients include MIT professor Charles Stark Draper, who is well-known as the father of inertial navigation and who developed the guidance computer for the Apollo moon landing project.
Distinguished Professor Jiyun Lee was recognized for her significant contributions to technological advancements that ensure the safety of satellite-based navigation systems for aviation. In particular, she was recognized as a world authority in the field of navigation integrity architecture design, which is essential for ensuring the stability of intelligent transportation systems and autonomous unmanned systems. Distinguished Professor Lee made a groundbreaking contribution to help ensure the safety of satellite-based navigation systems from ionospheric disturbances, including those affected by sudden changes in external factors such as the solar and space environment.
She has achieved numerous scientific discoveries in the field of ionospheric research, while developing new ionospheric threat modeling methods, ionospheric anomaly monitoring and mitigation techniques, and integrity and availability assessment techniques for next-generation augmented navigation systems. She also contributed to the international standardization of technology through the International Civil Aviation Organization (ICAO).
Distinguished Professor Lee and her research group have pioneered innovative navigation technologies for the safe and autonomous operation of unmanned aerial vehicles (UAVs) and urban air mobility (UAM). She was the first to propose and develop a low-cost navigation satellite system (GNSS) augmented architecture for UAVs with a near-field network operation concept that ensures high integrity, and a networked ground station-based augmented navigation system for UAM. She also contributed to integrity design techniques, including failure monitoring and integrity risk assessment for multi-sensor integrated navigation systems.
< Professor Jiyoon Lee upon receiving the Thurlow Award >
Bradford Parkinson, professor emeritus at Stanford University and winner of the 1986 Thurlow Award, who is known as the father of GPS, congratulated Distinguished Professor Lee upon hearing that she was receiving the Thurlow Award and commented that her innovative research has addressed many important topics in the field of navigation and her solutions are highly innovative and highly regarded.
Distinguished Professor Lee said, “I am very honored and delighted to receive this award with its deep history and tradition in the field of navigation.” She added, “I will strive to help develop the future mobility industry by securing safe and sustainable navigation technology.”
2024.01.26 View 3420 -
KAIST Research Team Breaks Down Musical Instincts with AI
Music, often referred to as the universal language, is known to be a common component in all cultures. Then, could ‘musical instinct’ be something that is shared to some degree despite the extensive environmental differences amongst cultures?
On January 16, a KAIST research team led by Professor Hawoong Jung from the Department of Physics announced to have identified the principle by which musical instincts emerge from the human brain without special learning using an artificial neural network model.
Previously, many researchers have attempted to identify the similarities and differences between the music that exist in various different cultures, and tried to understand the origin of the universality. A paper published in Science in 2019 had revealed that music is produced in all ethnographically distinct cultures, and that similar forms of beats and tunes are used. Neuroscientist have also previously found out that a specific part of the human brain, namely the auditory cortex, is responsible for processing musical information.
Professor Jung’s team used an artificial neural network model to show that cognitive functions for music forms spontaneously as a result of processing auditory information received from nature, without being taught music. The research team utilized AudioSet, a large-scale collection of sound data provided by Google, and taught the artificial neural network to learn the various sounds. Interestingly, the research team discovered that certain neurons within the network model would respond selectively to music. In other words, they observed the spontaneous generation of neurons that reacted minimally to various other sounds like those of animals, nature, or machines, but showed high levels of response to various forms of music including both instrumental and vocal.
The neurons in the artificial neural network model showed similar reactive behaviours to those in the auditory cortex of a real brain. For example, artificial neurons responded less to the sound of music that was cropped into short intervals and were rearranged. This indicates that the spontaneously-generated music-selective neurons encode the temporal structure of music. This property was not limited to a specific genre of music, but emerged across 25 different genres including classic, pop, rock, jazz, and electronic.
< Figure 1. Illustration of the musicality of the brain and artificial neural network (created with DALL·E3 AI based on the paper content) >
Furthermore, suppressing the activity of the music-selective neurons was found to greatly impede the cognitive accuracy for other natural sounds. That is to say, the neural function that processes musical information helps process other sounds, and that ‘musical ability’ may be an instinct formed as a result of an evolutionary adaptation acquired to better process sounds from nature.
Professor Hawoong Jung, who advised the research, said, “The results of our study imply that evolutionary pressure has contributed to forming the universal basis for processing musical information in various cultures.” As for the significance of the research, he explained, “We look forward for this artificially built model with human-like musicality to become an original model for various applications including AI music generation, musical therapy, and for research in musical cognition.” He also commented on its limitations, adding, “This research however does not take into consideration the developmental process that follows the learning of music, and it must be noted that this is a study on the foundation of processing musical information in early development.”
< Figure 2. The artificial neural network that learned to recognize non-musical natural sounds in the cyber space distinguishes between music and non-music. >
This research, conducted by first author Dr. Gwangsu Kim of the KAIST Department of Physics (current affiliation: MIT Department of Brain and Cognitive Sciences) and Dr. Dong-Kyum Kim (current affiliation: IBS) was published in Nature Communications under the title, “Spontaneous emergence of rudimentary music detectors in deep neural networks”.
This research was supported by the National Research Foundation of Korea.
2024.01.23 View 3559 -
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 5138 -
Center for Global Strategies and Planning Hosts Successful Virtual KAIST U.S. Alumni Connection Event
< Screen capture of the KAIST U.S. Alumni meeting held online on December 8 >
On December 8th, the Center for Global Strategies and Planning at KAIST, led by Vice President Man-Sung Yim of the International Office, conducted a virtual event to bring together KAIST alumni in the United States. The purpose of this event was to showcase KAIST's current initiatives in the U.S., facilitate information exchanges among U.S. alumni, and foster networking opportunities. Over 130 KAIST alumni based in the U.S. registered and attended the event.
The event began with a warm welcome from President Kwang-Hyung Lee, followed by a presentation from Vice President Man-Sung Yim on the current status and vision of KAIST's U.S. collaboration project as well as that of KAIST U.S. Foundation, Inc. Additionally, a distinguished KAIST alumnus, Seok-Hyun Yun, a professor from Harvard Medical School, delivered a keynote speech that highlighted the development of collaborative projects between KAIST and the United States. Alumni Hyun Gook Yoon, a manager at Ford Motor Company, and Eunkwang Joo, CEO of Wasder, also presented recent technological trends in the fields of batteries and blockchain, respectively.
President Kwang-Hyung Lee said, "This event serves as a crucial opportunity to enhance exchanges between KAIST and the U.S., playing a pivotal role in expanding KAIST's global presence." The event also featured small group discussions and networking sessions focusing on revitalizing collaborative efforts between KAIST and the United States.
After the small group discussions, a KAIST alumna and the current president of the Boston KAIST Alumni Association, Jiyoung Lee, shared her belief that the event will provide a meaningful opportunity for KAIST alumni from across the U.S. to come together and build a strong alumni community. Vice President Man-Sung Yim said, "Because collaboration with KAIST alumni in the U.S. is essential for the development of KAIST and innovative science and technology at the global level, we are committed to sustainably organizing meaningful events."
This virtual event for KAIST U.S. alumni has set a new milestone for global networking, marking the beginning of future collaborations and development.
2023.12.08 View 3508 -
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 4561 -
The Relentless Rain: East Asia's Recent Floods and What Lies Beneath
In just a month's time, East Asia witnessed torrential downpours that would usually span an entire season. Japan, battered by three times its usual monthly rainfall, faced landslides and flooding that claimed over 200 lives. Meanwhile, South Korea grappled with its longest monsoon in seven years, leaving more than 40 individuals dead or missing. But these events, as harrowing as they sound, are more than just weather anomalies. They're telltale signs, symptoms of a larger malaise that has gripped our planet.
Diving deep into these rain-soaked mysteries, a recently published paper in the journal Science Advances offers a fresh perspective. Led by a research team at the Korea Advanced Institute of Science and Technology (KAIST), Korea, the research unpacks the influence of human-induced climate changes on the East Asia Summer Monsoon frontal system.
Heavy summer rain has a significant impact on agriculture and industry, and can be said to be one of the greatest threats to human society by causing disasters such as floods and landslides, affecting the local ecosystem. It has been reported from all over the world that the intensity of summer heavy rain has changed over the past few decades. However, summer rain in East Asia is caused by various forms such as typhoons, extratropical cyclones, and fronts, and efforts to study heavy frontal rain, which account for more than 40% of summer rainfall, is still insufficient. In addition, because heavy rain is also influenced by natural fluctuations or coincidences in the climate system, it is not yet known to what extent warming due to human activities affects the intensity of heavy frontal precipitation.
An international joint research team consisting of eight institutions from Korea, the United States, and Japan, including KAIST, Tokyo University, Tokyo Institute of Technology, Chonnam National University, GIST, and Utah State University, confirmed the intensity of heavy rain caused by the weather fronts in East Asia using observation data for the past 60 years and found that the coast of southeastern China. It was found that the intensity of heavy rain increased by about 17% across the Korean Peninsula and Japan. To investigate the cause of these changes, the research team used the Earth Metaverse experiment, which simulated Earth with and without greenhouse gas emissions due to human activities, and found that heavy rain intensity was strengthened by about 6% due to greenhouse gas emissions, and the changes discovered were has succeeded for the first time in the world in showing that warming cannot be explained without the effects of human activities.
< Figure 1. (Left) Observed difference in frontal rainfall intensity (FRI) from the later (1991–2015) to the earlier periods (1958–1982) (Right) Visualization of the impact of anthropogenic warming on the intensity of heavy frontal rain analyzed using the Earth Metaverse experiment. >
"It's not just about connecting the dots," said Moon, the first author of the paper, "it's about seeing the larger pattern. Our data analysis reveals a clear and intensified trend in East Asia's frontal rainfall, one that's intertwined with human actions and increasingly harmful for lives and property."
One of the intriguing finds from the study is the mechanics behind this intensification. The team found increased moisture transport due to a warmer climate, which, when coupled with the strengthening of a gigantic weather system called the West North Pacific Subtropical High, results in enhanced frontal rainfall. It’s akin to the climate dialing up the volume on rain events. As the atmosphere warms, it holds more moisture, leading to heavier downpours when conditions are right.
Nobuyuki Utsumi, another voice from the team, makes the science accessible for all, saying, "Monsoon rain isn't just rain anymore. The frequency, the intensity, it's changing. And our actions, our carbon footprint, are casting a larger shadow than we anticipated."
While the devastating news of floods fills headlines, Professor Simon Wang of Utah State University, reminds us of the underlying importance of their study. "It's like reading a detective novel. To solve the mystery of these floods, one has to trace them back to their roots. This work hints at a future where such intense rain events aren't the exception but might become an everyday reality."
Hyungjun Kim, the principal investigator of the team throws in a note of caution, "Understanding this is just the first step. Predicting and preparing for these extremes is the real challenge. Every amplified rainfall event is a message from the future, urging us to adapt." So far, predicting rainfall intensity and locations remains a challenging task for even the most sophisticated weather models.
< Figure 2. Comparison of rates of change in Anthropocene fingerprints. The horizontal axis shows the long-term change slope of the Anthropocene fingerprint signal (1958 to 2015). Shows the probability distribution of slopes extracted from the non-warming experiment (blue) and the warming experiment (red). The vertical solid lines are the slope of the Anthropocene fingerprint signal extracted from observational data. >
The researchers say, “Facing climate change, the narrative of this new study is more than mere numbers and data. It's a story of our planet, our actions, and the rain-soaked repercussions we're beginning to face. As we mop up the aftermath of another flood, research like Moon's beckons us to look deeper, understand better, and act wiser.”
< Figure 3. Comparison of water vapor convergence and rate of change of the western North Pacific high pressure. Shows the gradient of change in water vapor convergence (horizontal axis) and the Northwestern Pacific-East Asia pressure gradient (vertical axis) extracted from warming (red) and non-warming (blue) experiments. Shows the distribution of slope changes of the two indices during the period 1958 to 1982 (P1) and 1991 to 2015 (P2). >
The results of this study were published on November 24 in Science Advances. (Paper title: Anthropogenic warming induced intensification of summer monsoon frontal precipitation over East Asia)
This research was conducted with support from the National Research Foundation of Korea's Overseas Scientist Attraction Project (BP+) and the Anthropocene Research Center.
2023.12.05 View 3099 -
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 3108 -
KAIST proposes alternatives to chemical factories through “iBridge”
- A computer simulation program “iBridge” was developed at KAIST that can put together microbial cell factories quickly and efficiently to produce cosmetics and food additives, and raw materials for nylons
- Eco-friendly and sustainable fermentation process to establish an alternative to chemical plants
As climate change and environmental concerns intensify, sustainable microbial cell factories garner significant attention as candidates to replace chemical plants. To develop microorganisms to be used in the microbial cell factories, it is crucial to modify their metabolic processes to induce efficient target chemical production by modulating its gene expressions. Yet, the challenge persists in determining which gene expressions to amplify and suppress, and the experimental verification of these modification targets is a time- and resource-intensive process even for experts. The challenges were addressed by a team of researchers at KAIST (President Kwang-Hyung Lee) led by Distinguished Professor Sang Yup Lee.
It was announced on the 9th by the school that a method for building a microbial factory at low cost, quickly and efficiently, was presented by a novel computer simulation program developed by the team under Professor Lee’s guidance, which is named “iBridge”. This innovative system is designed to predict gene targets to either overexpress or downregulate in the goal of producing a desired compound to enable the cost-effective and efficient construction of microbial cell factories specifically tailored for producing the chemical compound in demand from renewable biomass.
Systems metabolic engineering is a field of research and engineering pioneered by KAIST’s Distinguished Professor Sang Yup Lee that seeks to produce valuable compounds in industrial demands using microorganisms that are re-configured by a combination of methods including, but not limited to, metabolic engineering, synthetic biology, systems biology, and fermentation engineering.
In order to improve microorganisms’ capability to produce useful compounds, it is essential to delete, suppress, or overexpress microbial genes. However, it is difficult even for the experts to identify the gene targets to modify without experimental confirmations for each of them, which can take up immeasurable amount of time and resources.
The newly developed iBridge identifies positive and negative metabolites within cells, which exert positive and/or negative impact on formation of the products, by calculating the sum of covariances of their outgoing (consuming) reaction fluxes for a target chemical. Subsequently, it pinpoints "bridge" reactions responsible for converting negative metabolites into positive ones as candidates for overexpression, while identifying the opposites as targets for downregulation.
The research team successfully utilized the iBridge simulation to establish E. coli microbial cell factories each capable of producing three of the compounds that are in high demands at a production capacity that has not been reported around the world. They developed E. coli strains that can each produce panthenol, a moisturizing agent found in many cosmetics, putrescine, which is one of the key components in nylon production, and 4-hydroxyphenyllactic acid, an anti-bacterial food additive. In addition to these three compounds, the study presents predictions for overexpression and suppression genes to construct microbial factories for 298 other industrially valuable compounds.
Dr. Youngjoon Lee, the co-first author of this paper from KAIST, emphasized the accelerated construction of various microbial factories the newly developed simulation enabled. He stated, "With the use of this simulation, multiple microbial cell factories have been established significantly faster than it would have been using the conventional methods. Microbial cell factories producing a wider range of valuable compounds can now be constructed quickly using this technology."
Professor Sang Yup Lee said, "Systems metabolic engineering is a crucial technology for addressing the current climate change issues." He added, "This simulation could significantly expedite the transition from resorting to conventional chemical factories to utilizing environmentally friendly microbial factories."
< Figure. Conceptual diagram of the flow of iBridge simulation >
The team’s work on iBridge is described in a paper titled "Genome-Wide Identification of Overexpression and Downregulation Gene Targets Based on the Sum of Covariances of the Outgoing Reaction Fluxes" written by Dr. Won Jun Kim, and Dr. Youngjoon Lee of the Bioprocess Research Center and Professors Hyun Uk Kim and Sang Yup Lee of the Department of Chemical and Biomolecular Engineering of KAIST. The paper was published via peer-review on the 6th of November on “Cell Systems” by Cell Press.
This research was conducted with the support from the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project (Project Leader: Distinguished Professor Sang Yup Lee, KAIST) and Development of Platform Technology for the Production of Novel Aromatic Bioplastic using Microbial Cell Factories Project (Project Leader: Research Professor So Young Choi, KAIST) of the Korean Ministry of Science and ICT.
2023.11.09 View 4309 -
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 5676 -
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 9683 -
KAIST builds a high-resolution 3D holographic sensor using a single mask
Holographic cameras can provide more realistic images than ordinary cameras thanks to their ability to acquire 3D information about objects. However, existing holographic cameras use interferometers that measure the wavelength and refraction of light through the interference of light waves, which makes them complex and sensitive to their surrounding environment.
On August 23, a KAIST research team led by Professor YongKeun Park from the Department of Physics announced a new leap forward in 3D holographic imaging sensor technology.
The team proposed an innovative holographic camera technology that does not use complex interferometry. Instead, it uses a mask to precisely measure the phase information of light and reconstruct the 3D information of an object with higher accuracy.
< Figure 1. Structure and principle of the proposed holographic camera. The amplitude and phase information of light scattered from a holographic camera can be measured. >
The team used a mask that fulfills certain mathematical conditions and incorporated it into an ordinary camera, and the light scattered from a laser is measured through the mask and analyzed using a computer. This does not require a complex interferometer and allows the phase information of light to be collected through a simplified optical system. With this technique, the mask that is placed between the two lenses and behind an object plays an important role. The mask selectively filters specific parts of light,, and the intensity of the light passing through the lens can be measured using an ordinary commercial camera. This technique combines the image data received from the camera with the unique pattern received from the mask and reconstructs an object’s precise 3D information using an algorithm.
This method allows a high-resolution 3D image of an object to be captured in any position. In practical situations, one can construct a laser-based holographic 3D image sensor by adding a mask with a simple design to a general image sensor. This makes the design and construction of the optical system much easier. In particular, this novel technology can capture high-resolution holographic images of objects moving at high speeds, which widens its potential field of application.
< Figure 2. A moving doll captured by a conventional camera and the proposed holographic camera. When taking a picture without focusing on the object, only a blurred image of the doll can be obtained from a general camera, but the proposed holographic camera can restore the blurred image of the doll into a clear image. >
The results of this study, conducted by Dr. Jeonghun Oh from the KAIST Department of Physics as the first author, were published in Nature Communications on August 12 under the title, "Non-interferometric stand-alone single-shot holographic camera using reciprocal diffractive imaging".
Dr. Oh said, “The holographic camera module we are suggesting can be built by adding a filter to an ordinary camera, which would allow even non-experts to handle it easily in everyday life if it were to be commercialized.” He added, “In particular, it is a promising candidate with the potential to replace existing remote sensing technologies.”
This research was supported by the National Research Foundation’s Leader Research Project, the Korean Ministry of Science and ICT’s Core Hologram Technology Support Project, and the Nano and Material Technology Development Project.
2023.09.05 View 4241 -
A KAIST Research Team Develops a Smart Color-Changing Flexible Battery with Ultra-high Efficiency
With the rapid growth of the smart and wearable electronic devices market, smart next-generation energy storage systems that have energy storage functions as well as additional color-changing properties are receiving a great deal of attention. However, existing electrochromic devices have low electrical conductivity, leading to low efficiency in electron and ion mobility, and low storage capacities. Such batteries have therefore been limited to use in flexible and wearable devices.
On August 21, a joint research team led by Professor Il-Doo Kim from the KAIST Department of Materials Science and Engineering (DMSE) and Professor Tae Gwang Yun from the Myongji University Department of Materials Science and Engineering announced the development of a smart electrochromic Zn-ion battery that can visually represent its charging and discharging processes using an electrochromic polymer anode incorporated with a “π-bridge spacer”, which increases electron and ion mobility efficiency.
Batteries topped with electrochromic properties are groundbreaking inventions that can visually represent their charged and discharged states using colors, and can be used as display devices that cut down energy consumption for indoor cooling by controlling solar absorbance. The research team successfully built a flexible and electrochromic smart Zn-ion battery that can maintain its excellent electrochromic and electrochemical properties, even under long-term exposure to the atmosphere and mechanical deformations.
< Figure 1. Electrochromic zinc ion battery whose anode is made of a polymer that turns dark blue when charged and transparent when discharged. >
To maximize the efficiency of electron and ion mobility, the team modelled and synthesized the first π-bridge spacer-incorporated polymer anode in the world. π-bonds can improve the mobility of electrons within a structure to speed up ion movement and maximize ion adsorption efficiency, which improves its energy storage capacity.
In anode-based batteries with a π-bridge spacer, the spacer provides room for quicker ion movement. This allows fast charging, an improved zinc-ion discharging capacity of 110 mAh/g, which is 40% greater than previously reported, and a 30% increase in electrochromic function that switches from dark blue to transparent when the device is charged/discharged. In addition, should the transparent flexible battery technology be applied to smart windows, they would display darker colors during the day while they absorb solar energy, and function as a futuristic energy storage technique that can block out UV radiation and replace curtains.
< Figure 2. A schematic diagram of the structure of the electrochromic polymer with π-π spacer and the operation of a smart flexible battery using this cathode material. >
< Figure 3. (A) Density Functional Theory (DFT) theory-based atomic and electronic structure analysis. (B) Comparison of rate characteristics for polymers with and without π-bridge spacers. (C) Electrochemical performance comparison graph with previously reported zinc ion batteries. The anode material, which has an electron donor-acceptor structure with a built-in π-bridge spacer, shows better electrochemical performance and electrochromic properties than existing zinc ion batteries and electrochromic devices. >
Professor Il-Doo Kim said, “We have developed a polymer incorporated with a π-bridge spacer and successfully built a smart Zn-ion battery with excellent electrochromic efficiency and high energy storage capacity.” He added, “This technique goes beyond the existing concept of batteries that are used simply as energy storage devices, and we expect this technology to be used as a futuristic energy storage system that accelerates innovation in smart batteries and wearable technologies.”
This research, co-first authored by the alums of KAIST Departments of Material Sciences of Engineering, Professor Tae Gwang Yun of Myongji University, Dr. Jiyoung Lee, a post-doctoral associate at Northwestern University, and Professor Han Seul Kim at Chungbuk National University, was published as an inside cover article for Advanced Materials on August 3 under the title, “A π-Bridge Spacer Embedded Electron Donor-Acceptor Polymer for Flexible Electrochromic Zn-Ion Batteries”.
< Figure 4. Advanced Materials Inside Cover (August Issue) >
This research was supported by the Nanomaterial Technology Development Project under the Korean Ministry of Science and ICT, the Nano and Material Technology Development Project under the National Research Foundation of Korea, the Successive Academic Generation Development Project under the Korean Ministry of Education, and the Alchemist Project under the Korean Ministry of Trade, Industry & Energy.
2023.09.01 View 4868