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KAIST Discovers Molecular Switch that Reverses Cancerous Transformation at the Critical Moment of Transition
< (From left) PhD student Seoyoon D. Jeong, (bottom) Professor Kwang-Hyun Cho, (top) Dr. Dongkwan Shin, Dr. Jeong-Ryeol Gong >
Professor Kwang-Hyun Cho’s research team has recently been highlighted for their work on developing an original technology for cancer reversal treatment that does not kill cancer cells but only changes their characteristics to reverse them to a state similar to normal cells. This time, they have succeeded in revealing for the first time that a molecular switch that can induce cancer reversal at the moment when normal cells change into cancer cells is hidden in the genetic network.
KAIST (President Kwang-Hyung Lee) announced on the 5th of February that Professor Kwang-Hyun Cho's research team of the Department of Bio and Brain Engineering has succeeded in developing a fundamental technology to capture the critical transition phenomenon at the moment when normal cells change into cancer cells and analyze it to discover a molecular switch that can revert cancer cells back into normal cells.
A critical transition is a phenomenon in which a sudden change in state occurs at a specific point in time, like water changing into steam at 100℃. This critical transition phenomenon also occurs in the process in which normal cells change into cancer cells at a specific point in time due to the accumulation of genetic and epigenetic changes.
The research team discovered that normal cells can enter an unstable critical transition state where normal cells and cancer cells coexist just before they change into cancer cells during tumorigenesis, the production or development of tumors, and analyzed this critical transition state using a systems biology method to develop a cancer reversal molecular switch identification technology that can reverse the cancerization process. They then applied this to colon cancer cells and confirmed through molecular cell experiments that cancer cells can recover the characteristics of normal cells.
This is an original technology that automatically infers a computer model of the genetic network that controls the critical transition of cancer development from single-cell RNA sequencing data, and systematically finds molecular switches for cancer reversion by simulation analysis. It is expected that this technology will be applied to the development of reversion therapies for other cancers in the future.
Professor Kwang-Hyun Cho said, "We have discovered a molecular switch that can revert the fate of cancer cells back to a normal state by capturing the moment of critical transition right before normal cells are changed into an irreversible cancerous state."
< Figure 1. Overall conceptual framework of the technology that automatically constructs a molecular regulatory network from single-cell RNA sequencing data of colon cancer cells to discover molecular switches for cancer reversion through computer simulation analysis. Professor Kwang-Hyun Cho's research team established a fundamental technology for automatic construction of a computer model of a core gene network by analyzing the entire process of tumorigenesis of colon cells turning into cancer cells, and developed an original technology for discovering the molecular switches that can induce cancer cell reversal through attractor landscape analysis. >
He continued, "In particular, this study has revealed in detail, at the genetic network level, what changes occur within cells behind the process of cancer development, which has been considered a mystery until now." He emphasized, "This is the first study to reveal that an important clue that can revert the fate of tumorigenesis is hidden at this very critical moment of change."
< Figure 2. Identification of tumor transition state using single-cell RNA sequencing data from colorectal cancer. Using single-cell RNA sequencing data from colorectal cancer patient-derived organoids for normal and cancerous tissues, a critical transition was identified in which normal and cancerous cells coexist and instability increases (a-d). The critical transition was confirmed to show intermediate levels of major phenotypic features related to cancer or normal tissues that are indicative of the states between the normal and cancerous cells (e). >
The results of this study, conducted by KAIST Dr. Dongkwan Shin (currently at the National Cancer Center), Dr. Jeong-Ryeol Gong, and doctoral student Seoyoon D. Jeong jointly with a research team at Seoul National University that provided the organoids (in vitro cultured tissues) from colon cancer patient, were published as an online paper in the international journal ‘Advanced Science’ published by Wiley on January 22nd.
(Paper title: Attractor landscape analysis reveals a reversion switch in the transition of colorectal tumorigenesis) (DOI: https://doi.org/10.1002/advs.202412503)
< Figure 3. Reconstruction of a dynamic network model for the transition state of colorectal cancer.
A new technology was established to build a gene network computer model that can simulate the dynamic changes between genes by integrating single-cell RNA sequencing data and existing experimental results on gene-to-gene interactions in the critical transition of cancer. (a). Using this technology, a gene network computer model for the critical transition of colorectal cancer was constructed, and the distribution of attractors representing normal and cancer cell phenotypes was investigated through attractor landscape analysis (b-e). >
This study was conducted with the support of the National Research Foundation of Korea under the Ministry of Science and ICT through the Mid-Career Researcher Program and Basic Research Laboratory Program and the Disease-Centered Translational Research Project of the Korea Health Industry Development Institute (KHIDI) of the Ministry of Health and Welfare.
< Figure 4. Quantification of attractor landscapes and discovery of transcription factors for cancer reversibility through perturbation simulation analysis. A methodology for implementing discontinuous attractor landscapes continuously from a computer model of gene networks and quantifying them as cancer scores was introduced (a), and attractor landscapes for the critical transition of colorectal cancer were secured (b-d). By tracking the change patterns of normal and cancer cell attractors through perturbation simulation analysis for each gene, the optimal combination of transcription factors for cancer reversion was discovered (e-h). This was confirmed in various parameter combinations as well (i). >
< Figure 5. Identification and experimental validation of the optimal target gene for cancer reversion. Among the common target genes of the discovered transcription factor combinations, we identified cancer reversing molecular switches that are predicted to suppress cancer cell proliferation and restore the characteristics of normal colon cells (a-d). When inhibitors for the molecular switches were treated to organoids derived from colon cancer patients, it was confirmed that cancer cell proliferation was suppressed and the expression of key genes related to cancer development was inhibited (e-h), and a group of genes related to normal colon epithelium was activated and transformed into a state similar to normal colon cells (i-j). >
< Figure 6. Schematic diagram of the research results. Professor Kwang-Hyun Cho's research team developed an original technology to systematically discover key molecular switches that can induce reversion of colon cancer cells through a systems biology approach using an attractor landscape analysis of a genetic network model for the critical transition at the moment of transformation from normal cells to cancer cells, and verified the reversing effect of actual colon cancer through cellular experiments. >
2025.02.05 View 25243 -
KAIST Uncovers the Principles of Gene Expression Regulation in Cancer and Cellular Functions
< (From left) Professor Seyun Kim, Professor Gwangrog Lee, Dr. Hyoungjoon Ahn, Dr. Jeongmin Yu, Professor Won-Ki Cho, and (below) PhD candidate Kwangmin Ryu of the Department of Biological Sciences>
A research team at KAIST has identified the core gene expression networks regulated by key proteins that fundamentally drive phenomena such as cancer development, metastasis, tissue differentiation from stem cells, and neural activation processes. This discovery lays the foundation for developing innovative therapeutic technologies.
On the 22nd of January, KAIST (represented by President Kwang Hyung Lee) announced that the joint research team led by Professors Seyun Kim, Gwangrog Lee, and Won-Ki Cho from the Department of Biological Sciences had uncovered essential mechanisms controlling gene expression in animal cells.
Inositol phosphate metabolites produced by inositol metabolism enzymes serve as vital secondary messengers in eukaryotic cell signaling systems and are broadly implicated in cancer, obesity, diabetes, and neurological disorders.
The research team demonstrated that the inositol polyphosphate multikinase (IPMK) enzyme, a key player in the inositol metabolism system, acts as a critical transcriptional activator within the core gene expression networks of animal cells. Notably, although IPMK was previously reported to play an important role in the transcription process governed by serum response factor (SRF), a representative transcription factor in animal cells, the precise mechanism of its action was unclear.
SRF is a transcription factor directly controlling the expression of at least 200–300 genes, regulating cell growth, proliferation, apoptosis, and motility, and is indispensable for organ development, such as in the heart.
The team discovered that IPMK binds directly to SRF, altering the three-dimensional structure of the SRF protein. This interaction facilitates the transcriptional activity of various genes through the SRF activated by IPMK, demonstrating that IPMK acts as a critical regulatory switch to enhance SRF's protein activity.
< Figure 1. The serum response factor (SRF) protein, a key transcription factor in animal cells, directly binds to inositol polyphosphate multikinase (IPMK) enzyme and undergoes structural change to acquire DNA binding ability, and precisely regulates growth and differentiation of animal cells through transcriptional activation. >
The team further verified that disruptions in the direct interaction between IPMK and SRF lead to the reduced functionality and activity of SRF, causing severe impairments in gene expression.
By highlighting the significance of the intrinsically disordered region (IDR) in SRF, the researchers underscored the biological importance of intrinsically disordered proteins (IDPs). Unlike most proteins that adopt distinct structures through folding, IDPs, including those with IDRs, do not exhibit specific structures but play crucial biological roles, attracting significant attention in the scientific community.
Professor Seyun Kim commented, "This study provides a vital mechanism proving that IPMK, a key enzyme in the inositol metabolism system, is a major transcriptional activator in the core gene expression network of animal cells. By understanding fundamental processes such as cancer development and metastasis, tissue differentiation from stem cells, and neural activation through SRF, we hope this discovery will lead to the broad application of innovative therapeutic technologies."
The findings were published on January 7th in the international journal Nucleic Acids Research (IF=16.7, top 1.8% in Biochemistry and Molecular Biology), under the title “Single-molecule analysis reveals that IPMK enhances the DNA-binding activity of the transcription factor SRF" (DOI: 10.1093/nar/gkae1281).
This research was supported by the National Research Foundation of Korea's Mid-career Research Program, Leading Research Center Program, and Global Research Laboratory Program, as well as by the Suh Kyungbae Science Foundation and the Samsung Future Technology Development Program.
2025.01.24 View 8949 -
KAIST Alumni Association to Honor Alumni of the Year Award Winners
Photo 1. Photo of the KAIST Alumni of the Year Award Recipients
(From left) UST President Lee-whan Kim, CEO Han Chung of iThree Systems Co., Ltd., CEO Dong Myung Kim of LG Energy Solution Co., Ltd., and Professor Hyun Myung of the School of Electrical Engineering at KAIST
KAIST (President Kwang Hyung Lee) announced on Monday, the 13th of January that the Alumni Association (President Yun-Tae Lee) has selected its Alumni of the Year.
This year’s honorees are: ▴ President Lee-whan Kim of the Korea National University of Science and Technology (UST), ▴ CEO Han Chung of i3 Systems, ▴ CEO Dong Myung Kim of LG Energy Solution, and ▴ Professor Hyun Myung of the School of Electrical Engineering at KAIST.
The honorees were selected based on their achievements over the past year, and the award ceremony will be held at the 2025 KAIST Alumni Association New Year’s Gathering to be held at the L Tower in Seoul at 5 PM on Friday the 17th.
The KAIST Alumni of the Year Award is an award presented by the Alumni Association to alumni who have contributed to the development of the country and the society or have brought honor to their alma mater through outstanding academic achievements and community service. Since its establishment in 1992, 126 recipients have been awarded.
Lee-whan Kim (Master's graduate of Mechanical Engineering, 82), the President of the Korea National University of Science and Technology (UST), established a leading foundation for national science and technology policy and strategy, and played a leading role in innovating national science and technology capabilities through the advancement of the national research and development system and the advancement of science and technology personnel training. In particular, he played a pivotal role in the establishment of UST and the Korea Science Academy (KSA), and greatly contributed to establishing a foundation for the training and utilization of science and technology personnel.
Han Chung (Master's graduate of Electrical Engineering, 91, with Ph.D. degree in 96), the CEO of i3 Systems, is a first-generation researcher in the field of domestic infrared detectors. He developed military detectors for over 30 years and founded i3 Systems, a specialized infrared detector company, in 1998. Currently, he supplies more than 80% of the infrared detectors used by the Korean military, and has also achieved export results to over 20 countries.
Dong Myung Kim (Master's graduate of Materials Science and Engineering, 94, with Ph.D. degree in 98) the CEO of LG Energy Solution Co., Ltd. has led innovation in the battery field with his ceaseless exploration and challenging spirit, and is known as an authority in the secondary battery industry. He played a leading role in establishing K-Battery as a global leader, strengthened the country's future industrial competitiveness, and greatly contributed to the development of science and technology.
Hyun Myung (Bachelor's graduate of Electrical Engineering, 92, with Master's degree in 94, and Ph.D. degree in 98) a Professor of Electrical Engineering, KAIST, won first place in the world at the Quadruped Robot Challenge (QRC) hosted by the IEEE’s International Conference on Robotics and Automation (ICRA) 2023 with the 'DreamWaQ' system, an AI walking technology based on deep reinforcement learning that utilizes non-video sensory technologies. He contributed to enhancing the competitiveness of the domestic robot industry by developing his own fully autonomous walking technology that recognizes the environment around the robot and finds the optimal path.
Yun-Tae Lee, the 27th president of the KAIST Alumni Association, said, “KAIST alumni have been the driving force behind the growth of industries in all walks of life by continuously conducting research and development in the field of advanced science and technology for a long time,” and added, “I am very proud of the KAIST alumni award recipients who are leading science and technology on the world stage beyond Korea, and I sincerely thank them for their efforts and achievements.”
2025.01.15 View 4433 -
KAIST Research Team Develops Stretchable Microelectrodes Array for Organoid Signal Monitoring
< Photo 1. (From top left) Professor Hyunjoo J. Lee, Dr. Mi-Young Son, Dr. Mi-Ok Lee(In the front row from left) Doctoral student Kiup Kim, Doctoral student Youngsun Lee >
On January 14th, the KAIST research team led by Professor Hyunjoo J. Lee from the School of Electrical Engineering in collaboration with Dr. Mi-Young Son and Dr. Mi-Ok Lee at Korea Research Institute of Bioscience and Biotechnology (KRIBB) announced the development of a highly stretchable microelectrode array (sMEA) designed for non-invasive electrophysiological signal measurement of organoids.
Organoids* are highly promising models for human biology and are expected to replace many animal experiments. Their potential applications include disease modeling, drug screening, and personalized medicine as they closely mimic the structure and function of humans.
*Organoids: three-dimensional in vitro tissue models derived from human stem cells
Despite these advantages, existing organoid research has primarily focused on genetic analysis, with limited studies on organoid functionality. For effective drug evaluation and precise biological research, technology that preserves the three-dimensional structure of organoids while enabling real-time monitoring of their functions is needed. However, it’s challenging to provide non-invasive ways to evaluate the functionalities without incurring damage to the tissues. This challenge is particularly significant for electrophysiological signal measurement in cardiac and brain organoids since the sensor needs to be in direct contact with organoids of varying size and irregular shape. Achieving tight contact between electrodes and the external surface of the organoids without damaging the organoids has been a persistent challenge.
< Figure 1. Schematic image of highly stretchable MEA (sMEA) with protruding microelectrodes. >
The KAIST research team developed a highly stretchable microelectrode array with a unique serpentine structure that contacts the surface of organoids in a highly conformal fashion. They successfully demonstrated real-time measurement and analysis of electrophysiological signals from two types of electrogenic organoids (heart and brain). By employing a micro-electromechanical system (MEMS)-based process, the team fabricated the serpentine-structured microelectrode array and used an electrochemical deposition process to develop PEDOT:PSS-based protruding microelectrodes. These innovations demonstrated exceptional stretchability and close surface adherence to various organoid sizes. The protruding microelectrodes improved contact between organoids and the electrodes, ensuring stable and reliable electrophysiological signal measurements with high signal-to-noise ratios (SNR).
< Figure 2. Conceptual illustration, optical image, and fluorescence images of an organoid captured by the sMEA with protruding microelectrodes.>
Using this technology, the team successfully monitored and analyzed electrophysiological signals from cardiac spheroids of various sizes, revealing three-dimensional signal propagation patterns and identifying changes in signal characteristics according to size. They also measured electrophysiological signals in midbrain organoids, demonstrating the versatility of the technology. Additionally, they monitored signal modulations induced by various drugs, showcasing the potential of this technology for drug screening applications.
< Figure 3. SNR improvement effect by protruding PEDOT:PSS microelectrodes. >
Prof. Hyunjoo Jenny Lee stated, “By integrating MEMS technology and electrochemical deposition techniques, we successfully developed a stretchable microelectrode array adaptable to organoids of diverse sizes and shapes. The high practicality is a major advantage of this system since the fabrication is based on semiconductor fabrication with high volume production, reliability, and accuracy. This technology that enables in situ, real-time analysis of states and functionalities of organoids will be a game changer in high-through drug screening.”
This study led by Ph.D. candidate Kiup Kim from KAIST and Ph.D. candidate Youngsun Lee from KRIBB, with significant contributions from Dr. Kwang Bo Jung, was published online on December 15, 2024 in Advanced Materials (IF: 27.4).
< Figure 4. Drug screening using cardiac spheroids and midbrain organoids.>
This research was supported by a grant from 3D-TissueChip Based Drug Discovery Platform Technology Development Program (No. 20009209) funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea), by the Commercialization Promotion Agency for R&D Outcomes (COMPA) funded by the Ministry of Science and ICT (MSIT) (RS-2024-00415902), by the K-Brain Project of the National Research Foundation (NRF) funded by the Korean government (MSIT) (RS-2023-00262568), by BK21 FOUR (Connected AI Education & Research Program for Industry and Society Innovation, KAIST EE, No. 4120200113769), and by Korea Research Institute of Bioscience and Biotechnology (KRIBB) Research Initiative Program (KGM4722432).
2025.01.14 View 3351 -
“Cross-Generation Collaborative Labs” for Semiconductor, Chemistry, and Computer Science Opened
< Photo of Professor Hoi-Jun Yoo (center) of the School of Electrical Engineering at the signboard unveiling ceremony >
KAIST held a ceremony to mark the opening of three additional ‘Cross-Generation Collaborative Labs’ on the morning of January 7th, 2025.
The “Next-Generation AI Semiconductor System Lab” by Professor Hoi-Jun Yoo of the School of Electrical Engineering, the “Molecular Spectroscopy and Chemical Dynamics Lab” by Professor Sang Kyu Kim of the Department of Chemistry, and the “Advanced Data Computing Lab” by Professor Sue Bok Moon of the School of Computer Science are the three new labs given the honored titled of the “Cross-Generation Collaborative Lab”.
The Cross-Generation Collaborative Lab is KAIST’s unique system that was set up to facilitate the collaboration between retiring professors and junior professors to continue the achievements and know-how the elders have accumulated over their academic career. Since its introduction in 2018, nine labs have been named to be the Cross-Generation Labs, and this year’s new addition brings the total up to twelve.
The ‘Next-Generation AI Semiconductor System Lab’ led by Professor Hoi-Jun Yoo will be operated by Professor Joo-Young Kim of the same school.
Professor Hoi-Jun Yoo is a world-renowned scholar with outstanding research achievements in the field of on-device AI semiconductor design. Professor Joo-Young Kim is an up-and-coming researcher studying large language models and design of AI semiconductors for server computers, and is currently researching technologies to design PIM (Processing-in-Memory), a core technology in the field of AI semiconductors.
Their research goal is to systematically collaborate and transfer next-generation AI semiconductor design technology, including brain-mimicking AI algorithms such as deep neural networks and generative AI, to integrate core technologies, and to maximize the usability of R&D outputs, thereby further solidifying the position of Korean AI semiconductor companies in the global market.
Professor Hoi-Jun Yoo said, “I believe that, we will be able to present a development direction of for the next-generation AI semiconductors industries at home and abroad through collaborative research and play a key role in transferring and expanding global leadership.”
< Professor Sang Kyu Kim of the Department of Chemistry (middle), at the signboard unveiling ceremony for his laboratory >
The “Molecular Spectroscopy and Chemical Dynamics Laboratory”, where Professor Sang Kyu Kim of the Department of Chemistry is in charge, will be operated by Professor Tae Kyu Kim of the same department, and another professor in the field of spectroscopy and dynamics will join in the future.
Professor Sang Kyu Kim has secured technologies for developing unique experimental equipment based on ultrashort lasers and supersonic molecular beams, and is a world leader who has been creatively pioneering new fields of experimental physical chemistry.
The research goal is to describe chemical reactions and verify from a quantum mechanical perspective and introduce new theories and technologies to pursue a complete understanding of the principles of chemical reactions. In addition, the accompanying basic scientific knowledge will be applied to the design of new materials.
Professor Sang Kyu Kim said, “I am very happy to be able to pass on the research infrastructure to the next generation through this system, and I will continue to nurture it to grow into a world-class research lab through trans-generational collaborative research.”
< Photo of Professor Sue Bok Moon (center) at the signboard unveiling ceremony by the School of Computing >
Lastly, the “Advanced Data Computing Lab” led by Professor Sue Bok Moon is joined by Professor Mee Young Cha of the same school and Professor Wonjae Lee of the Graduate School of Culture Technology.
Professor Sue Bok Moon showed the infinite possibilities of large-scale data-based social network research through Cyworld, YouTube, and Twitter, and had a great influence on related fields beyond the field of computer science.
Professor Mee Young Cha is a data scientist who analyzes difficult social issues such as misinformation, poverty, and disaster detection using big data-based AI. She is the first Korean to be recognized for her achievements as the director of the Max Planck Institute in Germany, a world-class basic science research institute. Therefore, there is high expectation for synergy effects from overseas collaborative research and technology transfer and sharing among the participating professors of the collaborative research lab. Professor Wonjae Lee is researching dynamic interaction analysis between science and technology using structural topic models.
They plan to conduct research aimed at improving the analysis and understanding of negative influences occurring online, and in particular, developing a hateful precursor detection model using emotions and morality to preemptively block hateful expressions.
Professor Sue Bok Moon said, “Through this collaborative research lab, we will play a key role in conducting in-depth collaborative research on unexpected negative influences in the AI era so that we can have a high level of competitiveness worldwide.”
The ceremonies for the unveiling of the new Cross-Generation Collaborative Lab signboard were held in front of each lab from 10:00 AM on the 7th, in the attendance of President Kwang Hyung Lee, Senior Vice President for Research Sang Yup Lee, and other key officials of KAIST and the new staff members to join the laboratories.
2025.01.07 View 4048 -
KAIST Wins CES 2025 Innovation Award, Showcasing Innovative Technologies
KAIST will showcase innovative technologies at the world’s largest technology fair, the Consumer Electronics Show (CES 2025). In addition, KAIST startups VIRNECT Inc., Standard Energy Inc., A2US Inc., and Panmnesia, Inc. won the 2025 CES Innovation Awards.
< Image 1. 3D-Graphical Profile of CES 2025 KAIST Exhibition Booth >
KAIST (President Kwang-Hyung Lee) announced on the 31st that it will operate a 140㎡ standalone booth at CES Eureka Park, which will be held in Las Vegas, USA from January 7th to 10th next year, to showcase KAIST's innovative technologies to global companies and investors.
KAIST startups VIRNECT, Standard Energy, A2US, and Panmnesia, Inc. won the 2025 CES Innovation Awards. ▴VIRNECT won the Innovation Award in the ‘Industrial Equipment and Machinery’ category for ‘VisionX’, an AI-based smart glass for industrial sites; ▴Standard Energy Co., Ltd. won the Innovation Award in the ‘Smart City’ category for developing the world’s first vanadium-ion battery; ▴A2US won the Innovation Award in the ‘Environment & Energy’ category for its portable air purifier that eliminates bacteria, odors, and fine dust in the air with just water droplets; ▴Panmnesia, Inc. won the Innovation Award in the ‘Computer Peripherals and Accessories’ category for its ‘CXL-based GPU Memory Expansion Kit’ that can drastically reduce the cost of building AI infrastructure.
< Image 2. (From left on the top row) VIRNECT, Standard Energy, (From left on the bottom row) A2US, Panmnesia, Inc. >
This exhibition will feature 15 startups that are standing out in cutting-edge technologies such as artificial intelligence (AI), robotics, mobility, and sustainability. In particular, AI-based deep tech startups in various industries such as logistics, architecture, and medicine will take up half of the total, showcasing the companies’ innovative AI technologies.
Polyphenol Factory Co.,Ltd introduces ‘Grabity’, a hair loss shampoo launched domestically, which applies the patented ingredient ‘LiftMax 308™’ that forms an instantaneous protective layer on the hair during the shampooing process. A real-time demonstration will be held at this exhibition hall so that visitors can experience the effects of the ingredient directly, and plans to enter the global market starting with the launch on Amazon in the US in January 2025.
VIRNECT will present ‘VisionX’, a prototype that won the Innovation Award this time. The product provides a chatbot AI through an AI voice interface, and has a function that allows users to check the status of the equipment in real time through conversations with the AI and receive troubleshooting guidance through voice conversations, so users can experience it directly at the KAIST Hall.
‘Standard Energy’ plans to exhibit ‘Energy Tile’, an indoor ESS that utilizes the world’s first vanadium ion battery (hereinafter referred to as VIB). VIB is absolutely safe from fire and has high installation flexibility, so it can be applied to smart cities and AI data centers.
‘A2US’ is the only company in the world that has hydroxyl radical water production technology, and won the Innovation Award for its first product, an air purifier. In the future, it is expected to be widely commercialized in air and water purification, smart farms, food tech, and semiconductor cleaning using safe and environmentally friendly hydroxyl radical water.
Panmnesia, Inc. won the CES Innovation Award for its GPU memory expansion solution equipped with its CXL 3.1 IP. By connecting a memory expansion device using Panmnesia’s CXL IP, the GPU’s memory capacity can be expanded to the terabyte level. Following the Innovation Award for ‘CXL-equipped AI Accelerator’ at CES 2024 last year, it is the only company to have won the Innovation Award for its AI-oriented CXL solution for two consecutive years.
In addition, technologies from a total of 15 companies will be introduced, including ▴Omelet ▴NEXTWAVE ▴Planby Technologies ▴Cosmo Bee ▴ImpactAI ▴Roen Surgical ▴DIDEN Roboticss ▴Autopedia ▴OAQ ▴HydroXpand ▴BOOKEND ▴Sterri.
On the central stage of the KAIST Hall, KAIST students selected as CES Student Supporters will conduct interviews with participating companies and promote the companies' innovative technologies and solutions. On the 8th, from 5 PM to 7 PM, a KAIST NIGHT event will be held where pre-invited investors and participating companies can network.
Keon Jae Lee, the head of the Institute of Technology Value Creation, said, “Through CES 2025, we will showcase innovative technologies and solutions from startups based on KAIST’s deep science and deep tech, and lead commercialization in cutting-edge technology fields such as AI, robotics, mobility, and environment/energy. KAIST plans to further promote technology commercialization by supporting the growth and marketing of innovative startups through the Institute of Technology Value Creation and by strengthening global networks and expanding cooperation opportunities.”
2024.12.31 View 5367 -
KAIST Secures Core Technology for Ultra-High-Resolution Image Sensors
A joint research team from Korea and the United States has developed next-generation, high-resolution image sensor technology with higher power efficiency and a smaller size compared to existing sensors. Notably, they have secured foundational technology for ultra-high-resolution shortwave infrared (SWIR) image sensors, an area currently dominated by Sony, paving the way for future market entry.
KAIST (represented by President Kwang Hyung Lee) announced on the 20th of November that a research team led by Professor SangHyeon Kim from the School of Electrical Engineering, in collaboration with Inha University and Yale University in the U.S., has developed an ultra-thin broadband photodiode (PD), marking a significant breakthrough in high-performance image sensor technology.
This research drastically improves the trade-off between the absorption layer thickness and quantum efficiency found in conventional photodiode technology. Specifically, it achieved high quantum efficiency of over 70% even in an absorption layer thinner than one micrometer (μm), reducing the thickness of the absorption layer by approximately 70% compared to existing technologies.
A thinner absorption layer simplifies pixel processing, allowing for higher resolution and smoother carrier diffusion, which is advantageous for light carrier acquisition while also reducing the cost. However, a fundamental issue with thinner absorption layers is the reduced absorption of long-wavelength light.
< Figure 1. Schematic diagram of the InGaAs photodiode image sensor integrated on the Guided-Mode Resonance (GMR) structure proposed in this study (left), a photograph of the fabricated wafer, and a scanning electron microscope (SEM) image of the periodic patterns (right) >
The research team introduced a guided-mode resonance (GMR) structure* that enables high-efficiency light absorption across a wide spectral range from 400 nanometers (nm) to 1,700 nanometers (nm). This wavelength range includes not only visible light but also light the SWIR region, making it valuable for various industrial applications.
*Guided-Mode Resonance (GMR) Structure: A concept used in electromagnetics, a phenomenon in which a specific (light) wave resonates (forming a strong electric/magnetic field) at a specific wavelength. Since energy is maximized under these conditions, it has been used to increase antenna or radar efficiency.
The improved performance in the SWIR region is expected to play a significant role in developing next-generation image sensors with increasingly high resolutions. The GMR structure, in particular, holds potential for further enhancing resolution and other performance metrics through hybrid integration and monolithic 3D integration with complementary metal-oxide-semiconductor (CMOS)-based readout integrated circuits (ROIC).
< Figure 2. Benchmark for state-of-the-art InGaAs-based SWIR pixels with simulated EQE lines as a function of TAL variation. Performance is maintained while reducing the absorption layer thickness from 2.1 micrometers or more to 1 micrometer or less while reducing it by 50% to 70% >
The research team has significantly enhanced international competitiveness in low-power devices and ultra-high-resolution imaging technology, opening up possibilities for applications in digital cameras, security systems, medical and industrial image sensors, as well as future ultra-high-resolution sensors for autonomous driving, aerospace, and satellite observation.
Professor Sang Hyun Kim, the lead researcher, commented, “This research demonstrates that significantly higher performance than existing technologies can be achieved even with ultra-thin absorption layers.”
< Figure 3. Top optical microscope image and cross-sectional scanning electron microscope image of the InGaAs photodiode image sensor fabricated on the GMR structure (left). Improved quantum efficiency performance of the ultra-thin image sensor (red) fabricated with the technology proposed in this study (right) >
The results of this research were published on 15th of November, in the prestigious international journal Light: Science & Applications (JCR 2.9%, IF=20.6), with Professor Dae-Myung Geum of Inha University (formerly a KAIST postdoctoral researcher) and Dr. Jinha Lim (currently a postdoctoral researcher at Yale University) as co-first authors. (Paper title: “Highly-efficient (>70%) and Wide-spectral (400 nm -1700 nm) sub-micron-thick InGaAs photodiodes for future high-resolution image sensors”)
This study was supported by the National Research Foundation of Korea.
2024.11.22 View 4680 -
KAIST Researchers Suggest an Extraordinary Alternative to Petroleum-based PET - Bacteria!
< (From left) Dr. Cindy Pricilia, Ph.D. Candidate Cheon Woo Moon, Distinguished Professor Sang Yup Lee >
Currently, the world is suffering from environmental problems caused by plastic waste. The KAIST research team has succeeded in producing a microbial-based plastic that is biodegradable and can replace existing PET bottles, making it a hot topic.
Our university announced on the 7th of November that the research team of Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering has succeeded in developing a microbial strain that efficiently produces pseudoaromatic polyester monomer to replace polyethylene terephthalate (PET) using systems metabolic engineering.
Pseudoaromatic dicarboxylic acids have better physical properties and higher biodegradability than aromatic polyester (PET) when synthesized as polymers, and are attracting attention as an eco-friendly monomer* that can be synthesized into polymers. The production of pseudoaromatic dicarboxylic acids through chemical methods has the problems of low yield and selectivity, complex reaction conditions, and the generation of hazardous waste.
*Monomer: A material for making polymers, which is used to synthesize polymers by polymerizing monomers together
< Figure. Overview of pseudoaromatic dicarboxylic acid production using metabolically engineered C. glutamicum. >
To solve this problem, Professor Sang Yup Lee's research team used metabolic engineering to develop a microbial strain that efficiently produces five types of pseudoaromatic dicarboxylic acids, including 2-pyrone-4,6-dicarboxylic acid and four types of pyridine dicarboxylic acids (2,3-, 2,4-, 2,5-, 2,6-pyridine dicarboxylic acids), in Corynebacterium, a bacterium mainly used for amino acid production.
The research team used metabolic engineering techniques to build a platform microbial strain that enhances the metabolic flow of protocatechuic acid, which is used as a precursor for several pseudoaromatic dicarboxylic acids, and prevents the loss of precursors.
Based on this, the genetic manipulation target was discovered through transcriptome analysis, producing 76.17 g/L of 2-pyrone-4,6-dicarboxylic acid, and by newly discovering and constructing three types of pyridine dicarboxylic acid production metabolic pathways, successfully producing 2.79 g/L of 2,3-pyridine dicarboxylic acid, 0.49 g/L of 2,4-pyridine dicarboxylic acid, and 1.42 g/L of 2,5-pyridine dicarboxylic acid.
In addition, the research team confirmed the production of 15.01 g/L through the construction and reinforcement of the 2,6-pyridine dicarboxylic acid biosynthesis pathway, successfully producing a total of five similar aromatic dicarboxylic acids with high efficiency.
In conclusion, the team succeeded in producing 2,4-, 2,5-, and 2,6-pyridine dicarboxylic acids at the world's highest concentration. In particular, 2,4-, 2,5-pyridine dicarboxylic acid achieved production on the scale of g/L, which was previously produced in extremely small amounts (mg/L).
Based on this study, it is expected that it will be applied to various polyester production industrial processes, and it is also expected that it will be actively utilized in research on the production of similar aromatic polyesters.
Professor Sang Yup Lee, the corresponding author, said, “The significance lies in the fact that we have developed an eco-friendly technology that efficiently produces similar aromatic polyester monomers based on microorganisms,” and “This study will help the microorganism-based bio-monomer industry replace the petrochemical-based chemical industry in the future.”
The results of this study were published in the international academic journal, the Proceedings of the National Academy of Sciences of United States of America (PNAS) on October 30th.
※ Paper title: Metabolic engineering of Corynebacterium glutamicum for the production of pyrone and pyridine dicarboxylic acids
※ Author information: Jae Sung Cho (co-first author), Zi Wei Luo (co-first author), Cheon Woo Moon (co-first author), Cindy Prabowo (co-author), Sang Yup Lee (corresponding author) - a total of 5 people
This study was conducted with the support of the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry Project and the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project (Project leader: Professor Sang Yup Lee) from the National Research Foundation supported by the Ministry of Science and Technology and ICT of Korea.
2024.11.08 View 7987 -
A KAIST Team Develops Face-Conforming LED Mask Showing 340% Improved Efficacy in Deep Skin Elasticity
- A KAIST research team led by Professor Keon Jae Lee has developed a deep skin-stimulating LED mask which has been verified in clinical trials to improve dermis elasticity by 340%.
< Figure 1. Overall concept of face-fit surface-lighting micro-LEDs (FSLED) mask. a. Optical image of the FSLED mask showing uniform surface-lighting. schematic illustration of the FSLED mask. The 2D to 3D transformation procedure b. Difference in cosmetic effect on deep skin elasticity, wrinkles, and sagging between FSLED mask and CLED mask. (improvement percentage in eight weeks) >
Conventional LED masks, with their rigid design, fail to conform closely to the skin's contours. This limitation causes substantial light reflection, with up to 90% reflected over a distance of 2 cm, reducing light penetration and limiting stimulation of the deep skin layers essential for effective skin rejuvenation.
To address these challenges, Professor Lee's team developed a face-conforming surface lighting micro-LED (FSLED) mask, which can provide uniform photostimulation to the dermis. The key technology lies in the mask's ability to deliver uniform light to deep skin tissues while maintaining a conformal skin attachment. This is achieved through a 3D origami structure, integrated with 3,770 micro-LEDs and flexible surface light-diffusion layer, minimizing the gaps between the light source and the skin.
In clinical trials involving 33 participants, the FSLED mask demonstrated a 340% improvement in deep skin elasticity compared to conventional LED masks, proving its efficacy in significantly reducing skin wrinkles, sagging and aging.
Professor Keon Jae Lee said, “The FSLED mask provides cosmetic benefits to the entire facial dermis without the side effects of low-temperature burns, making home-care anti-aging treatment that enhances the quality of human life possible. The product is being manufactured by Fronics, KAIST startup company, and will be distributed globally through Amorepacific's network, with sales starting in November.”
This result titled “Clinical Validation of Face-fit Surface-lighting Micro Light-emitting Diode Mask for Skin Anti-aging Treatment”, in which Min Seo Kim, a student of the Master-Doctorate integrated program, and Jaehun An, a Ph.D. candidate, in the Department of Materials Science and Engineering of KAIST, took part as co-first authors, was published in Advanced Materials on October 22nd, 2024 (DOI: 10.1002/adma.202411651).
Introductory Video: Face-conforming surface LED mask for skin anti-aging ( https://www.youtube.com/watch?v=kSccLwx8N_w )
2024.10.29 View 6422 -
KAIST Professor Uichin Lee Receives Distinguished Paper Award from ACM
< Photo. Professor Uichin Lee (left) receiving the award >
KAIST (President Kwang Hyung Lee) announced on the 25th of October that Professor Uichin Lee’s research team from the School of Computing received the Distinguished Paper Award at the International Joint Conference on Pervasive and Ubiquitous Computing and International Symposium on Wearable Computing (Ubicomp / ISWC) hosted by the Association for Computing Machinery (ACM) in Melbourne, Australia on October 8.
The ACM Ubiquitous Computing Conference is the most prestigious international conference where leading universities and global companies from around the world present the latest research results on ubiquitous computing and wearable technologies in the field of human-computer interaction (HCI).
The main conference program is composed of invited papers published in the Proceedings of the ACM (PACM) on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), which covers the latest research in the field of ubiquitous and wearable computing.
The Distinguished Paper Award Selection Committee selected eight papers among 205 papers published in Vol. 7 of the ACM Proceedings (PACM IMWUT) that made outstanding and exemplary contributions to the research community. The committee consists of 16 prominent experts who are current and former members of the journal's editorial board which made the selection after a rigorous review of all papers for a period that stretched over a month.
< Figure 1. BeActive mobile app to promote physical activity to form active lifestyle habits >
The research that won the Distinguished Paper Award was conducted by Dr. Junyoung Park, a graduate of the KAIST Graduate School of Data Science, as the 1st author, and was titled “Understanding Disengagement in Just-in-Time Mobile Health Interventions”
Professor Uichin Lee’s research team explored user engagement of ‘Just-in-Time Mobile Health Interventions’ that actively provide interventions in opportune situations by utilizing sensor data collected from health management apps, based on the premise that these apps are aptly in use to ensure effectiveness.
< Figure 2. Traditional user-requested digital behavior change intervention (DBCI) delivery (Pull) vs. Automatic transmission (Push) for Just-in-Time (JIT) mobile DBCI using smartphone sensing technologies >
The research team conducted a systematic analysis of user disengagement or the decline in user engagement in digital behavior change interventions. They developed the BeActive system, an app that promotes physical activities designed to help forming active lifestyle habits, and systematically analyzed the effects of users’ self-control ability and boredom-proneness on compliance with behavioral interventions over time.
The results of an 8-week field trial revealed that even if just-in-time interventions are provided according to the user’s situation, it is impossible to avoid a decline in participation. However, for users with high self-control and low boredom tendency, the compliance with just-in-time interventions delivered through the app was significantly higher than that of users in other groups.
In particular, users with high boredom proneness easily got tired of the repeated push interventions, and their compliance with the app decreased more quickly than in other groups.
< Figure 3. Just-in-time Mobile Health Intervention: a demonstrative case of the BeActive system: When a user is identified to be sitting for more than 50 mins, an automatic push notification is sent to recommend a short active break to complete for reward points. >
Professor Uichin Lee explained, “As the first study on user engagement in digital therapeutics and wellness services utilizing mobile just-in-time health interventions, this research provides a foundation for exploring ways to empower user engagement.” He further added, “By leveraging large language models (LLMs) and comprehensive context-aware technologies, it will be possible to develop user-centered AI technologies that can significantly boost engagement."
< Figure 4. A conceptual illustration of user engagement in digital health apps. Engagement in digital health apps consists of (1) engagement in using digital health apps and (2) engagement in behavioral interventions provided by digital health apps, i.e., compliance with behavioral interventions. Repeated adherences to behavioral interventions recommended by digital health apps can help achieve the distal health goals. >
This study was conducted with the support of the 2021 Biomedical Technology Development Program and the 2022 Basic Research and Development Program of the National Research Foundation of Korea funded by the Ministry of Science and ICT.
< Figure 5. A conceptual illustration of user disengagement and engagement of digital behavior change intervention (DBCI) apps. In general, user engagement of digital health intervention apps consists of two components: engagement in digital health apps and engagement in behavioral interventions recommended by such apps (known as behavioral compliance or intervention adherence). The distinctive stages of user can be divided into adoption, abandonment, and attrition. >
< Figure 6. Trends of changes in frequency of app usage and adherence to behavioral intervention over 8 weeks, ● SC: Self-Control Ability (High-SC: user group with high self-control, Low-SC: user group with low self-control) ● BD: Boredom-Proneness (High-BD: user group with high boredom-proneness, Low-BD: user group with low boredom-proneness). The app usage frequencies were declined over time, but the adherence rates of those participants with High-SC and Low-BD were significantly higher than other groups. >
2024.10.25 View 6756 -
KAIST Develops Thread-like, Flexible Thermoelectric Materials Applicable in Extreme Environments
A team of Korean researchers developed a thermoelectric material that can be used in wearable devices, such as smart clothing, and while maintaining stable thermal energy performance even in extreme environments. It has dramatically resolved the dilemma of striking the balance between achieving good performance and the mechanical flexibility of thermoelectric materials, which has been a long-standing challenge in the field of thermoelectric materials, and has also proven the possibility of commercialization.
KAIST (President Kwang-Hyung Lee) announced on the 21st that a joint research team of Professor Yeon Sik Jung of the Department of Materials Science and Engineering and Professor Inkyu Park of the Department of Mechanical Engineering, in collaboration with the research teams of Professor Min-Wook Oh of Hanbat National University (President Yong Jun Oh) and Dr. Jun-Ho Jeong of the Korea Institute of Machinery and Materials (President Seoghyun Ryu), have successfully developed ‘bismuth telluride (Bi2Te3) thermoelectric fibers,’ an innovative energy harvesting solution for next-generation flexible electronic devices.
Thermoelectric materials are materials that generate voltage when there is a temperature difference and convert thermal energy into electrical energy. Currently, about 70% of energy being lost as wasted heat, so due attention is being given to research on these as sustainable energy materials that can recover and harvesting energy from this waste heat.
Most of the heat sources around us are curved, such as the human body, vehicle exhaust pipes, and cooling fins. Inorganic thermoelectric materials based on ceramic materials boast high thermoelectric performance, but they are fragile and difficult to produce in curved shapes. On the other hand, flexible thermoelectric materials using existing polymer binders can be applied to surfaces of various shapes, but their performance was limited due to the low electrical conductivity and high thermal resistance of the polymer.
Existing flexible thermoelectric materials contain polymer additives, but the inorganic thermoelectric material developed by the research team is not flexible, so they overcame these limitations by twisting nano ribbons instead of additives to produce a thread-shaped thermoelectric material. Inspired by the flexibility of inorganic nano ribbons, the research team used a nanomold-based electron beam deposition technique to continuously deposit nano ribbons and then twisted them into a thread shape to create bismuth telluride (Bi2Te3) inorganic thermoelectric fibers.
These inorganic thermoelectric fibers have higher bending strength than existing thermoelectric materials, and showed almost no change in electrical properties even after repeated bending and tensile tests of more than 1,000 times. The thermoelectric device created by the research team generates electricity using temperature differences, and if clothes are made with fiber-type thermoelectric devices, electricity can be generated from body temperature to operate other electronic devices.
< Figure 1. Schematic diagram and actual image of the all-inorganic flexible thermoelectric yarn made without polymer additives >
In fact, the possibility of commercialization was proven through a demonstration of collecting energy by embedding thermoelectric fibers in life jackets or clothing. In addition, it opened up the possibility of building a high-efficiency energy harvesting system that recycles waste heat by utilizing the temperature difference between the hot fluid inside a pipe and the cold air outside in industrial settings.
Professor Yeon Sik Jung said, "The inorganic flexible thermoelectric material developed in this study can be used in wearable devices such as smart clothing, and it can maintain stable performance even in extreme environments, so it has a high possibility of being commercialized through additional research in the future." Professor Inkyu Park also emphasized, "This technology will become the core of next-generation energy harvesting technology, and it is expected to play an important role in various fields from waste heat utilization in industrial sites to personal wearable self-power generation devices."
This study, in which Hanhwi Jang, a Ph.D. student at KAIST's Department of Materials Science and Engineering, Professor Junseong Ahn of Korea University, Sejong Campus, and Dr. Yongrok Jeong of Korea Atomic Energy Research Institute contributed equally as joint first authors, was published in the online edition of the international academic journal Advanced Materials on September 17, and was selected as the back-cover paper in recognition of its excellence. (Paper title: Flexible All-Inorganic Thermoelectric Yarns)
Meanwhile, this study was conducted through the Mid-career Researcher Support Program and the Future Materials Discovery Program of the National Research Foundation of Korea, and the support from the Global Bio-Integrated Materials Center, the Ministry of Trade, Industry and Energy, and the Korea Institute of Industrial Technology Evaluation and Planning (KEIT) upon the support by the Ministry of Science and ICT.
2024.10.21 View 4030 -
KAIST Develops Technology for the Precise Diagnosis of Electric Vehicle Batteries Using Small Currents
Accurately diagnosing the state of electric vehicle (EV) batteries is essential for their efficient management and safe use. KAIST researchers have developed a new technology that can diagnose and monitor the state of batteries with high precision using only small amounts of current, which is expected to maximize the batteries’ long-term stability and efficiency.
KAIST (represented by President Kwang Hyung Lee) announced on the 17th of October that a research team led by Professors Kyeongha Kwon and Sang-Gug Lee from the School of Electrical Engineering had developed electrochemical impedance spectroscopy (EIS) technology that can be used to improve the stability and performance of high-capacity batteries in electric vehicles.
EIS is a powerful tool that measures the impedance* magnitude and changes in a battery, allowing the evaluation of battery efficiency and loss. It is considered an important tool for assessing the state of charge (SOC) and state of health (SOH) of batteries. Additionally, it can be used to identify thermal characteristics, chemical/physical changes, predict battery life, and determine the causes of failures. *Battery Impedance: A measure of the resistance to current flow within the battery that is used to assess battery performance and condition.
However, traditional EIS equipment is expensive and complex, making it difficult to install, operate, and maintain. Moreover, due to sensitivity and precision limitations, applying current disturbances of several amperes (A) to a battery can cause significant electrical stress, increasing the risk of battery failure or fire and making it difficult to use in practice.
< Figure 1. Flow chart for diagnosis and prevention of unexpected combustion via the use of the electrochemical impedance spectroscopy (EIS) for the batteries for electric vehicles. >
To address this, the KAIST research team developed and validated a low-current EIS system for diagnosing the condition and health of high-capacity EV batteries. This EIS system can precisely measure battery impedance with low current disturbances (10mA), minimizing thermal effects and safety issues during the measurement process.
In addition, the system minimizes bulky and costly components, making it easy to integrate into vehicles. The system was proven effective in identifying the electrochemical properties of batteries under various operating conditions, including different temperatures and SOC levels.
Professor Kyeongha Kwon (the corresponding author) explained, “This system can be easily integrated into the battery management system (BMS) of electric vehicles and has demonstrated high measurement accuracy while significantly reducing the cost and complexity compared to traditional high-current EIS methods. It can contribute to battery diagnosis and performance improvements not only for electric vehicles but also for energy storage systems (ESS).”
This research, in which Young-Nam Lee, a doctoral student in the School of Electrical Engineering at KAIST participated as the first author, was published in the prestigious international journal IEEE Transactions on Industrial Electronics (top 2% in the field; IF 7.5) on September 5th. (Paper Title: Small-Perturbation Electrochemical Impedance Spectroscopy System With High Accuracy for High-Capacity Batteries in Electric Vehicles, Link: https://ieeexplore.ieee.org/document/10666864)
< Figure 2. Impedance measurement results of large-capacity batteries for electric vehicles. ZEW (commercial EW; MP10, Wonatech) versus ZMEAS (proposed system) >
This research was supported by the Basic Research Program of the National Research Foundation of Korea, the Next-Generation Intelligent Semiconductor Technology Development Program of the Korea Evaluation Institute of Industrial Technology, and the AI Semiconductor Graduate Program of the Institute of Information & Communications Technology Planning & Evaluation.
2024.10.17 View 5523