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KAIST's 'FluidGPT' Wins Grand Prize at the 2025 AI Champion Competition
<Commemorative Photo After Winning at the 2025 AI Champions Award Ceremony>
The era has begun where an AI assistant goes beyond simple conversation to directly view the screen, make decisions, and complete tasks such as hailing a taxi or booking an SRT ticket.
KAIST (President Kwang Hyung Lee) announced on the 6th that the AutoPhone Team (Fluidez, KAIST, Korea University, Sungkyunkwan University), led by Professor Insik Shin (CEO of Fluidez Co., Ltd.) of the School of Computing, was selected as the inaugural AI Champion (1st place) in the '2025 Artificial Intelligence Champion (AI Champion) Competition,' hosted by the Ministry of Science and ICT.
This competition is the nation's largest AI technology contest, comprehensively evaluating the innovativeness, social impact, and commercial potential of AI technology. With 630 teams participating nationwide, the AutoPhone Team claimed the top honor and will receive 3 billion Korean won in research and development funding.
The technology developed by the AutoPhone Team, 'FluidGPT,' is a fully autonomous AI agent that understands a user's voice command and enables the smartphone to independently run apps, click, input, and even complete payments.
For example, when a user says, "Book an SRT ticket from Seoul Station to Busan," or "Call a taxi," FluidGPT opens the actual app and sequentially performs the necessary steps to complete the request.
The core of this technology is its 'Non-Invasive (API-Free)' structure. Previously, calling a taxi using an app required directly connecting to the app's internal system (API communication) through the taxi app's API. In contrast, this technology does not modify the existing app's code or link an API. Instead, the AI directly recognizes and operates the screen (UI), acquiring the ability to use the smartphone just like a human.
As a result, FluidGPT presents a new paradigm—"AI that sees, judges, and moves a hand on behalf of a person"—and is evaluated as a core technology that will usher in the 'AI Phone Era.'
FluidGPT moves beyond simple voice assistance to implement the concept of 'Agentic AI' (Action-Oriented Artificial Intelligence), where the AI directly views the screen, makes decisions, and takes action. As a fully action-oriented system, the AI clicks app buttons, fills in input fields, and references data to autonomously achieve the user's objective, foreshadowing an innovation in how smartphones are used.
Professor In-sik Shin of the School of Computing shared his thoughts, stating, "AI is now evolving from conversation to action. FluidGPT is a technology that understands the user's words and autonomously executes actual apps, and it will be the starting point of the 'AI Phone Era.' The AutoPhone Team possesses world-class research capabilities, and we will contribute to the widespread adoption of AI services that everyone can easily use."
KAIST President Kwang Hyung Lee remarked, "This achievement is a representative example that demonstrates KAIST's vision for AI convergence," adding, "AI technology is entering the daily lives of citizens and leading a new wave of innovation." He further added, "KAIST will continue to lead research in future core technologies such as AI and semiconductors to bolster national competitiveness."
2025.11.06 View 375 -
KAIST Uncovers the Mechanism Behind Overactive Immune Cells
<(From Right) Professor Eui-Cheol Shin, Ph.D candidate So-Young Kim, Professor Su-Hyung Park, Professor Hyuk Soo Eun, Dr. Hoyoung Lee>
“Why do immune cells that are supposed to eliminate viruses suddenly turn against our own body?”
There are instances where killer T cells—which are meant to precisely remove virus-infected cells—malfunction like overheated engines, attacking even healthy cells and damaging tissues. A KAIST research team has now identified the key mechanism that regulates this excessive activation of killer T cells, offering new insights into controlling immune overreactions and developing therapies for immune-related diseases.
KAIST (President Kwang Hyung Lee) announced on November 5 that a research team led by Professors Eui-Cheol Shin and Su-Hyung Park from the Graduate School of Medical Science and Engineering, in collaboration with Professor Hyuk Soo Eun from Chungnam National University College of Medicine, has uncovered the molecular basis of nonspecific activation in killer T cells and proposed a new therapeutic strategy to control it.
Killer T cells (CD8⁺ T cells) selectively eliminate infected cells to prevent viral spread. However, when excessively activated, they can attack uninfected cells, causing inflammation and tissue damage. Such overactive immune responses can lead to severe viral infections and autoimmune diseases.
In 2018, Professor Shin’s team was the first in the world to discover that killer T cells can be nonspecifically activated by cytokines and randomly attack host cells—a phenomenon they termed “bystander activation of T cells”. The current study builds on that discovery by revealing the molecular mechanism driving this abnormal process.
The team focused on a cytokine called interleukin-15 (IL-15). Experiments showed that IL-15 can abnormally excite killer T cells by a bystander activation mechanism, causing them to attack uninfected host cells. However, when there is a concurrent antigen-specific stimulation, IL-15-induced bystander activation is suppressed.
The researchers further identified that this suppression occurs through an intracellular signaling process. When the concentration of calcium ions (Ca²⁺) changes, a protein called calcineurin activates, which in turn triggers a regulatory protein known as NFAT, suppressing IL-15-induced bystander activation of killer T cells. In other words, the calcineurin–NFAT pathway activated by antigen stimulation acts as a brake on overactivation by a bystander mechanism.
The team also discovered that some immunosuppressants, which are known to block the calcineurin pathway, may not always suppress immune responses—in certain contexts, they can instead promote IL-15-induced bystander activation of killer T cells. This finding underscores that not all immunosuppressants work the same way and that treatments must be carefully tailored to each patient’s immune response.
Through gene expression analysis, the researchers identified a gene set that increase only in abnormally activated killer T cells induced by IL-15 as markers. They further confirmed that these same markers were elevated in bystander killer T cells from patients with acute hepatitis A, suggesting that the markers could be used for disease diagnosis.
<In a normal immune response, killer T cells are activated by antigen stimulation and selectively eliminate only virus-infected cells, thereby controlling viral replication and promoting the patient’s rapid recovery. However, when killer T cells are nonspecifically overactivated by interleukin-15, they may randomly attack normal cells as well, causing excessive tissue damage and leading to severe disease. Future research may identify diseases in which such nonspecific hyperimmune responses occur, making it possible to develop new drugs to control them>
This study provides crucial clues for understanding the pathogenesis of various immune-related diseases, including severe viral infections, chronic inflammatory disorders, autoimmune diseases, and organ transplant rejection. It also paves the way for developing novel immunoregulatory therapies targeting IL-15 signaling.
Professor Eui-Cheol Shin explained that, “this study shows that killer T cells are not merely defenders—they can transform into ‘nonspecific attackers’ depending on the inflammatory environment. By precisely regulating this abnormal activation, we may be able to develop new treatments for intractable immune diseases.”
This research was published in the journal Immunity on October 31, with Dr. Hoyoung Lee and Ph.D. candidate So-Young Kim as co–first authors.
Title: “TCR signaling via NFATc1 constrains IL-15-induced bystander activation of human memory CD8⁺ T cells”, DOI: doi.org/10.1016/j.immuni.2025.10.002
The study was supported by the National Research Foundation of Korea (NRF), the Korea Health Industry Development Institute (KHIDI), and the Institute for Basic Science (IBS).
2025.11.06 View 474 -
AI Finds Urban Commercial Districts Resilient to Climate Risk
< (From left) Integrated M.S.-Ph.D candidate Keonhee Jang, Postdoctoral Researcher Namwoo Kim, Professor Yoonjin Yoon, Researcher Seok-woo Yoon, Postdoctoral Researcher Young-jun Park, (Top) M.S candidate Juneyoung Ro >
KAIST announced on October 29th that its Urban AI Research Institute (Director, Distinguished Professor Yoonjin Yoon of Civil and Environmental Engineering conducted joint research in the field of 'Urban AI' with MIT's Senseable City Lab (Director, Professor Carlo Ratti) and disclosed the results at the 'Smart Life Week 2025' exhibition held at COEX, Seoul, in late September.
KAIST and MIT have been pursuing the 'Urban AI Joint Research Program' to interpret major urban problems using artificial intelligence. At this exhibition, the research results were presented in a form that citizens could directly experience, focusing on three themes: ▲Urban Climate Change, ▲Green Environment, and ▲Data Inclusivity.
Through this collaboration, the two institutions demonstrated that AI technology can expand beyond a tool for calculating urban problems to a new intelligence that promotes social understanding and empathy. They carried out three projects: ▲Urban Heat and Sales, ▲Nature That Heals, Seoul, and ▲Data Sonification.
The first project, 'Urban Heat and Sales,' is a study that analyzes the impact of climate change on urban commercial areas and the small business ecosystem using AI. An AI model was trained on over 300 million data points, including sales and weather for 96 business categories across 426 administrative dong (neighborhoods) in Seoul, to quantify the effect of climatic factors, such as temperature and humidity, on sales by industry type.
The results were visualized into 40,896 'Urban Heat Resilience' indicators, which score how well each region and business category can adapt to and recover from climate change. This allows the level of commercial area resilience to climate risk to be grasped at a glance, showing which areas are strong against temperature risks.
According to the study, for the convenience store sector, 64.7% of the total 426 dong were analyzed as 'climate-neutral areas,' which are relatively stable against climate change, while the remaining 35.3% belong to 'climate-sensitive areas,' which are significantly affected by climate change. This suggests that the operating environment for convenience stores varies significantly by region in terms of climate impact, and the data can be utilized for future location strategy planning from an urban resilience perspective.
< '3D Mesh Structure' that visually represents sales data for 426 regions in Seoul. The height and color of each region indicate the scale of sales. The left shows the distribution of sales in Seoul under actual temperature conditions, and the right shows the sales change predicted by AI when the temperature rises by 5 degrees. >
Visitors to the exhibition could select a region and business type on a real Seoul map and experience a system where the AI predicted sales changes in real-time based on future temperature rise scenarios.
This prediction model is a proprietary technology developed by KAIST, and plans are underway to expand cooperation with other major global cities, such as Boston and London. This research is expected to propose a new direction for establishing opening strategies for small business owners and developing urban climate risk response policies.
< Numerous visitors listening to explanations and experiencing the KAIST-MIT exhibition space >
The second project, 'Nature That Heals, Seoul,' is an extension of MIT's global project 'Feeling Nature' to Seoul. It combines urban environment data (Street View, maps, satellite images, etc.) with citizen survey data to train an AI to estimate the 'psychological green'—the actual psychological experience of green spaces felt by Seoul citizens.
This approach goes beyond simply calculating the area of trees or parks, offering new urban design directions that reflect citizens' emotional resilience and well-being. This research is expected to provide scientific evidence for future Seoul green space policies and locally tailored urban design.
The final project, 'Data Sonification,' is the world's first AI technology that translates over 300 million data points into sounds, like music, to be 'heard.' The AI uses data such as temperature, humidity, and sales to represent information through sound: for example, the pitch rises when the temperature goes up, and the sound lowers when sales decrease. This provides a new sensory experience of 'listening' to urban data through sound instead of sight.
This technology is a prime example of 'Barrier-Free AI' (AI for All), an inclusive AI technology that helps people with visual impairments or children—who may have difficulty accessing visual information—to intuitively understand data.
< A visitor experiencing Data Sonification, the world's first AI technology that converts data into sound >
Man-ki Kim, Chairman of the Seoul AI Hub (Seoul AI Foundation), which sponsored this research, stated, "We have achieved meaningful results by analyzing the urban environment and citizens' lives with artificial intelligence through collaboration with world-class research institutions like KAIST and MIT," adding, "This research has laid the groundwork for understanding urban change from the perspective of citizens and connecting it to policy and daily life."
Director Yoonjin Yoon remarked, "This exhibition demonstrated that artificial intelligence can evolve beyond a technology that merely calculates the city to an intelligence that understands and empathizes with people and the city," and concluded, "We will create data and experiences together with citizens, and collaborate with various cities worldwide to open a more inclusive and sustainable urban future."
This achievement is a global collaborative research project in the AI sector involving the KAIST Urban AI Research Institute and the MIT Senseable City Lab, and was conducted with sponsorship from the Seoul AI Hub.
※Research Results Images/Videos: https://05970c0c.slw-6vy.pages.dev/
2025.10.29 View 531 -
“AI,” the New Language of Materials Science and Engineering Spoken at KAIST
<(From Left) M.S candidate Chaeyul Kang, Professor Seumgbum Hong, Ph. D candidate Benediktus Madika, Ph.D candidate Batzorig Buyantogtokh, Ph.D candiate Aditi Saha, >
Collaborating authors include Professor Joshua Agar (Drexel University), Professors Chris Wolverton and Peter Voorhees (Northwestern University), Professor Peter Littlewood (University of St Andrews), and Professor Sergei Kalinin (University of Tennessee).
Paper Title: Artificial Intelligence for Materials Discovery, Development, and Optimization
The era has arrived in which artificial intelligence (AI) autonomously imagines and predicts the structures and properties of new materials. Today, AI functions as a researcher’s “second brain,” actively participating in every stage of research, from idea generation to experimental validation.
KAIST (President Kwang Hyung Lee) announced on October 26 that a comprehensive review paper analyzing the impact of AI, Machine Learning (ML), and Deep Learning (DL) technologies across materials science and engineering has been published in ACS Nano (Impact Factor = 18.7). The paper was co-authored by Professor Seungbum Hong and his team from the Department of Materials Science and Engineering at KAIST, in collaboration with researchers from Drexel University, Northwestern University, the University of St Andrews, and the University of Tennessee in the United States.
The research team proposed a full-cycle utilization strategy for materials innovation through an AI-based catalyst search platform, which embodies the concept of a Self-Driving Lab—a system in which robots autonomously perform materials synthesis and optimization experiments.
Professor Hong’s team categorized materials research into three major stages—Discovery, Development, and Optimization—and detailed the distinctive role of AI in each phase:
In the Discovery Stage, AI designs new structures, predicts properties, and rapidly identifies the most promising materials among vast candidate pools.
In the Development Stage, AI analyzes experimental data and autonomously adjusts experimental processes through Self-Driving Lab systems, significantly shortening research timelines.
In the Optimization Stage, AI employs Reinforcement Learning, which identifies optimal conditions through Bayesian Optimization, which efficiently finds superior results with minimal experimentation, to fine-tune designs and process conditions for maximum performance.
In essence, AI serves as a “smart assistant” that narrows down the most promising materials, reduces experimental trial and error, and autonomously optimizes experimental conditions to achieve the best-performing outcomes.
The paper further highlights how cutting-edge technologies such as Generative AI, Graph Neural Networks (GNNs), and Transformer models are transforming AI from a computational tool into a “thinking researcher.” Nonetheless, the team cautions that AI’s predictions are not error-proof and that key challenges persist, such as imbalanced data quality, limited interpretability of AI predictions, and integration of heterogeneous datasets.
To address these limitations, the authors emphasize the importance of developing AI systems capable of autonomously understanding physical principles and ensuring transparent, verifiable decision-making processes for researchers.
The review also explores the concept of the Self-Driving Lab, where AI autonomously designs experimental plans, analyzes results, and determines the next experimental steps—without manual operation by researchers. The AI-Based Catalyst Search Platform exemplifies this concept, enabling robots to automatically design, execute, and optimize catalyst synthesis experiments.
In particular, the study presents cases in which AI-driven experimentation has dramatically accelerated catalyst development, suggesting that similar approaches could revolutionize research in battery and energy materials.
<AI Driving Innovation Across the Entire Cycle of New Material Discovery, Development, and Optimization>
“This review demonstrates that artificial intelligence is emerging as the new language of materials science and engineering, transcending its role as a mere tool,” said Professor Seungbum Hong. “The roadmap presented by the KAIST team will serve as a valuable guide for researchers in Korea’s national core industries including batteries, semiconductors, and energy materials.”
Benediktus Madika (Ph.D. candidate), Aditi Saha (Ph.D. candidate), Chaeyul Kang (M.S. candidate), and Batzorig Buyantogtokh (Ph.D. candidate) from KAIST’s Department of Materials Science and Engineering contributed as co-first authors.
Collaborating authors include Professor Joshua Agar (Drexel University), Professors Chris Wolverton and Peter Voorhees (Northwestern University), Professor Peter Littlewood (University of St Andrews), and Professor Sergei Kalinin (University of Tennessee).
Paper Title: Artificial Intelligence for Materials Discovery, Development, and Optimization
DOI: 10.1021/acsnano.5c04200
This work was supported by the National Research Foundation of Korea (NRF) with funding from the Ministry of Science and ICT (RS-2023-00247245).
2025.10.27 View 618 -
KAIST Develops Ultrafast Photothermal Process Achieving 3,000 °C in 0.02 Seconds, Boosting Hydrogen Production Efficiency Sixfold
< (from left) Ph.D. candidate Seohak Park, Dr. Jaewan Ahn, Ph.D. candidate Dogyeong Jeon, Prof. Sung-Yool Choi, Prof. Il-Doo Kim, Dr. Chungseong Park, Ph.D. candidate Euichul Shin (top left) Dr. Hamin Shin, Dr. Jun-Hwe Cha i>
The rapid and energy-efficient synthesis of high-performance catalysts is a critical hurdle in advancing clean energy technologies like hydrogen production. Addressing this challenge, a research team at KAIST has now developed a novel platform technology that utilizes a 0.02-second flash of light to generate an ultrahigh temperature of 3,000 °C, enabling the highly efficient synthesis of catalysts. This breakthrough process reduces energy consumption by more than a thousandfold compared to conventional methods while increasing hydrogen production efficiency by up to six times, marking a significant step toward the commercialization of clean energy.
KAIST (President Kwang Hyung Lee) announced on October 20 that a joint research team, co-led by Professor Il-Doo Kim from the Department of Materials Science and Engineering and Professor Sung-Yool Choi from the School of Electrical Engineering, has developed a “direct-contact photothermal annealing” platform. This technique synthesizes high-performance nanomaterials through brief exposure to intense light, generating a transient temperature of 3,000 °C in just 0.02 seconds.
Using this intense photothermal energy, the researchers successfully converted chemically inert nanodiamond (ND) precursors into highly conductive and catalytically active carbon nanoonions (CNOs).
More impressively, the method simultaneously functionalizes the surface of the newly formed CNOs with single atoms. This integrated, one-step process restructures the support material and embeds catalytic functionality in a single light pulse, representing a significant innovation in catalyst synthesis.
CNOs, composed of concentric graphitic shells, are ideal catalyst supports due to their high conductivity, large specific surface area, and chemical stability. However, traditional CNO synthesis has been hindered by complex, multi-step post-processing required to load metal catalysts and by reliance on energy-intensive, time-consuming thermal treatments that limit scalability.
< Schematic Illustration of the Limitations of Conventional Thermal-Radiation Synthesis and the Carbon Nano-Onion Conversion via Direct-Contact Photothermal Treatment >
To overcome these limitations, the KAIST team leveraged the photothermal effect. They devised a method of mixing ND precursors with light-absorbing carbon black (CB) and applying an intense pulse from a xenon lamp. This approach triggers the transformation of NDs into CNOs in just 0.02 seconds, a phenomenon validated by molecular dynamics simulations.
A key innovation of this platform is the simultaneous synthesis of CNOs and functionalization of single-atom catalysts (SACs). When metal precursors, such as platinum (Pt), are included in the mixture, they decompose and anchor onto the surface of the nascent CNOs as individual atoms. The subsequent rapid cooling prevents atomic aggregation, resulting in a perfectly integrated one-step process for both synthesis and functionalization. The team has successfully synthesized eight different high-density SACs, including platinum (Pt), cobalt (Co), and nickel (Ni). The resulting Pt-CNO demonstrated a sixfold enhancement in hydrogen evolution efficiency compared to conventional catalysts, achieving high performance with significantly smaller quantities of precious metals. This highlights the technology's potential for scalable and sustainable hydrogen production.
“We have developed, for the first time, a direct-contact photothermal annealing process that reaches 3,000°C in under 0.02 seconds,” said Professor Il-Doo Kim. “This ultrafast synthesis and single-atom functionalization platform reduces energy consumption by more than a thousandfold compared to traditional methods. We expect it to accelerate the commercialization of technologies in hydrogen energy, gas sensing, and environmental catalysis.”
The study’s first authors are Dogyeong Jeon (Ph.D. candidate, Department of Materials Science and Engineering, KAIST), Dr. Hamin Shin (an alumnus of the Department of Materials Science and Engineering and a current postdoctoral researcher at ETH Zurich), and Dr. Jun-Hwe Cha (an alumnus of the School of Electrical Engineering, now at SK hynix). Professors Sung-Yool Choi and Il-Doo Kim are the corresponding authors.\
< Inside Cover Image of the September Issue of ACS >
The research was published as a Supplementary Cover Article in the September issue of ACS Nano, a leading international journal of the American Chemical Society (ACS).
※ Paper title: “Photothermal Annealing-Enabled Millisecond Synthesis of Carbon Nanoonions and Simultaneous Single-Atom Functionalization,” DOI: 10.1021/acsnano.5c11229
This research was supported by the Global R&D Infrastructure Program and the Leading Research Center Program of the National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT, and the Nano Convergence Technology Center’s Semiconductor–Battery Interfacing Platform Development Project.
2025.10.21 View 903 -
KAIST Launches Student Led ESG Research Platform with Brand Revenue
KAIST (President Kwang Hyung Lee) announced on the 19th of October that it is launching a new action-oriented ESG program, 'PDSP (Problem Definition to Solution Program),' which returns brand revenue to students to support research aimed at solving social problems. Brand revenue refers to profits from the sale of branded products, such as 'Nubjuk-i,' and the brand shop that KAIST operates near the campus's duck pond.
This initiative is the first model to concretize KAIST's brand value and social responsibility through a student-centric approach, serving as an innovative starting point that connects 'research–startup–social contribution.'
The project is funded by dividends from Brand KAIST, a subsidiary of KAIST Holdings (CEO Hyunmin Bae), led by co-CEOs Hyun Jung Suk and Byeongjun Bok (CEO of KAI Patent Law Firm, and KAIST Industrial Design alumni).
By reinvesting brand revenue into student research activities, KAIST aims to implement a KAIST-style virtuous cycle ESG structure: 'Brand->Revenue->Student->Social Contribution.'
PDSP is a research program where KAIST undergraduate students voluntarily form teams to explore social and technological problems and propose solutions. The program name, 'Problem Definition to Solution Program,' signifies that students directly define the problem and design the solution, aiming to become a practical research platform that connects learned knowledge to solving social issues.
Through the PDSP, KAIST is expanding the concept of ESG beyond Environment, Society, and Governance to 'Practicing Social Responsibility through Education and Science.'
The process of students proactively defining social problems and proposing solutions is itself a form of ESG value realization, and KAIST seeks to build a science and technology-based, action-oriented ESG model through this.
The PDSP operates with two research tracks: Deep Tech and ESG. The 'Deep Tech Track' supports fundamental technology research that will lead future industries, leveraging KAIST's advanced science and technology capabilities in areas such as Artificial Intelligence (AI), semiconductors, robotics, biotechnology, new materials, and energy. The 'ESG Track' focuses on research on social issues such as climate change, carbon neutrality, and aging, concentrating on realizing a sustainable society through science and technology.
<KAIST PDSP (Problem Definition to Solution Program) Poster>
This program is regarded not merely as an idea contest but as a 'student-led Deep Tech incubation program' that promotes substantial technological innovation originating from research labs.
Participation is open to approximately 20 teams, each composed of three to five undergraduate students. Each team can choose to apply for either the Deep Tech Track or the ESG Track. A maximum of 1.5 million KRW in research activity expenses will be provided per team for three months, with the funding executed according to KAIST's internal research project standards. Applications are accepted through the KAIST portal site from September 29 until midnight on November 5. Selected teams, after being reviewed by an evaluation committee, will go through stages including orientation, interim check, and performance presentation.
Hyeonmin Bae, CEO of KAIST Holdings (Professor of Electrical Engineering), stated, "The PDSP will be the starting point for KAIST-style autonomous research culture where students define problems and design solutions themselves," adding, "We plan to actively consider providing initial investments and commercialization support for outstanding research teams to develop their ideas into startups."
Hyeong-Jeong Suk, CEO of Brand KAIST (Professor of Industrial Design), said, "This program, where Brand KAIST's revenue is reinvested into student research, shows that the KAIST brand is evolving beyond a mere symbol to a platform for creating social value. I believe the true power of the KAIST brand lies in students creating new change that bridges technology and society through creative research."
A student who submitted an application for the program commented, "I wanted to explore social topics like environmental issues or technological inequality through research, and I am excited that this program offers such an opportunity," adding, "I feel a sense of pride as a KAIST student to be able to give back the knowledge I've gained to society."
KAIST President Kwang Hyung Lee emphasized, "Creating a co-prosperity innovation model that returns the value generated by the KAIST brand to our students is also KAIST's strength," and "I hope that the problems defined by the students themselves will contribute to the progress of humanity, and that creative research will become the driving force for social change."
Since its establishment in 1971, leading South Korea's scientific and technological development and industrial innovation, KAIST is realizing the 'virtuous cycle of brand value' through its PDSP, presenting a new ESG paradigm that combines student-led social contribution and technological innovation.
2025.10.20 View 477 -
Chemobiological Platform Enables Renewable Conversion of Sugars into Core Aromatic Hydrocarbons of Petroleum
<(From Left) Professor Sun Kyu Han, Ph.D candidate Tae Wan Kim, Professor Kyeong Rok Choi, Professor Sang Yup Lee>
With growing concerns over fossil fuel depletion and the environmental impacts of petrochemical production, scientists are actively exploring renewable strategies to produce essential industrial chemicals. A collaborative research team—led by Distinguished Professor Sang Yup Lee, Senior Vice President for Research, from the Department of Chemical and Biomolecular Engineering, together with Professor Sunkyu Han from the Department of Chemistry at the Korea Advanced Institute of Science and Technology (KAIST)—has developed an integrated chemobiological platform that converts renewable carbon sources such as glucose and glycerol into oxygenated precursors, which are subsequently deoxygenated in the same solvent system to yield benzene, toluene, ethylbenzene, and p-xylene (BTEX), which are fundamental aromatic hydrocarbons used in fuels, polymers, and consumer products.
<Figure 1. Schematic representation of the chemobiological synthesis of BTEX from glucose or glycerol in Escherichia coli>
From Sugars to Aromatic Hydrocarbons of Petroleum
The researchers designed four metabolically engineered strains of Escherichia coli, each programmed to produce a specific oxygenated precursor—phenol, benzyl alcohol, 2-phenylethanol, or 2,5-xylenol. These intermediates are generated through tailored genetic modifications, such as deletion of feedback-regulated enzymes, overexpression of pathway-specific genes, and introduction of heterologous enzymes to expand metabolic capabilities.
During fermentation, the products were continuously extracted into the organic solvent isopropyl myristate (IPM). Acting as a dual-function solvent, IPM not only mitigated the toxic effects of aromatic compounds on cell growth but also served directly as the reaction medium for downstream chemical upgrading. By eliminating the need for intermediate purification, solvent exchange, or distillation, this solvent-integrated system streamlined the conversion of renewable feedstocks into valuable aromatics.
Overcoming Chemical Barriers in An Unconventional Solvent
A central innovation of this work lies in adapting chemical deoxygenation reactions to function efficiently within IPM—a solvent rarely used in organic synthesis. Traditional catalysts and reagents often proved ineffective under these conditions due to solubility limitations or incompatibility with biologically derived impurities.
Through systematic optimization, the team established mild and selective catalytic strategies compatible with IPM. For example, phenol was successfully deoxygenated to benzene in up to 85% yield using a palladium-based catalytic system, while benzyl alcohol was efficiently converted to toluene after activated charcoal pretreatment of the IPM extract. More challenging transformations, such as converting 2-phenylethanol to ethylbenzene, were achieved through a mesylation–reduction sequence adapted to the IPM phase. Likewise, 2,5-xylenol derived from glycerol was converted to p-xylene in 62% yield via a two-step reaction, completing the renewable synthesis of the full BTEX spectrum.
A Sustainable, Modular Framework
Beyond producing BTEX, the study establishes a generalizable framework for integrating microbial biosynthesis with chemical transformations in a continuous solvent environment. This modular approach reduces energy demand, minimizes solvent waste, and enables process intensification—key factors for scaling up renewable chemical production.
The high boiling point of IPM (>300 °C) simplifies product recovery, as BTEX compounds can be isolated by fractional distillation while the solvent is readily recycled. Such a design is consistent with the principles of green chemistry and the circular economy, providing a practical alternative to fossil-based petrochemical processes.
Toward A Carbon-Neutral Future
Dr. Xuan Zou, the first author of this paper, explaind, “By coupling the selectivity of microbial metabolism with the efficiency of chemical catalysis, this platform establishes a renewable pathway to some of the most widely used building blocks in the chemical industry. Future efforts will focus on optimizing metabolic fluxes, extending the platform to additional aromatic targets, and adopting greener catalytic systems.”
In addition, Distinguished Professor Sang Yup Lee noted “As the global demand for BTEX and related chemicals continues to grow, this innovation provides both a scientific and industrial foundation for reducing reliance on petroleum-based processes. It marks an important step toward lowering the carbon footprint of the fuel and chemical sectors while ensuring a sustainable supply of essential aromatic hydrocarbons.”
This research was supported by the Development of Platform Technologies of Microbial Cell Factories for the Next-Generation Biorefineries Project (2022M3J5A1056117) and the Development of Advanced Synthetic Biology Source Technologies for Leading the Biomanufacturing Industry Project (RS-2024-00399424), funded by the National Research Foundation supported by the Korean Ministry of Science and ICT. This study was published in the latest issue of the Proceedings of the National Academy of Sciences of the United States of America (PNAS).
2025.10.13 View 917 -
KAIST Exports Global License for New Drug Candidate for Intractable Epilepsy Worth 750 Billion KRW
<(From Left) Professor Jeong Ho Lee, CEO Cheolwon Park, Principal Researcher Sang-min Park>
KAIST (President Kwang Hyung Lee) announced on the 9th of October that Sovargen (co-led by CEOs Cheolwon Park and Jeong Ho Lee), a faculty startup led by Professor Jeong Ho Lee of the KAIST Graduate School of Medical Science and Engineering, has successfully achieved a global technology export deal worth a total of 750 billion KRW. The deal involves an innovative RNA-based new drug candidate for the treatment of intractable epilepsy.
This achievement is drawing attention as a representative example of how groundbreaking discoveries from KAIST’s fundamental medical science research can evolve into actual drug development and global market expansion.
Professor Jeong Ho Lee’s research team was the first in the world to identify that the cause of severe brain diseases such as intractable epilepsy and malignant brain tumors lies in brain somatic mutations—acquired mutations that occur in neural stem cells. Their findings were published in Nature (2015) and Nature Medicine (2018).
Later, together with Cheolwon Park of Sovargen, an expert in drug development, they discovered an RNA-based therapeutic—an Antisense Oligonucleotide (ASO)—that directly targets MTOR, a key mutated gene responsible for epilepsy. Through a large-scale technology transfer agreement with a global pharmaceutical company, they also demonstrated the drug’s commercial potential.
This achievement is particularly significant in that it was led by Professor Jeong Ho Lee, a physician-scientist (M.D.-Ph.D.) who integrates intensive basic research with translational studies and venture entrepreneurship.
An idea that originated in a basic research lab has developed into the world’s first innovative drug (first-in-class) candidate through a startup, creating a virtuous cycle that connects back to the global market.
Sovargen’s Principal Researcher Sang Min Park (KAIST Graduate School of Medical Science and Engineering alumnus) stated, “From identifying the disease cause to developing a new drug and exporting the technology globally, this achievement was made possible entirely through the power of Korean science.” Sovargen CEO Cheolwon Park added, “This success was made possible thanks to the strong support of President Kwang Hyung Lee and key KAIST leaders for both the Graduate School of Medical Science and Engineering and faculty-led startups.”
Professor Jeong Ho Lee commented, “While traditional medical schools in Korea are centered around clinical practice, KAIST fosters a research culture focused on innovation and industrialization. This enabled us to achieve both groundbreaking basic research and global new drug technology export.” He continued, “This success serves as an excellent example of the future direction of KAIST’s medical science research.”
Experts have evaluated this accomplishment as one that opens new therapeutic possibilities for patients suffering from intractable epilepsy—conditions that previously had no treatment options—while also demonstrating that Korean medical science and biotech ventures are capable of competing on the global stage in innovative new drug development.
KAIST President Kwang Hyung Lee remarked, “This achievement is a representative example of how KAIST’s research philosophy—‘from fundamentals to industry’—has been realized in the field of medical science.” He added, “KAIST will continue to pursue bold fundamental research to lead innovations that advance human health and the future bioindustry.”
2025.10.10 View 661 -
Next Generation Robots Roaming Shipyards and City Centers
< Diden Robotics Research Team Co., Ltd (Leftmost person in the front row is CEO Joon-Ha Kim)>
KAIST announced on the September 30th that domestic robot startups, founded on KAIST research achievements, are driving new innovation at shipyards and urban worksites.
An industrial walking robot that freely climbs walls and ceilings and a humanoid walking robot that walks through downtown Gangnam are attracting attention as they enter the stage of commercialization. The stars are DIDEN Robotics Co., Ltd. and Eurobotics Co., Ltd.
Diden Robotics is providing a new breakthrough in the industrial automation market, including the shipbuilding industry, by commercializing its innovative 'Seungwol (Ascend and Cross) Robot' technology, which allows it to move freely and work on steel walls and ceilings. Eurobotics is commercializing world-class humanoid walking technology, and this achievement is scheduled to be officially presented at the international humanoid robot conference, 'Humanoids 2025,' to be held on October 1st.
< Diden Robot's Outer Plate (Longi) and Welding Test >
Diden Robotics is a robotics startup jointly founded in March 2024 by four alumni from the KAIST Mechanical Engineering Hu-bo Lab DRCD research team (Professor Hae-Won Park). Its flagship product, 'DIDEN 30,' is a quadrupedal robot designed for use in high-risk work environments that are difficult for humans to access, combining autonomous driving technology, a foot-shaped leg structure, and magnetic feet.
The 'DIDEN 30' successfully completed the 'Longitudinal (longi) Overcoming Test,' in which it stepped over steel stiffeners (longitudinals) densely installed as part of the structure at a ship construction site, proving its potential for field deployment. Currently, the company is conducting research to enhance its functionality so it can stably pass through access holes, the narrow entryways inside ships. It is also pushing for performance improvements so it can be deployed for real tasks such as welding, inspection, and painting starting in the second half of 2026.
A next-generation bipedal walking robot, 'DIDEN Walker,' is also under development. Targeting the completion of a prototype in the fourth quarter of 2025, it is being designed for stable walking in cramped and complex industrial environments. Plans are also underway to equip it with an upper-body manipulator for automated welding in the shipbuilding industry.
Diden Robotics is accelerating the advancement of its proprietary 'Physical AI' technology. The core is the self-developed AI learning platform, 'DIDEN World,' which applies an offline reinforcement learning method where the AI generates optimal motion data in a virtual simulation beforehand and learns without trial and error, increasing learning efficiency and stability.
< Diden Robot (DIDEN 30) >
Furthermore, to actually implement the AI technology, the company is internalizing its hardware and advancing its 3D recognition technology, which serves as the robot's 'eyes.' It is aiming for a completely autonomous walking system that requires no worker intervention by 2026, using technology such as 3D mapping based on four cameras.
In addition to this technological development, Diden Robotics successfully performed the longitudinal overcoming, Seungwol test, and welding work on blocks under construction through a joint development with Samsung Heavy Industries in September. This is a significant achievement, meaning Diden Robotics' technology has been validated in actual industrial settings, moving beyond the laboratory level.
Meanwhile, Diden Robotics is collaborating with major domestic shipyards, including Samsung Heavy Industries, HD Hyundai Samho, Hanwha Ocean, and HD Korea Shipbuilding & Offshore Engineering, to develop site-customized robots.
Joon-Ha Kim, CEO of Diden Robotics, stated, "The successful tests at the Samsung Heavy Industries site proved the practicality and stability of our technology. We will establish ourselves as a leading company in solving labor shortages and driving automation in the shipbuilding industry."
< (Eurobotics Research Team Co., Ltd.)(Leftmost person in the top row is CEO Byung-ho Yoo) >
Eurobotics is an autonomous walking startup jointly founded by three alumni from Professor Hyun Myung's research team at KAIST. It is promoting the commercialization of autonomous walking technology for indoor and outdoor industrial sites, including rough terrain. In a recently released video, a humanoid equipped with control technology developed by Eurobotics attracted attention by walking naturally through the crowd in downtown Gangnam.
The core technology is the 'Blind Walking Controller.' It determines locomotion based only on internal information without external sensors like cameras or LiDAR, enabling stable walking regardless of day, night, or weather. The robot performs locomotion by 'imagining' the terrain without precise terrain modeling, demonstrating robust performance with the same controller across various environments such as sidewalks, downhill slopes, and stairs.
This technology originated from the quadrupedal walking competition at the 2023 International Conference on Robotics and Automation (ICRA), where Professor Myung's lab participated, and proved its world-class capability by winning, beating MIT by a large margin. At the time, Byungg-ho Yoo, CEO of Eurobotics, led the team, and Co-CTOs Min-ho Oh and Dong-kyu Lee directly participated in developing the core autonomous walking technology. Based on this, they continued further development tailored to the humanoid environment and have entered the commercialization stage.
< Eurobotics' Humanoid Walking >
Byung-ho Yoo, CEO of Eurobotics, emphasized, "This video is the first step toward complete humanoid autonomous walking. We will develop KAIST's research achievements into technologies that can be immediately utilized in industrial settings."
Hyeonmin Bae, Head of the KAIST Startup Center, said, "We will provide close support from the initial stages to help the on-campus robotics industry grow actively and assist them in settling down stably."
Kwang Hyung Lee, President of KAIST, stated, "This achievement is a representative case showing that KAIST's fundamental technologies are rapidly spreading to industrial fields through startups. KAIST will continue to actively support innovative entrepreneurship based on challenging research and help lead the global robotics industry."
※ https://2025humanoids.org https://www.seoulairobot.com/
2025.09.30 View 1693 -
KAIST Develops Semiconductor Neuron that Remembers and Responds Like the Brain
<(From left, clockwise) Professor Kyung Min Kim, Min-Gu Lee, Dae-Hee Kim, Dr. Han-Chan Song, Tae-Uk Ko, Moon-Gu Choi, and Eun-Young Kim>
The human brain does more than simply regulate synapses that exchange signals; individual neurons also process information through “intrinsic plasticity,” the adaptive ability to become more sensitive or less sensitive depending on context. Existing artificial intelligence semiconductors, however, have struggled to mimic this flexibility of the brain. A KAIST research team has now developed next-generation, ultra-low-power semiconductor technology that implements this ability as well, drawing significant attention.
KAIST (President Kwang Hyung Lee) announced on September 28 that a research team led by Professor Kyung Min Kim of the Department of Materials Science and Engineering developed a “Frequency Switching Neuristor” that mimics “intrinsic plasticity,” a property that allows neurons to remember past activity and autonomously adjust their response characteristics.
“Intrinsic plasticity” refers to the brain’s adaptive ability- for example, becoming less startled when hearing the same sound repeatedly, or responding more quickly to a specific stimulus after repeated training. The “Frequency Switching Neuristor” is an artificial neuron device that autonomously adjusts the frequency of its signals, much like how the brain becomes less startled by repeated stimuli or, conversely, increasingly sensitive through training.
The research team combined a “volatile Mott memristor,” which reacts momentarily before returning to its original state, with a “non-volatile memristor,” which remembers input signals for long periods of time. This enabled the implementation of a device that can freely control how often a neuron fires (its spiking frequency).
<Figure 1. Conceptual comparison between a neuron and a frequency-tunable neuristor. The intrinsic plasticity of brain neurons regulates excitability through ion channels. Similarly, the frequency-tunable neuristor uses a volatile Mott device to generate current spikes, while a non-volatile VCM device adjusts resistance states to realize comparable frequency modulation characteristics>
In this device, neuronal spike signals and memristor resistance changes influence each other, automatically adjusting responses. Put simply, it reproduces within a single semiconductor device how the brain becomes less startled by repeated sounds or more sensitive to repeated stimuli.
To verify the effectiveness of this technology, the researchers conducted simulations with a “sparse neural network.” They found that, through the neuron’s built-in memory function, the system achieved the same performance with 27.7% less energy consumption compared to conventional neural networks.
They also demonstrated excellent resilience: even if some neurons were damaged, intrinsic plasticity allowed the network to reorganize itself and restore performance. In other words, artificial intelligence using this technology consumes less electricity while maintaining performance, and it can compensate for partial circuit failures to resume normal operation.
Professor Kyung Min Kim, who led the research, stated, “This study implemented intrinsic plasticity, a core function of the brain, in a single semiconductor device, thereby advancing the energy efficiency and stability of AI hardware to a new level. This technology, which enables devices to remember their own state and adapt or recover even from damage, can serve as a key component in systems requiring long-term stability, such as edge computing and autonomous driving.”
This research was carried out with Dr. Woojoon Park (now at Forschungszentrum Jülich, Germany) and Dr. Hanchan Song (now at ETRI) as co-first authors, and the results were published online on August 18 in Advanced Materials (IF 26.8), a leading international journal in materials science.
※ Paper title: “Frequency Switching Neuristor for Realizing Intrinsic Plasticity and Enabling Robust Neuromorphic Computing,” DOI: 10.1002/adma.202502255
This research was supported by the National Research Foundation of Korea and Samsung Electronics.
2025.09.30 View 901 -
KAIST, Cancer Cell Nuclear Hypertrophy May Suppress Spread
<(From Left) Ph.D candidate Saemyeong Hong, Dr. Changgon Kim, Professor Joon Kim, Professor Ji Hun Kim>
In tissue biopsies, cancer cells are frequently observed to have nuclei (the cell's genetic information storage) larger than normal. Until now, this was considered a sign that the cancer was worsening, but the exact cause and effect had not been elucidated. In this study, the KAIST research team found that cancer cell nuclear hypertrophy is not a cause of malignancy but a temporary response to replication stress, and that it can, in fact, suppress metastasis. This discovery is expected to lead to the development of new diagnostic and therapeutic strategies for cancer and metastasis inhibition.
KAIST (President Kwang Hyung Lee) announced on the September 26th that a research team led by Professor Joon Kim of the Graduate School of Medical Science and Engineering, in collaboration with the research teams of Professor Ji Hun Kim and Professor You-Me Kim, discovered the molecular reason why the nucleus enlarges in cancer cells. This achievement provides an important clue for understanding nuclear hypertrophy, a phenomenon frequently observed in pathological examinations but whose direct cause and relationship with cancer development were unclear.
The research team confirmed that DNA replication stress (the burden and error signal that occurs when a cell copies its DNA), which is common in cancer cells, causes the 'actin' protein inside the nucleus to aggregate (polymerize), which is the direct cause of the nuclear enlargement.
<Mechanisms Inducing Nuclear Enlargement in Cancer Cells and Its Impact on Cellular Physiology>
This result suggests that the change in cancer cell nuclear size may not simply be a "trait evolved by the cancer cell for its benefit." Rather, it suggests that it is a temporary, makeshift response to stress, and that it may impose constraints on the cancer cell's potential for metastasis.
Therefore, future research needs to explore whether changes in nuclear size can become a target for cancer treatment or a clue related to the suppression of metastasis. That is, nuclear hypertrophy may be a temporary response to replication stress and should not necessarily be seen as indicating the malignancy of the cancer.
This conclusion was substantiated through: (1) Gene Function Screening (inhibiting thousands of genes sequentially to find the key genes involved in nuclear size regulation); (2) Transcriptome Analysis (confirming which gene programs are activated when the nucleus enlarges); (3) 3D Genome Structure Analysis (Hi-C), which revealed that nuclear hypertrophy is not just a size change but is connected to changes in DNA folding and gene arrangement; and (4) Mouse Xenograft Models (confirming that cancer cells with enlarged nuclei actually have reduced motility and metastatic ability).
Professor Joon Kim of the Graduate School of Medical Science and Engineering said, "We confirmed that DNA replication stress disrupts the nuclear size balance, explaining the underlying mechanism of long-standing pathological observations," adding, "The possibility of utilizing nuclear structural changes as a new indicator for cancer diagnosis and metastasis prediction has now opened up."
Dr. Changgon Kim (currently a Hematology and Oncology specialist at Korea University Anam Hospital) and Saemyeong Hong, a PhD candidate from the KAIST Graduate School of Medical Science and Engineering, participated as co-first authors in this study. The results were published online in the international journal PNAS (Proceedings of the National Academy of Sciences of the United States of America) on September 9th.
※ Paper Title: Replication stress-induced nuclear hypertrophy alters chromatin topology and impacts cancer cell fitness ※ DOI: https://doi.org/10.1073/pnas.2424709122
Meanwhile, this research was supported by the Mid-career Researcher Program and the Engineering Research Center (ERC) program of the National Research Foundation of Korea.
2025.09.29 View 871 -
Thinking outside the box to Fabricate Customized 3D Neural Chips
<(From Left) Professor Yoonkey Nam, Dr. Dongjo Yoon from the Department of Bio and Brain Engineering>
Cultured neural tissues have been widely used as a simplified experimental model for brain research. However, existing devices for growing and recording neural tissues, which are manufactured using semiconductor processes, have limitations in terms of shape modification and the implementation of three-dimensional (3D) structures.
By "thinking outside the box," a KAIST research team has successfully created a customized 3D neural chip. They first used a 3D printer to fabricate a hollow channel structure, then used capillary action to automatically fill the channels with conductive ink, creating the electrodes and wiring. This achievement is expected to significantly increase the design freedom and versatility of brain science and brain engineering research platforms.
On the 25th, KAIST announced that a research team led by Professor Yoonkey Nam from the Department of Bio and Brain Engineering has successfully developed a platform technology that overcomes the limitations of traditional semiconductor-based manufacturing. This technology allows for the precise fabrication of "3D microelectrode array" (neural interfaces with multiple microelectrodes arranged in a 3D space to measure and stimulate the electrophysiological signal of neurons) in various customized forms for in vitro culture chips.
Existing 3D microelectrode array fabrication, based on semiconductor processes, has limited 3D design freedom and is expensive. While 3D printing-based fabrication techniques have recently been proposed to overcome these issues, they still have limitations in terms of 3D design freedom for various in vitro neural network structures because they follow the traditional sequence of "conductive material patterning → insulator coating → electrode opening."
The KAIST research team leveraged the excellent 3D design freedom provided by 3D printing technology and its ability to use printed materials as insulators. By reversing the traditional process, they established an innovative method that allows for more flexible design and functional measurement of 3D neuronal network models for in vitro culture.
<Schematic Diagram of an Integrated Cell Culture Substrate-Microelectrode Array Platform for In Vitro Cultured 3D Neural Network Models>
First, they used a 3D printer to print a hollow 3D insulator with micro-tunnels. This structure was designed to serve as a stable scaffold for conductive materials in 3D space while also supporting the creation of various 3D neuronal networks. They then demonstrated that by using capillary action to fill these internal micro-tunnels with conductive ink, they could create a 3D scaffold-microelectrode array with more freely arranged microelectrodes within a complex 3D culture support structure.
The new platform can be used to create various chip shapes, such as probe-type, cube-type, and modular-type, and supports the fabrication of electrodes using different materials like graphite, conductive polymers, and silver nanoparticles. This allows for the simultaneous measurement of multichannel neural signals from both inside and outside the 3D neuronal network, enabling precise analysis of the dynamic interactions and connectivity between neurons.
Professor Nam stated, "This research, which combines 3D printing and capillary action, is an achievement that significantly expands the freedom of neural chip fabrication." He added that it will contribute to the advancement of fundamental brain science research using neural tissue, as well as applied fields like cell-based biosensors and biocomputing.
Dr. Dongjo Yoon from KAIST's Department of Bio and Brain Engineering participated as the first author of the study. The research findings were published online in the international academic journal Advanced Functional Materials (June 25th issue).
※Paper Title: Highly Customizable Scaffold-Type 3D Microelectrode Array Platform for Design and Analysis of the 3D Neuronal Network In Vitro
This research was supported by the Consolidator Grants Program and the Global Basic Research Laboratory Program of the National Research Foundation of Korea.
2025.09.26 View 761