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Playground for Future Quantum Technology: KAIST-MIT Quantum Information Winter School Successfully Concluded
< Group photo of the KAIST-MIT Quantum Information Winter School >
“Through the KAIST-MIT Quantum Information Winter School, I was able to view research from a broader perspective. The experience of collaborating with students from various universities and majors to complete a project was very refreshing,” said Jun-hyeong Cho, a student at the KAIST School of Electrical Engineering.
KAIST announced on the 16th that the Graduate School of Quantum Science and Technology successfully concluded the ‘KAIST-MIT Quantum Information Winter School,’ held jointly with the Massachusetts Institute of Technology (MIT) from January 5th to 16th at the KAIST main campus in Daejeon.
For this year’s Winter School, 50 junior and senior undergraduate students from Korea and abroad were selected to receive intensive training to grow into next-generation quantum talent. Eight world-renowned scholars from KAIST and MIT participated in the program, providing a multi-dimensional curriculum that spanned theory and practice—ranging from theoretical lectures and introductions to cutting-edge quantum experiments to visits to government-funded research institutes and student poster presentations.
Celebrating its third anniversary since its inception in 2024, the Winter School is now evaluated as a premier quantum information education program in Korea. Alongside KAIST faculty, world-class scholars from MIT participated directly in lectures and field training, operating an intensive curriculum that covered the entirety of quantum information science.
The lecturing faculty included world authorities in quantum computing, quantum devices, quantum machine learning, and quantum simulation, such as MIT professors Pablo Jarillo-Herrero, Seth Lloyd, Kevin P. O’Brien, and William D. Oliver, as well as KAIST scholars Jaewook Ahn, Joonwoo Bae, Gil-Young Cho, and Jae-yoon Choi.
Going beyond theoretical lectures, participants gained a broad understanding of research trends, technical limitations, and future development directions of state-of-the-art quantum technology through experimental training in core areas such as quantum computing, communication, sensing, and simulation.
< Scene from a Winter School lecture >
Furthermore, students visited the Korea Research Institute of Standards and Science (KRISS) and the Electronics and Telecommunications Research Institute (ETRI) to experience actual research sites, engaging in field-oriented education that bridges quantum theory and practice. The poster presentation session, where students shared their own research ideas, received enthusiastic responses as a forum for deep academic exchange, allowing students to receive direct feedback from MIT faculty.
Tae-hee Kim, a student from Pusan National University, remarked, “I was greatly inspired by the passion of the MIT faculty and the high level of questions from the students. It served as a motivation for me to pursue deeper studies independently.” Byung-jin Hwang, a student from Yonsei University, added, “I expected lectures from world-class scholars to be difficult, but I was impressed by the explanations tailored to the undergraduate level. The poster presentation session was particularly memorable.”
Eun-seong Kim, Dean of the KAIST Graduate School of Quantum Science and Technology, stated, “The KAIST-MIT Quantum Information Winter School is a special educational program where students can learn directly from world-renowned quantum researchers and experience cutting-edge research. We look forward to the active participation of future talents who will lead the quantum industry.”
Participants for this Winter School were selected through a document review process, and the program was operated entirely free of charge. KAIST covered all educational expenses and provided dormitory accommodations and lunch. Detailed information about the event can be found on the KAIST Graduate School of Quantum Science and Technology website (https://quantumschool.kaist.ac.kr/).
< Poster for the KAIST-MIT Quantum Information Winter School >
2026.01.16 View 2289 -
Chairman Jae-Chul Kim of Dongwon Group Donates a Total of 60.3 Billion Won to KAIST
<Jae-Chul Kim, Honorary Chairman of Dongwon Group>
"In the era of AI, a new future lies within the sea of data. I ask that KAIST leaps forward to become the world's No. 1 AI research group." — Jae-Chul Kim, Honorary Chairman of Dongwon Group
KAIST announced on January 16th that Honorary Chairman Jae-Chul Kim of Dongwon Group has pledged an additional 5.9 billion KRW in development funds to foster Artificial Intelligence (AI) talent and strengthen research infrastructure, bringing his total contribution to 60.3 billion KRW. This marks his second additional donation since 2020, continuing his steadfast support for strengthening South Korea's national competitiveness in the field of AI.
Through his initial donation in 2020, Chairman Kim established the 'Kim Jaechul Graduate School of AI' at KAIST, urging the university to secure world-class capabilities. Upon hearing that KAIST’s AI research level ranked 5th among global universities over the past five years (2020–2024), Chairman Kim requested that the university strive to reach the No. 1 spot in the world.
In response, President Kwang Hyung Lee explained, "To surpass Carnegie Mellon University (CMU), which is currently evaluated as the world’s best with an AI faculty of about 45, the KAIST Graduate School of AI needs to expand its faculty to over 50 and construct a dedicated research building." Chairman Kim responded by saying, "I will build the building," and this latest donation is a fulfillment of that promise.
This third pledge of 5.9 billion KRW was decided to cover the projected budget shortfall as the design of the AI Education and Research Building enters full-scale development.
The AI Education and Research Building will be a facility with 8 floors above ground and 1 basement level, covering a total floor area of 18,182 m² (approx. 5,500 pyeong). It is scheduled for completion in February 2028. Once finished, it will serve as a global AI research hub housing 50 faculty members and 1,000 students.
Since the 2021 academic year, KAIST has been selecting 60 Master’s and 10 Doctoral students annually as 'Dongwon Scholars' outside of the regular quota for a period of 10 years. While the tuition and research incentives for the first three years were supported by the donation, KAIST has been utilizing its own budget since the 2024 academic year to ensure students can focus entirely on their research.
Moving forward, the Kim Jaechul Graduate School of AI plans to build a world-class faculty and operate systematic Master's and Doctoral programs to cultivate global AI leaders. In addition to technical expertise, the school will offer educational programs focused on character and holistic development, leading the charge in strengthening Korea's AI competitiveness.
Honorary Chairman Jae-Chul Kim stated, "I hope this donation serves as a small 'priming water' for South Korea to leap forward as an AI powerhouse. I look forward to seeing global core talents grow here and contribute to our national strength."
President Kwang Hyung Lee expressed his gratitude, saying, "Chairman Kim’s unwavering support is the greatest driving force for KAIST to secure global AI sovereignty. We will ensure the Kim Jaechul Graduate School of AI becomes a mecca where the world's best AI minds gather to innovate, honoring the Chairman’s vision."
2026.01.16 View 2112 -
KAIST Proposes AI-Driven Strategy to Solve Long-Standing Mystery of Gene Function
<(From Left) Distinguisehd Professor Sang Yup Lee, Dr. Gi Bae Kim, Professor Bernhard O. Palsson>
“We know the genes, but not their functions.” To resolve this long-standing bottleneck in microbial research, a joint research team has proposed a cutting-edge research strategy that leverages Artificial Intelligence (AI) to drastically accelerate the discovery of microbial gene functions.
KAIST announced on January 12th that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, in collaboration with Professor Bernhard Palsson from the Department of Bioengineering at UCSD, has published a comprehensive review paper. The study systematically analyzes and organizes the latest AI-based research approaches aimed at revolutionizing the speed of gene function discovery.
Since the early 2000s, when whole-genome sequencing became a reality, there were high expectations that the genetic blueprint of life would be fully decoded. However, even twenty years later, the roles of a significant portion of genes within microbial genomes remain unknown.
While various experimental methods—such as gene deletion, analysis of gene expression profiles, and in vitro activity assays—have been employed, discovering gene functions remains a time-consuming and costly endeavor. This is primarily due to the limitations of large-scale experimentation, complex biological interactions, and the discrepancy between laboratory results and actual in vivo responses.
To overcome these hurdles, the research team emphasized that an AI-driven approach combining computational biology with experimental biology is essential.
In this paper, the team provides a comprehensive overview of computational biology approaches that have facilitated gene function discovery, ranging from traditional sequence similarity analysis to the latest deep-learning-based AI models.
Notably, 3D protein structure prediction technologies such as AlphaFold (developed by Google DeepMind) and RoseTTAFold (developed by the University of Washington) have opened new doors. These tools go beyond simple functional estimation, offering the potential to understand the underlying mechanisms of how gene functions operate. Furthermore, generative AI is now extending research boundaries toward designing proteins with specifically desired functions.
Focusing on transcription factors (proteins that act as genetic switches) and enzymes (proteins that catalyze chemical reactions), the team presented various application cases and future research directions that integrate gene sequence analysis, protein structure prediction, and diverse metagenomic analyses.
<Schematic illustration of computational biology methods for enzyme function prediction>
2026.01.12 View 2071 -
KAIST-Yonsei Team Identifies Origin Cells for Malignant Brain Tumor Common in Young Adults
<Dr. Jung Won Park, (Upper Right) Professor Jeong Ho Lee, Professor Seok-Gu Kang>
IDH-mutant glioma, caused by abnormalities in a specific gene (IDH), is the most common malignant brain tumor among young adults under the age of 50. It is a refractory brain cancer that is difficult to treat due to its high recurrence rate. Until now, treatment has focused primarily on removing the visible tumor mass. However, a Korean research team has discovered for the first time that normal brain cells acquire the initial IDH mutation and spread out through the cortex long before a visible tumor mass harboring additional cancer mutations forms, opening a new path for early diagnosis and treatment to suppress recurrence.
KAIST announced on January 9th that a joint research team led by Professor Jeong Ho Lee from the Graduate School of Medical Science and Engineering and Professor Seok-Gu Kang from the Department of Neurosurgery at Yonsei University Severance Hospital has identified that IDH-mutant gliomas originate from Glial Progenitor Cells (GPCs) present in normal brain tissue.
Glial Progenitor Cells (GPC): Cells that exist in the normal brain and can become the starting point for malignant brain tumors if genetic mutations occur.
Through precise analysis of tumor tissue obtained via extensive resection surgery and the surrounding normal cerebral cortex, the research team discovered that "cells of origin" harboring the IDH mutation already existed within brain tissue that appeared normal to the naked eye.
< Brain-Derived Refractory Brain Tumor Origin Cells (AI-Generated Image) >
This result proves for the first time that malignant brain tumors do not emerge suddenly at a specific point in time, but rather begin within a normal brain and progress slowly over a long period.
The research team then used "spatial transcriptomics"—a cutting-edge analysis technology that shows "which genes are operating where" simultaneously—to confirm that these origin cells with mutations were indeed Glial Progenitor Cells (GPCs) located in the cerebral cortex.
Furthermore, they successfully reproduced the process of brain tumor development in an animal model by introducing the same genetic "driver mutation" found in patients into the GPCs of mice.
This study is a significant expansion of previous research identifying the "origin" of IDH wildtype malignant brain tumors. In 2018, the joint research team led a paradigm shift in brain tumor research by revealing that IDH wildtype glioblastoma, a representative malignant brain tumor, originates not from the tumor body itself, but from neural stem cells in the subventricular zone—the source of new brain cells in the adult brain (Lee et al., Nature, 2018).
The current study clarifies that even though "IDH wildtype glioblastoma" and "IDH-mutant glioma" are both types of brain cancer, their starting cells and points of origin are entirely different, proving that different types of brain tumors have fundamentally different developmental processes.
< Mechanistic Elucidation of Malignant Brain Tumor Development Induced by IDH Mutations and Subsequent Genetic Alterations in Normal Cortical Glial Progenitor Cells >
Professor Seok-Gu Kang (Co-Corresponding Author) stated, "Brain tumors may not start exactly where the tumor mass is visible. A target approach focused on the origin cells and the site of origin according to the brain tumor subtype will serve as a crucial clue to changing the paradigm of early diagnosis and recurrence suppression treatment."
Based on these research results, Sovagen Co., Ltd, a faculty startup from KAIST, is developing an innovative RNA-based drug to suppress the evolution and recurrence of IDH-mutant malignant brain tumors. Additionally, Severance Hospital is pursuing the development of technologies to detect and control early mutant cells in refractory brain tumors through the Korea-US Innovative Result Creation R&D project.
Dr. Jung Won Park (Postdoctoral Researcher at KAIST Graduate School of Medical Science and Engineering), a neurosurgeon and the sole first author of the study, said, "This achievement was made possible by combining KAIST’s world-class basic science research capabilities with the clinical expertise of Yonsei Severance Hospital. The question I kept asking while treating patients—'Where does this tumor originate?'—was the starting point of this research."
The findings were published on January 8th in the world-renowned academic journal Science.
Paper Title: IDH-mutant gliomas arise from glial progenitor cells harboring the initial driver mutation
DOI: 10.1126/science.adt0559
Authors: Jung Won Park (KAIST, First Author), Seok-Gu Kang (Yonsei Severance Hospital, Corresponding Author), Jeong Ho Lee (KAIST, Sovagen, Corresponding Author)
This research was conducted with support from the Suh Kyung-bae Science Foundation, the National Research Foundation of Korea, the Ministry of Science and ICT, the Ministry of Health and Welfare, and the Korea Health Industry Development Institute (Physician-Scientist Training Program).
2026.01.09 View 1908 -
Direct Printing of Nanolasers, the Key to Optical Computing and Quantum Security
< (From left) Professor Ji Tae Kim (KAIST), Dr. Shiqi Hu (First Author, AI-based Intelligent Design-Manufacturing Integrated Research Group, KAIST-POSTECH), and Professor Junsuk Rho (POSTECH) >
In future high-tech industries, such as high-speed optical computing for massive AI, quantum cryptographic communication, and ultra-high-resolution augmented reality (AR) displays, nanolasers—which process information using light—are gaining significant attention as core components for next-generation semiconductors. A research team at our university has proposed a new manufacturing technology capable of high-density placement of nanolasers on semiconductor chips, which process information in spaces thinner than a human hair.
KAIST announced on January 6th that a joint research team, led by Professor Ji Tae Kim from the Department of Mechanical Engineering and Professor Junsuk Rho from POSTECH (President Seong-keun Kim), has developed an ultra-fine 3D printing technology capable of creating "vertical nanolasers," a key component for ultra-high-density optical integrated circuits.
Conventional semiconductor manufacturing methods, such as lithography, are effective for mass-producing identical structures but face limitations: the processes are complex and costly, making it difficult to freely change the shape or position of devices. Furthermore, most existing lasers are built as horizontal structures lying flat on a substrate, which consumes significant space and suffers from reduced efficiency due to light leakage into the substrate.
To solve these issues, the research team developed a new 3D printing method to vertically stack perovskite, a next-generation semiconductor material that generates light efficiently. This technology, known as "ultra-fine electrohydrodynamic 3D printing," uses electrical voltage to precisely control invisible ink droplets at the attoliter scale ($10^{-18}$ L).
Through this method, the team successfully printed pillar-shaped nanostructures—much thinner than a human hair—directly and vertically at desired locations without the need for complex subtractive processes (carving material away).
The core of this technology lies in significantly increasing laser efficiency by making the surface of the printed perovskite nanostructures extremely smooth. By combining the printing process with gas-phase crystallization control technology, the team achieved high-quality structures with nearly single-crystalline alignment. As a result, they were able to realize high-efficiency vertical nanolasers that operate stably with minimal light loss.
Additionally, the team demonstrated that the color of the emitted laser light could be precisely tuned by adjusting the height of the nanostructures. Utilizing this, they created laser security patterns invisible to the naked eye—identifiable only with specialized equipment—confirming the potential for commercialization in anti-counterfeiting technology.
< 3D Printing of Perovskite Nanolasers >
Professor Jitae Kim stated, "This technology allows for the direct, high-density implementation of optical computing semiconductors on a chip without complex processing. It will accelerate the commercialization of ultra-high-speed optical computing and next-generation security technologies."
The research results, with Dr. Shiqi Hu from the Department of Mechanical Engineering as the first author, were published online on December 6, 2025, in ACS Nano, an international prestigious journal in the field of nanoscience.
Paper Title: Nanoprinting with Crystal Engineering for Perovskite Lasers
DOI: https://doi.org/10.1021/acsnano.5c16906
This research was conducted with support from the Ministry of Science and ICT’s Excellent Young Researcher Program (RS-2025-00556379), the Mid-career Researcher Support Program (RS-2024-00356928), and the InnoCORE AI-based Intelligent Design-Manufacturing Integrated Research Group (N10250154).
2026.01.06 View 2266 -
President Kwang Hyung Lee, 2026 New Year Message
In his 2026 New Year’s Address, KAIST President Kwang Hyung Lee stated, “Based on the ‘QAIST-New Culture Strategy’ that encourages asking questions and taking on challenges, KAIST will accelerate AI-centered innovation in education and research to leap forward as a world-class university.”
President Lee highlighted the major achievements of the past year, including:
▲Educational innovation to nurture inquisitive minds ▲Advancement of education and research systems through the establishment of the College of AI ▲Establishment of a postdoc-centered research ecosystem through the InnoCORE Program, a national initiative to cultivate world-class AI talent ▲An approximately 20 percent increase in research funding ▲Expansion of research collaboration with global companies and universities
Particularly in the education sector, he explained that KAIST has fostered a culture where failure is viewed as a starting point for new challenges. This has been achieved through initiatives such as student-generated exam questions, the ‘Problem Definition to Solution Program (PDSP)’—where students define and solve problems on their own—and the operation of ‘KAIST Failure Week.’
He emphasized that these changes led to tangible results, with undergraduate early-admission applicants increasing by 1.9 times and graduate school applicants by 1.3 times over the past three years.
At the same time, efforts have been made to improve students' learning and living environments. KAIST has pursued the renovation and remodeling of all dormitories and enhanced student dining facilities and menu options to ensure students enjoy a more comfortable campus life. President Lee stressed, “The most precious members of KAIST are our students, and the university's role is to create an environment where they can freely ask questions and take on challenges.”
In the research field, KAIST secured billions of Korean won in annual research funding through joint initiatives with Germany’s Merck and Taiwan’s Formosa Group. It also established a strategic hub connecting to the global startup ecosystem through the KAIST–IDIS Silicon Valley Campus. Furthermore, 26 buildings have been newly constructed or expanded over the past five years, and 24 buildings are currently under construction or scheduled to break ground, ensuring the continuous expansion of education and research infrastructure.
In terms of technology commercialization, as of 2025, KAIST launched 59 deep-tech startups and completed technology transfers totaling KRW 8.2 billion. Notably, Sovargen, a faculty startup, successfully concluded a KRW 750 billion technology export deal.
President Lee presented the following key priorities for 2026: ▲Elevating the College of AI to a world-leading level ▲Advancing the Pyeongtaek, Osong, and Sejong campus projects ▲Expanding global partnerships ▲Ensuring the safe execution of 24 major construction projects
President Lee concluded by saying, “KAIST has now firmly established itself as a leading university representing the Republic of Korea, and its global recognition is rising rapidly through internationalization efforts. If we continue to work together in 2026, KAIST will stand proudly as a truly world-class university.”
2025.12.31 View 4497 -
KAIST Awakens dormant immune cells inside tumors to attack cancer
<(From Left) Professor Ji-Ho Park, Dr. Jun-Hee Han from the Department of Bio and Brain Engineering>
Within tumors in the human body, there are immune cells (macrophages) capable of fighting cancer, but they have been unable to perform their roles properly due to suppression by the tumor. KAIST researchers have overcome this limitation by developing a new therapeutic approach that directly converts immune cells inside tumors into anticancer cell therapies.
KAIST (President Kwang Hyung Lee) announced on the 30th that a research team led by Professor Ji-Ho Park of the Department of Bio and Brain Engineering has developed a therapy in which, when a drug is injected directly into a tumor, macrophages already present in the body absorb it, produce CAR (a cancer-recognizing device) proteins on their own, and are converted into anticancer immune cells known as “CAR-macrophages.”
Solid tumors—such as gastric, lung, and liver cancers—grow as dense masses, making it difficult for immune cells to infiltrate tumors or maintain their function. As a result, the effectiveness of existing immune cell therapies has been limited.
CAR-macrophages, which have recently attracted attention as a next-generation immunotherapy, have the advantage of directly engulfing cancer cells while simultaneously activating surrounding immune cells to amplify anticancer responses.
However, conventional CAR-macrophage therapies require immune cells to be extracted from a patient’s blood, followed by cell culture and genetic modification. This process is time-consuming, costly, and has limited feasibility for real-world patient applications.
To address this challenge, the research team focused on “tumor-associated macrophages” that are already accumulated around tumors.
They developed a strategy to directly reprogram immune cells in the body by loading lipid nanoparticles—designed to be readily absorbed by macrophages—with both mRNA encoding cancer-recognition information and an immunostimulant that activates immune responses.
In other words, in this study, CAR-macrophages were created by “directly converting the body’s own macrophages into anticancer cell therapies inside the body.”
<Figure . Schematic illustration of the strategy for in vivo CAR-macrophage generation and cancer cell eradication via co-delivery of CAR mRNA and immunostimulants using lipid nanoparticles (LNPs)>
When this therapeutic agent was injected into tumors, macrophages rapidly absorbed it and began producing proteins that recognize cancer cells, while immune signaling was simultaneously activated. As a result, the generated “enhanced CAR-macrophages” showed markedly improved cancer cell–killing ability and activated surrounding immune cells, producing a powerful anticancer effect.
In animal models of melanoma (the most dangerous form of skin cancer), tumor growth was significantly suppressed, and the therapeutic effect was shown to have the potential to extend beyond the local tumor site to induce systemic immune responses.
Professor Ji-Ho Park stated, “This study presents a new concept of immune cell therapy that generates anticancer immune cells directly inside the patient’s body,” adding that “it is particularly meaningful in that it simultaneously overcomes the key limitations of existing CAR-macrophage therapies—delivery efficiency and the immunosuppressive tumor environment.”
This research was led by Jun-Hee Han, Ph.D., of the Department of Bio and Brain Engineering at KAIST as the first author, and the results were published on November 18 in ACS Nano, an international journal in the field of nanotechnology.
※ Paper title: “In Situ Chimeric Antigen Receptor Macrophage Therapy via Co-Delivery of mRNA and Immunostimulant,” Authors: Jun-Hee Han (first author), Erinn Fagan, Kyunghwan Yeom, Ji-Ho Park (corresponding author), DOI: 10.1021/acsnano.5c09138
This research was supported by the Mid-Career Researcher Program of the National Research Foundation of Korea.
2025.12.31 View 3620 -
Presenting a Brain-Like Next-Generation AI Semiconductor that Sees and Judges Instantly
< (From left) Professor Sanghun Jeon, Ph.D candidate Seungyeob Kim, Postdoctoral researcher Hongrae Cho, Ph.D candidates Sang-ho Lee and Taeseung Jung, and M.S candidate Seonjae Park >
With the advancement of Artificial Intelligence (AI), the importance of ultra-low-power semiconductor technology that integrates sensing, computation, and memory into a single unit is growing. However, conventional structures face challenges such as power loss due to data movement, latency, and limitations in memory reliability. A Korean research team has drawn international academic attention by presenting core technologies for an integrated ‘Sensor–Compute–Store’ AI semiconductor to solve these issues.
KAIST announced on December 31st that Professor Sanghun Jeon’s research team from the School of Electrical Engineering presented a total of six papers at the ‘International Electron Devices Meeting (IEEE IEDM 2025)’—the world’s most prestigious semiconductor conference—held in San Francisco from December 8 to 10. Among these, the papers were simultaneously selected as a Highlight Paper and a Top Ranked Student Paper.
Highlight Paper: Monolithically Integrated Photodiode–Spiking Circuit for Neuromorphic Vision with In-Sensor Feature Extraction [Link: https://iedm25.mapyourshow.com/8_0/sessions/session-details.cfm?scheduleid=255]
Top Ranked Student Paper: A Highly Reliable Ferroelectric NAND Cell with Ultra-thin IGZO Charge Trap Layer; Trap Profile Engineering for Endurance and Retention Improvement [Link: https://iedm25.mapyourshow.com/8_0/sessions/session-details.cfm?scheduleid=124]
The research on the M3D integrated neuromorphic vision sensor, selected as a highlight paper, is a semiconductor that stacks the human eye and brain within a single chip. Simply put, the sensors that detect light and the circuits that process signals like a brain are made into very thin layers and stacked vertically in one chip, implementing a structure where the process of 'seeing' and 'judging' occurs simultaneously.
Through this, the research team completed the world's first "In-Sensor Spiking Convolution" platform, where AI computation technology that "sees and judges at the same time" takes place directly within the camera sensor.
< Figure 1. Summary of research on vertically stacked optical signal-to-spike frequency converter for AI >
< Figure 2. Representative diagram of the development of a 2T-2C near-pixel analog computing cell based on oxide thin-film transistors >
Previously, this technology required several stages: capturing an image (sensor), converting it to digital (ADC), storing it in memory (DRAM), and then calculating (CNN). However, this new technology eliminates unnecessary data movement as the calculation happens immediately within the sensor. As a result, it has become possible to implement real-time, ultra-low-power Edge AI with significantly reduced power consumption and dramatically improved response speeds.
Based on this approach, the research team presented six core technologies at the conference covering all layers of AI semiconductors, from input to storage. They simultaneously created neuromorphic semiconductors that operate like the brain using much less electricity while utilizing existing semiconductor processes, along with next-generation memory optimized for AI.
First, on the sensor side, they designed the system so that judgment occurs at the sensor stage rather than having separate components for capturing images and calculating. Consequently, power consumption decreased and response speeds increased compared to the conventional method of taking a photo and sending it to another chip for calculation.
< Figure 3. Schematic diagram of a next-generation biomimetic tactile system using neuromorphic devices >
< Figure 4. Representative diagram of NC-NAND development research based on Ultra-thin-Mo and Sub-3.5 nm HZO >
Furthermore, in the field of memory, they implemented a next-generation NAND flash that uses the same materials but operates at lower voltages, lasts longer, and can store data stably even when the power is turned off. Through this, they presented a foundational technology that satisfies the requirements for high-capacity, high-reliability, and low-power memory necessary for AI.
< Figure 5. Representative diagram of next-generation 3D FeNAND memory development research >
< Figure 6. Representative diagram of research on charge behavior characterization and quantitative analysis methodology for next-generation FeNAND memory >
Professor Sanghun Jeon, who led the research, stated, "This research is significant in that it demonstrates that the entire hierarchy can be integrated into a single material and process system, moving away from the existing AI semiconductor structure where sensing, computation, and storage were designed separately." He added, "Moving forward, we plan to expand this into a next-generation AI semiconductor platform that encompasses everything from ultra-low-power Edge AI to large-scale AI memory."
Meanwhile, this research was conducted with support from basic research projects of the Ministry of Science and ICT and the National Research Foundation of Korea, as well as the Center for Heterogeneous Integration of Extreme-scale & Property Semiconductors (CH³IPS). It was carried out in collaboration with Samsung Electronics, Kyungpook National University, and Hanyang University.
2025.12.31 View 1628 -
Turning PC and Mobile Devices into AI Infrastructure, Reducing ChatGPT Costs
< (From left) KAIST School of Electrical Engineering: Dr. Jinwoo Park, M.S candidate Seunggeun Cho, and Professor Dongsu Han >
Until now, AI services based on Large Language Models (LLMs) have mostly relied on expensive data center GPUs. This has resulted in high operational costs and created a significant barrier to entry for utilizing AI technology. A research team at KAIST has developed a technology that reduces reliance on expensive data center GPUs by utilizing affordable, everyday GPUs to provide AI services at a much lower cost.
On December 28th, KAIST announced that a research team led by Professor Dongsu Han from the School of Electrical Engineering developed 'SpecEdge,' a new technology that significantly lowers LLM infrastructure costs by utilizing affordable, consumer-grade GPUs widely available outside of data centers.
SpecEdge is a system where data center GPUs and "edge GPUs"—found in personal PCs or small servers—collaborate to form an LLM inference infrastructure. By applying this technology, the team successfully reduced the cost per token (the smallest unit of text generated by AI) by approximately 67.6% compared to methods using only data center GPUs.
To achieve this, the research team utilized a method called 'Speculative Decoding.' In this process, a small language model placed on the edge GPU quickly generates a high-probability token sequence (a series of words or word fragments). Then, the large-scale language model in the data center verifies this sequence in batches. During this process, the edge GPU continues to generate words without waiting for the server's response, simultaneously increasing LLM inference speed and infrastructure efficiency.
< Figure 1. Language data flow diagram of the developed SpecEdge >
< Figure 2. Detailed computation time reduction method of SpecEdge >
< Figure 3. Illustration of efficient batching of verification requests from multiple edge GPUs on the server GPU within SpecEdge >
Compared to performing speculative decoding solely on data center GPUs, SpecEdge improved cost efficiency by 1.91 times and server throughput by 2.22 times. Notably, the technology was confirmed to work seamlessly even under standard internet speeds, meaning it can be immediately applied to real-world services without requiring a specialized network environment.
Furthermore, the server is designed to efficiently process verification requests from multiple edge GPUs, allowing it to handle more simultaneous requests without GPU idle time. This has realized an LLM serving infrastructure structure that utilizes data center resources more effectively.
This research presents a new possibility for distributing LLM computations—which were previously concentrated in data centers—to the edge, thereby reducing infrastructure costs and increasing accessibility. In the future, as this expands to various edge devices such as smartphones, personal computers, and Neural Processing Units (NPUs), high-quality AI services are expected to become available to a broader range of users.
< Figure 4. Conceptual comparison of the developed SpecEdge vs. conventional methods >
Professor Dongsu Han, who led the research, stated, "Our goal is to utilize edge resources around the user, beyond the data center, as part of the LLM infrastructure. Through this, we aim to lower AI service costs and create an environment where anyone can utilize high-quality AI."
Dr. Jinwoo Park and M.S candidate Seunggeun Cho from KAIST participated in this study. The research results were presented as a 'Spotlight' (top 3.2% of papers, with a 24.52% acceptance rate) at the NeurIPS (Neural Information Processing Systems) conference, the world's most prestigious academic conference in the field of AI, held in San Diego from December 2nd to 7th.
Paper Title: SpecEdge: Scalable Edge-Assisted Serving Framework for Interactive LLMs
Paper Links: NeurIPS Link, arXiv Link
This research was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP) under the project 'Development of 6G System Technology to Support AI-Native Application Services.'
2025.12.29 View 2135 -
Vieworks CEO Hu-sik Kim Appointed as 28th KAIST Alumni Association President
< Hu-sik Kim, 28th President of KAIST Alumni Association (CEO of Vieworks) >
KAIST announced on December 23rd that Hu-sik Kim, CEO of Vieworks—a company specializing in medical and industrial imaging solutions—has been appointed as the 28th President of the KAIST Alumni Association.
President-elect Hu-sik Kim, an alumnus with a Master’s degree in Physics (Class of ’95) from KAIST, is a technology-driven leader who has dedicated 26 years to the field of imaging solutions. He is recognized as a "field-oriented innovator" who has pioneered global niche markets with world-first technologies and driven long-term growth by prioritizing people and organizational culture as core competencies.
While working professionally, he enrolled in the KAIST Master’s program to strengthen his theoretical and practical expertise in optics. Later, he played a leading role in co-founding a venture company with fellow alumni, successfully growing Vieworks into a prominent global mid-sized enterprise.
In his inauguration remarks, President Kim stated, “I feel a profound sense of responsibility to give back to the nation and the community for the benefits I have received. I will do my best to ensure that the values of innovation and entrepreneurship are realized through our alumni network, and that the alumni association and our alma mater can prosper together.”
President Kim’s term will span two years starting from January 2026. The inauguration ceremony will be held during the "2026 New Year’s Greeting Ceremony" on January 16, 2026, at the El Tower in Seoul.
2025.12.23 View 1805 -
KAIST, AI judges manufacturing beyond craftsmanship and language barriers
<(From Left) M.S candidate Inhyo Lee, Ph.D candidate Heekyu Kim, Ph.D candidate joonyoung Kim, Professor Seunghwa Ryu>
Most of the plastic products we use are made through injection molding, a process in which molten plastic is injected into a mold to mass-produce identical items. However, even slight changes in conditions can lead to defects, so the process has long relied on the intuition of highly skilled workers. Now, KAIST researchers have proposed an AI-based solution that autonomously optimizes processes and transfers manufacturing knowledge, addressing concerns that expertise could be lost due to the retirement of skilled workers and the increase in foreign labor.
KAIST (President Kwang Hyung Lee) announced on the 22nd of December that a research team led by Professor Seunghwa Ryu from the Department of Mechanical Engineering · InnoCORE PRISM-AI Center has, for the first time in the world, developed generative AI technology that autonomously optimizes injection molding processes, along with an LLM-based knowledge transfer system that makes on-site expertise accessible to anyone. The team also reported that these achievements were published consecutively in an internationally renowned journal.
The first achievement is a generative AI–based process inference technology that automatically infers optimal process conditions based on environmental changes or quality requirements. Previously, whenever temperature, humidity, or desired quality levels changed, skilled workers had to rely on trial and error to readjust conditions.
The research team implemented a diffusion model–based approach that reverse-engineers process conditions satisfying target quality requirements, using environmental data and process parameters collected over several months from an actual injection molding factory.
In addition, the team built a surrogate model that substitutes for actual production, enabling quality prediction without running the real process. As a result, they achieved an error rate of just 1.63%, significantly lower than the 23~44% error rates of representative existing technologies such as GAN* and VAE** models traditionally used for process prediction. Experiments applying the AI-generated conditions to real processes confirmed successful production of acceptable products, demonstrating practical applicability.
*GAN (Generative Adversarial Network): a method in which two AI models compete with each other to generate data
**VAE (Variational Autoencoder): a method that compresses and learns common patterns in data and then reconstructs them
<Figure 1. Generative AI–Based Process Reasoning Technology>
The second achievement is the IM-Chat, an LLM-based knowledge transfer system designed to address skilled worker retirement and multilingual work environments. IM-Chat is a multi-agent AI system that combines large language models (LLMs) with retrieval-augmented generation (RAG), serving as an AI assistant for manufacturing sites by providing appropriate solutions to problems encountered by novice or foreign workers.
When a worker asks a question in natural language, the AI understands it and, if necessary, automatically calls the generative process inference AI, simultaneously providing optimal process condition calculations along with relevant standards and background explanations.
For example, when asked, “What is the appropriate injection pressure when the factory humidity is 43.5%?”, the AI calculates the optimal condition and presents the supporting manual references as well. With support for multilingual interfaces, foreign workers can receive the same level of decision-making support.
This research is regarded as a core manufacturing AI transformation (AX) technology that can be extended beyond injection molding to molds, presses, extrusion, 3D printing, batteries, bio-manufacturing, and other industries.
In particular, the work is significant in that it presents a paradigm for autonomous manufacturing AI, integrating generative AI and LLM agents through a Tool-Calling approach*, enabling AI to make its own judgments and invoke necessary functions.
*Tool-Calling approach: a method in which AI autonomously calls and uses the functions or programs required for a given situation
<Figure 2. Large Language Model–Based Multilingual Knowledge Transfer Multi-Agent IM-Chat>
<Figure 3. Example of Operation of the Large Language Model (LLM)–Based Multilingual Knowledge Transfer Multi-Agent IM-Chat>
<Figure 4. Illustration of the Application of an LLM-Based Multilingual Knowledge Transfer Multi-Agent IM-Chat (AI-Generated)>
Professor Seunghwa Ryu explained, “This is a case where we addressed fundamental problems in manufacturing in a data-driven way by combining AI that autonomously optimizes processes with LLMs that make on-site knowledge accessible to anyone,” adding, “We will continue expanding this approach to various manufacturing processes to accelerate intelligence and autonomy across the industry.”
This research involved doctoral candidates Junhyeong Lee, Joon-Young Kim, and Heekyu Kim from the Department of Mechanical Engineering as co–first authors, with Professor Seunghwa Ryu as the corresponding author. The results were published consecutively in the April and December issues of Journal of Manufacturing Systems (JCR 1/69, IF 14.2), the world’s top-ranked international journal in engineering and industrial fields.
※ Paper 1: “Development of an Injection Molding Production Condition Inference System Based on Diffusion Model,” DOI: https://doi.org/10.1016/j.jmsy.2025.01.008 ※ Paper 2: “IM-Chat: A multi-agent LLM framework integrating tool-calling and diffusion modeling for knowledge transfer in injection molding industry,” DOI: https://doi.org/10.1016/j.jmsy.2025.11.007
This research was supported by the Ministry of Science and ICT, the Ministry of SMEs and Startups, and the Ministry of Trade, Industry and Energy.
2025.12.22 View 2341 -
KAIST-UEL Team Develops Origami Airless Wheel to Explore Lunar Caves
<(From Upper Left) Ph.D candidate Seong-Bin Lee, CEO Namsuk Cho, Researcher Geonho Lee, Researcher Seungju Lee, M.S candidate Junseo Kim,
Principal Researcher Jong Tai Jang, Professor Se Kwon Kim, Professor Taewon Seo, Center Director Chae Kyung Sim, Professor Dae-Young Lee>
<(From Left) Principal Researcher Jong Tai Jang, CEO Namsuk Cho, Ph.D candidate Seong-Bin Lee, Professor Dae-Young Lee,Center Director Chae Kyung Sim>
New variable-diameter wheel overcomes steep terrain and harsh lunar conditions, paving the way for subsurface lunar exploration.
A joint research team from the Korea Advanced Institute of Science and Technology (KAIST) and the Unmanned Exploration Laboratory (UEL) has developed a transformative wheel capable of navigating the Moon’s most extreme terrains, including steep lunar pits and lava tubes.
The study presents a novel "origami-inspired" deployable airless wheel that can significantly expand its diameter to traverse obstacles that would trap traditional rovers. The research was published in the December issue of Science Robotics.
The Challenge: Small Rovers vs. Big Obstacles Lunar lava tubes and pits are prime candidates for future human habitats due to their natural shielding from cosmic radiation and extreme temperature fluctuations, but accessing them is perilous. Deploying a swarm of small, independent rovers can be an effective strategy to mitigate the risks associated with a single large rover. This strategy ensures mission continuity through redundancy; even if some units fail, the remaining rovers can complete the exploration.
However, small rovers face an inherent physical limitation: their compact wheel size severely restricts their ability to traverse steep, rugged terrains like lunar pit entrances. While variable-diameter wheels could theoretically solve this by offering high traversability on demand, creating such a system for the Moon has been a formidable challenge. Designing a lightweight transformable wheel that can withstand the harsh lunar environment—specifically the abrasive dust and the vacuum that causes metal parts to fuse ("cold welding")—has remained a significant engineering hurdle.
A Transformable Wheel for Extreme Environments To conquer these obstacles, a research team, led by Professor Dae-Young Lee from KAIST’s Department of Aerospace Engineering, developed a new type of compliant wheel that eliminates complex mechanical joints. By applying the structural principles of the “Da Vinci bridge” combined with origami design, the team created a wheel that uses the flexibility of its materials to transform.
Capable of expanding from a compact 230 mm to 500 mm in diameter, the wheel allows compact rovers to maintain a low profile during transport, yet scale significant obstacles once deployed. Crucially, by utilizing a specialized elastic metal frame and fabric tensioners instead of traditional hinges, the design ensures reliable operation in the harsh lunar environment, effectively resisting the risks of cold welding and mechanical failure caused by fine dust.
The team rigorously tested the wheel’s capabilities using artificial lunar soil (simulants). The wheel demonstrated superior traction on loose slopes and proved its structural integrity by withstanding a drop impact equivalent to a 100-meter fall in lunar gravity.
< Driving performance field tests conducted in various environments such as artificial lunar soil, extreme temperatures, mud, and rocky terrain >
Scientific and Engineering Significance The project brought together experts from major Korean space institutes to validate the technology's potential. Prof. Lee highlighted the wheel as a practical and reliable solution for navigating the Moon's most difficult terrains, expressing optimism that this unique technology would position the team as leaders in future lunar missions despite remaining challenges involving communication and power.
From a scientific perspective, Dr. Chae Kyung Sim, Head of the Planetary Science Group at KASI (Korea Astronomy and Space Science Institute), emphasized the value of lunar pits as "natural geological heritages," noting that this research significantly lowers the technical barriers to accessing these sites and brings actual exploration missions closer to reality. Furthermore, Dr. Jongtae Jang, Principal Researcher at KARI (Korea Aerospace Research Institute), underscored the engineering rigor behind the design, explaining that the wheel was meticulously optimized and validated using mathematical thermal models to endure the Moon’s extreme 300-degree temperature fluctuations.
About KAIST KAIST is the first and top science and technology university in Korea. KAIST has been the gateway to advanced science and technology, innovation, and entrepreneurship, and our graduates have been key ingredients behind Korea’s innovations.
About UEL(Unmanned Exploration Laboratory), inc. has cutting edge technology about planetary exploration mobility robotics in the Republic of Korea. UEL provides unmanned exploration systems from design and manufacturing the mobility platforms to perform the rover missions on Earth, the Moon, and beyond.
Journal Reference Science Robotics
DOI 10.1126/scirobotics.adx2549
2025.12.18 View 1897