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School of Electrical Engineering We thrive
to be the world’s
top IT powerhouse.
We thrive to be the world’s top IT powerhouse.

Our mission is to lead innovations
in information technology, create lasting impact,
and educate next-generation leaders of the world.

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School of Electrical Engineering We thrive
to be the world’s
top IT powerhouse.
We thrive to be the world’s top IT powerhouse.

Our mission is to lead innovations
in information technology, create lasting impact,
and educate next-generation leaders of the world.

  • 2
  • 6
Learn More
School of Electrical Engineering We thrive
to be the world’s
top IT powerhouse.
We thrive to be the world’s top IT powerhouse.

Our mission is to lead innovations
in information technology, create lasting impact,
and educate next-generation leaders of the world.

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  • 6
Learn More
School of Electrical Engineering We thrive
to be the world’s
top IT powerhouse.
We thrive to be the world’s top IT powerhouse.

Our mission is to lead innovations
in information technology, create lasting impact,
and educate next-generation leaders of the world.

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  • 6
Learn More
School of Electrical Engineering We thrive
to be the world’s
top IT powerhouse.
We thrive to be the world’s top IT powerhouse.

Our mission is to lead innovations
in information technology, create lasting impact,
and educate next-generation leaders of the world.

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Learn More
AI in EE AI and machine learning
are a key thrust
in EE research
AI and machine learning are a key thrust in EE research

AI/machine learning  efforts are already   a big part of   ongoing
research in all 6 divisions - Computer, Communication, Signal,
Wave, Circuit and Device - of KAIST EE 

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Prof. Minsoo Rhu’s team
develops a simulation
framework called vTrain
Read more...
Prof. Jun-Bo Yoon’s Team
Achieves Human-Level Tactile Sensing with
Breakthrough Pressure Sensor
Read more...
Prof.
Seungwon Shin’s Team
Validates Cyber Risks
of LLMs
Read more...
Prof. Seunghyup Yoo’s team Develops
Wearable Carbon Dioxide Sensor
to Enable Real-time Apnea Diagnosis​
Read more...
Prof. Choi and Yoon’s
Joint Team Develops
Neuromorphic Semiconductor Chip
that Learns and Corrects Itself​
Read more...
Prof. Jung-Yong Lee’s Team
Develops High-Efficiency
Avalanche Quantum Dots
Read more...
Prof. Junmo Kim’s Team
Develop AI That
Imagines and Understands
How Images Change Like Humans
Read more...
Prof. Hyunjoo J. Lees Team Develops Stretchable
Microelectrodes Array
for Organoid Signal Monitoring
Read more...
Prof. Sanghun Jeon's Team Develops
Hafnia-Based Ferroelectric Memory Technology
Read more...
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Highlights

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<(From left) Daebeom Kim (Ph.D. candidate, team leader), Seungjae Lee (Ph.D. candidate), Seoyeon Jang (Ph.D. candidate), Jei Kong (M.S. candidate), Professor Hyun Myung>
The Urban Robotics Lab, led by Professor Hyun Myung from the School of Electrical Engineering, secured the first place overall at the “Nothing Stands Still (NSS) Challenge 2025,”held in the “Future of Construction: Safe, Reliable, and Precise Robots in Construction Environments” workshop at the 2025 IEEE International Conference on Robotics and Automation (ICRA), the world’s premier robotics conference, which took place in Atlanta, USA, from May 19 to 23, 2025.
 
NSS Challenge is co-hosted by HILTI, a global construction company based in Liechtenstein, and Gradient Spaces Group at Stanford University. It is an advanced version of HILTI SLAM (Simultaneous Localization and Mapping) Challenge, which has been held since 2021, and is now considered one of the most prestigious challenges at ICRA.
 
 
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<A scene from the oral presentation on the winning team’s technology (presenters: Seungjae Lee and Seoyeon Jang, Ph.D. candidates)>

 

This challenge evaluates how accurately and robustly LiDAR scan data, collected across various time periods in structurally dynamic environments such as construction and industrial sites, can be registered. Rather than focusing solely on single-instance registration accuracy, it emphasizes multi-session localization and mapping (Multi-session SLAM) technologies capable of handling structural changes over time, making it one of the most technically demanding competitions in the field.
 
Urban Robotics Lab team secured the first place overall by a significant margin over National Taiwan University (3rd place) and Northwestern Polytechnical University of China (2nd place), with their novel localization and mapping technology that solves the alignment problem of LiDAR data collected across diverse periods and locations. The winning team will be awarded a prize of $4,000.
 
 
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<Fig. 1. Example of multiway registration of LiDAR scans from different time periods>

 

Urban Robotics Lab team developed a multiway registration framework capable of robustly aligning multiple scans without prior connectivity information. This framework consists of three core components: CubicFeat, an algorithm that summarizes local features within each scan and identifies correspondences; Quatro, a global registration algorithm that aligns scans based on those correspondences; and Chamelion, a refinement module based on change detection. This combination of techniques shows stable alignment performance even in highly dynamic industrial environments by focusing on static structural elements.

 

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<Fig. 2. Example of change detection using the Chamelion algorithm>

 

LiDAR scan registration technology is a core component of SLAM used in various autonomous systems, including self-driving cars, autonomous robots, legged platforms, aerial vehicles, and maritime navigation systems. In particular, the awarded technology has demonstrated exceptional precision in estimating the relative poses between scans in complex environments, proving both its academic significance and practical applicability in industry.
 
Professor Hyun Myung of the School of Electrical Engineering at KAIST stated, “It is deeply meaningful to have demonstrated our technological capabilities by solving multi-session SLAM challenges in complex and constantly changing industrial environments.” He added, “I am grateful to the students who persevered and never gave up, even when many other teams withdrew due to the difficulty of the competition.”
 
 
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<Competition leaderboard; lower RMSE (Root Mean Square Error) indicates a higher score. (Unit: meters)>

 

The Urban Robotics Lab team first participated in the SLAM Challenge in 2022, winning 2nd place in the academic division, and in 2023, they took 1st place overall in the LiDAR division and 1st place in the academic division of the vision track.

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<Ph.D. candidate Hyejeong Yeon>

Hyejeong Yeon, a Ph.D. candidate in the School of Electrical and Electronic Engineering at KAIST under the supervision of Professor Kyung Cheol Choi, received the Distinguished Student Paper Award at SID 2025 (Society for Information Display 2025 International Symposium – Display Week 2025) held from May 11 to 16.

 

SID is the most prestigious international symposium in the field of display technology. In 2025, a total of 925 papers from 20 countries were submitted, and outstanding papers were selected by each technical committee.

 

The paper by Hyejeong Yeon, a Ph.D. candidate, was recognized by the Flexible Displays Committee for its excellence, and was selected as a Distinguished Student Paper, and the title of the awarded paper is: “Flexible Bifacial OLED-Based Photomedicine for User-Friendly Healthcare Platforms.”

 

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<Distinguished Student Paper Award(Left), Young Leadership Conference Participation Certificate(Right)>

 

The research was published in the Journal of the SID under the title : “Wearable User-Centric Phototherapeutics with Bifacial OLEDs for At-Home Wound Healing.” Furthermore, Yeon was selected to present her work at the Young Leadership Conference, a special session for promising young researchers, where her study was chosen as one of the top 10 outstanding papers of the year.

 

  • Conference: SID 2025 (Society for Information Display 2025 International Symposium – Display Week 2025)
  • Date: May 11–16, 2025
  • Award: Distinguished Student Paper Award
  • Paper Title: Flexible Bifacial OLED-Based Photomedicine for User-Friendly Healthcare Platforms
  • Paper Link: https://doi.org/10.1002/jsid.2076
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교수님 900
〈(from left) Ph.D. candidate Jiwan Kim, Professor Ian Oakley and Ph.D. candidate Mingyu Han 〉
When will the futuristic vision of natural gesture-based interaction with computers, as seen in sci-fi films like Iron Man, become a reality? Researchers from the KAIST School of Electrical Engineering have developed AI technologies that enable natural and expressive input for wearable devices.
 
Professor Ian Oakley’s research team at KAIST’s School of Electrical Engineering has developed two systems: BudsID, a finger-identification system for wireless earbuds, and SonarSelect, which enables mid-air gesture input on commercial smartwatches. These two studies were presented at the ACM Conference on Human Factors in Computing Systems (CHI)—the world’s premier conference in the field of human-computer interaction—held in Yokohama, Japan from April 26 to May 1. The presentations were part of the “Earables and Hearable” and “Interaction Techniques” sessions, respectively.

 

BudsID uses magnetic sensing to distinguish between fingers based on magnetic field changes that occur when a user wearing a magnetic ring touches an earbud. A lightweight deep learning model identifies which finger is used, allowing different functions to be assigned to each finger, thus expanding the input expressiveness of wireless earbuds.

 

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<Figure 1: Overall system architecture of BudsID: A user wears a magnetic ring, and magnetic field variations upon earbud touch are detected via deep learning to identify the finger and assign different functions accordingly, enhancing interaction expressiveness.>

 

This magnetic sensing system for wireless earbuds allows users to go beyond traditional interactions like play, pause, or call handling. By mapping different functions or input commands to individual fingers, the interaction capabilities can extend to augmented reality device control and beyond.

 

SonarSelect leverages active sonar sensing using only the built-in microphone, speaker, and motion sensors of a commercial smartwatch. It recognizes mid-air gestures around the device, enabling precise pointer manipulation and target selection.

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<Figure 2: Three target selection methods using SonarSelect’s around-device movement sensing on commercial smartwatches: A) Double-Crossing, B) Dwelling, C) Pinching.>

 

This gesture interaction technology, based on finger movements detected via active sonar, addresses usability issues of small smartwatch screens and touch occlusion. It enables delicate 3D spatial interactions around the device.

 

Jiwan Kim, first author of both papers, said, “We hope our research into around-device sensing for wearable interaction technologies will help shape the future of how people interact with wearable computing devices.”

 

Professor Ian Oakley’s research team has made both project systems available as open source, allowing researchers and industry professionals to freely use the technology.

 

[BudsID]

[SonarSelect]

 

This research was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (grants 2023R1A2C1004046, RS-2024-00407732) and the Institute for Information & Communications Technology Planning & Evaluation (IITP) under the University ICT Research Center (ITRC) support program (IITP-2024-RS-2024-00436398).

 
교수님 홍보 이미지영

교수님 홍보 이미지영

EE Professor Sanghyeon Kim’s lab has been selected for one of five new ICT projects for the first half of this year by the Samsung Research Funding & Incubation Center for Future Technology.

 

The Samsung Research Funding & Incubation Center for Future Technology is a funding initiative that supports innovative research projects across a wide range of fields, from natural sciences to engineering, with the aim of advancing science, technology, and industry in Korea.

 

Professor Kim’s lab will carry out a project titled “Low-Loss Active Power Delivery Network with Embedded On-Chip Voltage Regulator for Ultra-Low Power Computing” The research team plans to explore a solution to the power delivery problem, which has recently emerged as a key issue in the fields of semiconductor chips and packaging. Specifically, they will investigate a method of delivering power at high voltage and stepping it down on the backside of the chip.

 

The goal is to implement an on-chip voltage regulator using GaN-based switches, which have excellent material potential, and ferroelectric capacitors. Ultimately, the core idea is to integrate this system as an active component of the backside power delivery network (BSPDN).

 

Meanwhile, the foundational concept of this project was presented by the research team at IEDM — one of the three major conferences in the semiconductor field—in December last year, and improved technologies will be presented at the upcoming VLSI Symposium in June.

교수님 360 2
교수님 사업수주
< Figure 1. (From left) Professor Myoungsoo Jung, Professor John Kim, Professor Song Min Kim, Professor Minsoo Rhu >
Professors Myoungsoo Jung, John Kim, Song Min Kim, Minsoo Rhu, have recently been awarded 40 billion KRW in national R&D funding by the Ministry of Science and ICT and the Institute of Information & Communications Technology Planning & Evaluation (IITP), as part of the ‘K-Cloud Project’ initiative.
 
The K-Cloud Project aims to strengthen the domestic cloud industry’s competitiveness by securing world-class low-power, high-performance data center hardware and software core technologies. Under the leadership of Professor Jung, our research team has been selected for the K-Cloud Project that focuses on developing computational memory hardware based on AI infrastructure, AI integration, Compute Express Link (CXL), and chiplet technologies. The research team will receive over 40 billion KRW in research funding over the next four years.
 
The K-Cloud Project is a national initiative designed to enhance the country’s competitiveness in cloud computing industry, developing hardware and software technologies which are necessary for building datacenters with ultra-high speed and low-power. As part of this K-Cloud Project, the research team, which is led by Prof. Myoungsoo Jung, have been selected to lead programs focused on AI infrastructure, AI integration, Compute Express Link (CXL), and silicon hardware of computational memory based on chiplet technologies, securing 40B KRW in research funding over the next four years.
 
Specifically, the team will develop a low-power, high-performance SoC for computational memory, which minimizes data movement by performing AI-related computations close to where data is stored. In addition, the team will develop technologies to construct integrated AI systems by interconnecting these devices using CXL, a high-speed interconnect protocol. Finally, the team will apply optimization software based on AI algorithm to complete an AI infrastructure platform and validate its performance using real-world workloads such as large language models (LLMs), retrieval-augmented generation (RAG), and recommendation systems.
 
 
교수님 그림 2
< SoC Architecture >

 

This project, including the development of these core technologies, is led by Panmnesia—a faculty startup founded by Professor Myoungsoo Jung—and involves participation from other KAIST research groups from our department. This includes research teams of Professors John Kim, Minsoo Rhu, and Song Min Kim. In addition, a university-industry consortium comprising Seoul National University, Yonsei University, Korea University, Hanyang University, Chung-Ang University, POSTECH, and UNIST, the Korea Electronics Technology Institute (KETI), and four industry partners is collaborating on the project. External institutions, such as Chung-Ang University Hospital, will also collaborate for real-world validation and demonstration.
 
Through this effort, we expect that the collaboration between faculty startups and research laboratories originating from our department will produce impactful research outcomes that contribute to both academia and industry.
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< (From left) Professor Chris Donahue of Carnegie Mellon University, Ph.D. candidate Yewon Kim of the School of Electrical Engineering at KAIST, and Professor Sung-Ju Lee of the School of Electrical Engineering at KAIST >

 

Imagine if music creators had a collaborator who could help brainstorm initial ideas or assist when they hit a creative block or someone who could genuinely support exploring various musical directions. A research team at KAIST’s School of Electrical Engineering has developed an AI tool designed to be such a co-creative partner in music composition.

 

Professor Sung-Ju Lee’s research team at the School of Electrical Engineering has developed an AI-based music creation support system named Amuse. This research was awarded the Best Paper Award, an honor given to only the top 1% of papers, at CHI (ACM Conference on Human Factors in Computing Systems), the world’s leading conference in human-computer interaction, held in Yokohama, Japan from April 26 to May 1.

 

Amuse is an AI-based system that supports songwriting by transforming diverse forms of inspiration, such as text, images, or audio, into harmonic structures (chord progressions). For example, when a user inputs a phrase like “memories of a warm summer beach,” an image, or a sound clip, Amuse generates and suggests a chord progression that matches the mood and atmosphere of the inspiration.

 

Unlike conventional generative AI, Amuse respects the user’s creative process and offers a flexible, interactive approach that allows users to modify and integrate the AI’s suggestions, encouraging natural and creative exploration.

 

The core technology of the Amuse system is a hybrid generation method. It first uses a large language model to generate music chords based on the user’s textual input. Then, a second AI model trained on actual music data filters out unnatural or awkward results through a process called rejection sampling. These two processes are seamlessly integrated to produce musically coherent outcomes.

 

피겨1
< (Figure 1) System structure of Amuse. Music-related keywords are extracted from user input, and a chord progression is generated using a large language model and refined via rejection sampling (left). Chords can also be extracted from audio inputs (right). The bottom visualizes the harmonic structure of the generated chords. >

 

The research team conducted user studies with actual musicians, and the findings suggest that Amuse has strong potential not just as a music-generating tool but as a co-creative partner that enables collaboration between humans and AI.

 

The study, authored by Ph.D. candidate Yewon Kim(KAIST), Professor Sung-Ju Lee(KAIST), and Professor Chris Donahue (Carnegie Mellon University), demonstrates the creative potential of AI systems for both academia and industry.

<Demo Video>
 

Professor Sung-Ju Lee stated, “Recent generative AI technologies have raised concerns due to the risk of replicating copyrighted content or producing results that ignore the creator’s intent. Our team was aware of these issues and focused on what creators actually need, prioritizing user-centric design in developing this AI system.”

 

He added, “Amuse is an attempt to explore collaborative possibilities with AI while maintaining the creator’s agency. We expect it to be a starting point that guides future development of AI-powered music tools toward a more creator-friendly direction.”

 

This research was supported by the National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT. (Project No. RS-2024-00337007)

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〈 (From left) President Kwang Hyung Lee and Professor Shinhyun Choi, recipient of the Hyeon-Woo KAIST Scholastic Award 〉

Professor Shinhyun Choi of the School of Electrical Engineering has been selected as the recipient of the Hyeon-Woo KAIST Scholastic Award, hosted by KAIST and sponsored by the Hyeon-Woo Cultural Foundation (Chairman Soo-Il Kwak), in recognition of his achievements in next-generation AI hardware development and innovative semiconductor research.

 

Professor Choi’s primary research areas focus on the development of future memory and computing devices, including: ▲ Next-generation memory and computing systems using resistive switching devices that are faster and more efficient than conventional methods ▲ Integration with edge computing and neuromorphic computing to enable intelligent computer memory functions ▲Development of more efficient and creative computing and memory device operations, different from the traditional three-terminal transistor structure.

 

One of his representative achievements is the successful development of an ultra-low-power next-generation phase-change memory (PCM) device optimized for vertical stacking, which reduces electricity consumption by more than 15 times compared to the conventional method that relies on expensive advanced photolithography* processes.  * Photolithography: A process that engraves microscopic circuit patterns on silicon wafers for semiconductor chips, which involves advanced technology and high costs.

 

Furthermore, based on next-generation memory and computing devices, Professor Choi developed new computing hardware (chips) capable of efficiently running AI algorithms, potentially replacing power-hungry chips such as CPUs and GPUs. This achievement enables faster and more efficient data processing and has led to significant accomplishments in practical applications such as smartphones and autonomous driving.

 

In addition, by analyzing the operating principles of memory devices down to the atomic level based on fundamental physical laws, he has made major contributions in proposing methods to improve memory performance with greater speed and stability.

 

Professor Choi’s research spans the entire spectrum of semiconductor technology—from material analysis and device development to integrated system applications. His outstanding achievements have been published in top-tier journals such as Nature, Nature Electronics, Nature Communications, and Science Advances.

 

Professor Choi stated, “It is an honor to receive this meaningful award for my research in IT and AI-related hardware, which are driving major societal changes. I am deeply moved that this research can provide new perspectives to both academia and industry. I will continue to strive to produce research that inspires future scholars and contributes to society.”

 

Meanwhile, now in its fifth year, the Hyeon-Woo KAIST Scholastic Award was established with donations from Chairman Soo-Il Kwak of the Hyeon-Woo Cultural Foundation to recognize scholars at KAIST who have made outstanding academic achievements. One faculty member is selected each year through a rigorous evaluation by the Hyeon-Woo Foundation Selection Committee and the KAIST Faculty Award Recommendation Committee. The award includes a plaque and a prize of 10 million KRW. This year’s award ceremony was held on April 30 at Jeong Geun-Mo Hall in the KAIST Academic Cultural Complex.

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1. 배현민 교수 수상사진1
〈 (From left) President Kwang Hyung Lee and Professor Hyeonmin Bae, recipient of the Research Grand Prize 〉

 

Professor Hyeonmin Bae from the School of Electrical Engineering was awarded the Grand research prize at the ‘KAIST Research Day 2025’ event held at the Jeong Geun Mo Conference Hall in the Academic Cultural Complex on April 30th. 

 

Professor Bae was recognized for his outstanding achievements in “Research and Development of Quantitative Medical Imaging Ultrasound Equipment Using Artificial Intelligence,” and shared his decade-long research journey in a commemorative lecture at the event.

 

By integrating artificial intelligence with ultrasound technology, Professor Bae successfully commercialized quantitative ultrasound techniques, previously unattainable. The technological prowess of this innovation was demonstrated through a live demo at the Radiological Society of North America (RSNA) held in Chicago in 2024. This advanced technology can be implemented as software in existing ultrasound equipment, enabling not only early cancer detection but also the diagnosis of critical diseases in major organs such as the lungs, liver, and heart.

 

Professor Bae expressed his aspirations for the technology: “I hope quantitative ultrasound technology can facilitate more accurate and swift diagnoses, significantly benefiting diverse medical fields. I am committed to continuing my research to enhance global healthcare welfare.”

 

3. 리서치데이 수상자 사진1 e1746340998947
〈 Group Photo of 2025 KAIST Research Day Awardees 〉

 

Meanwhile, at this year’s Research Day, Professors Kyeongha Kwon (A Wireless, Implantable Bioelectronic System for Monitoring Urinary Bladder Function Following Surgical Recovery) and Minsoo Rhu (uPIMulator: Pathfinding Future PIM Architectures by Demystifying a Commercial PIM Technology) were selected for ‘KAIST’s Top 10 Research Achievements of 2024.’

 

Additionally, professors Junil Choi (Next-generation Visible Light Communication Encryption Technology Using Chiral Nanoparticles / Next-generation Communication) and Kyoungsik Yu (Silicon Photonic Integrated Circuits for Quantum Information Processing) were recognized in the ‘Research achievements in 14 leading technologies of the future 2025’

 

President Kwang Hyung Lee highlighted, ” KAIST aims to become the world’s first and foremost in research, celebrating today at Research Day the outstanding accomplishments of our researchers, and will continue growing as a global research institution that contributes to the nation and humanity through research, leading innovation and convergence”

 

KAIST Research Day, established in 2016, serves as an annual platform showcasing KAIST’s research and development (R&D) achievements and fostering active interaction among researchers to promote interdisciplinary collaboration.

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