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Professor Sihyun Kim Awarded 2026 Young Researcher Grant by the National Research Foundation of Korea ▲ Professor Sihyun Kim Professor Sihyun Kim from the Department of Electronic Engineering / System Semiconductor Engineering / Semiconductor Engineering at Sogang University has been selected for the 2026 Young Researcher Grant (Type B), a basic research project supported by the Ministry of Science and ICT and the National Research Foundation of Korea (NRF). The research project is titled "Mosaic Ferroelectric RAM (FeRAM) for Multi-Level Compute-in-Memory (CiM)," and will receive a total grant of 600 million KRW over a four-year period from March 2026 to February 2030. With the rapid advancement of generative AI technologies, the importance of Compute-in-Memory (CiM), a low-power and high-density computing architecture, is increasing. Existing CiM technologies based on SRAM and eDRAM face challenges such as low area efficiency and degraded energy efficiency. To overcome these limitations, Professor Sihyun Kim’s research team proposed a new multi-level CiM cell technology utilizing hafnia-based Ferroelectric RAM (FeRAM). The goal is to develop a high-efficiency CiM cell scheme that integrates multi-level weights into analog voltages through 3D stacking-based FeRAM structural innovation specialized for MAC operations, enabling parallel computation without data destruction. Through this research and development project, the team will conduct full-cycle research, ranging from material and unit process development to cell/array fabrication, and performance verification at the macro and system levels. By developing new device technology, the team aims to provide a breakthrough solution to the energy consumption, performance, and cost issues of memory for large-scale AI operations. Furthermore, by securing core technologies and preempting related fields, this research is expected to enhance national competitiveness in the hardware-based AI and memory semiconductor markets, where steady growth is anticipated in the future.
2026.03.17
Dr. Minsoo Kim of the Department of Electronic Engineering (Advisor: Professor Hongseok Kim) Appointed as Professor at Hanbat National University ▲ (From left) Assistant Professor Dr. Minsoo Kim, Professor Hongseok Kim Dr. Minsoo Kim, an alumnus of Sogang University’s Department of Electronic Engineering and a former doctoral student under Professor Hongseok Kim, was appointed as an Assistant Professor in the field of Energy AI in the Department of Electrical Engineering at Hanbat National University (March 1, 2026). After graduating from Sogang University in 2019, Dr. Kim conducted research on AI-based power grid optimization by combining deep learning and optimization theory, and received his Ph.D. in 2024. During the final stage of his doctoral program, he was awarded a National Research Foundation of Korea grant as principal investigator for a project on AI-based power grid optimization, which further led him to expand his research into electrical engineering as a postdoctoral researcher at the Korea Institute of Energy Technology. As a postdoctoral researcher, he carried out international collaborative research on Energy AI with MIT and the University of Michigan and published related papers. Since entering his Ph.D. program in 2019, Dr. Kim has published and presented 18 papers in SCIE journals and leading international conferences, including eight as first author. Professor Hongseok Kim commented that Dr. Kim’s appointment marks another proud achievement for NICE Lab and expressed his hope that more Sogang alumni will continue to grow into distinguished faculty members in the future.
2026.03.13
Jaegeun Lim, Integrated M.S.–Ph.D. (Advisor: Prof. Gilcho Ahn), Paper Accepted to JSSC 2025 ▲ (From left) Professor Gilcho Ahn, integrated M.S.–Ph.D. student Jaegeun Lim Jaegeun Lim, an integrated M.S.–Ph.D. student in the Mixed-Signal Circuit Design Lab (advisor: Gilcho Ahn) in our Department of Electronic Engineering, has had a paper accepted to the IEEE Journal of Solid-State Circuits (JSSC), the most prestigious international journal in analog circuit design (JCR Impact Factor 5.6, 2025). The IEEE Journal of Solid-State Circuits (JSSC) is a monthly journal that publishes across a broad range of semiconductor circuit topics with a particular emphasis on transistor-level integrated-circuit design. It also covers subjects directly related to IC design such as circuit modeling, technology, system design, layout, and test. The accepted paper, titled “A Hybrid Voltage-Time Domain Pipelined ADC With Reference-Embedded Time-Domain Residues,” proposes an 12-bit ADC that uses dual residues to inherently compensate time-domain reference variation without off-chip trimming or background calibration, thereby ensuring full-scale reference matching across the hybrid-domain stages.
2025.11.07
Selected for the “2025 Basic Research Laboratory (BRL) Program A joint research team consisting of Professor Hongseok Kim (Department of Electrical and Electronic Engineering, Sogang University), Professor Seongju Ryu (Department of System Semiconductor Engineering, Sogang University), Professor Youngmin Lee (Department of Artificial Intelligence, Sogang University), and Professor Byungkwon Park (Department of Electrical Engineering, Soongsil University) has been newly selected for the 2025 Basic Research Laboratory Support Program (Advanced Track) funded by the Ministry of Science and ICT and the National Research Foundation of Korea. The research project is titled “A National Power Grid Optimization Laboratory Based on Physics-Informed Neural Networks with Built-in Hardware Accelerators,” and will run for three years from June 1, 2025, to May 31, 2028. The total grant is 1.5 billion KRW (approximately 500 million KRW per year). Although the share of renewable energy in Korea is growing rapidly, the power grid remains highly vulnerable to unpredictable fluctuations. As solar and wind power installations increase, the need to balance supply and demand in real time becomes more critical. However, traditional methods struggle to handle large-scale problems and often require lengthy computation times, making them difficult to apply in actual operation. Consequently, grid stability deteriorates and the risk of frequent blackouts increases. To address these societal challenges, this research aims to develop “next-generation power grid optimization technology that combines AI with dedicated hardware chips.” First, AI-based learning models will be used to rapidly assess the grid’s state and propose optimal operational strategies in real time. Simultaneously, a dedicated hardware accelerator chip will be designed to perform complex calculations far more quickly. Through this approach, we will develop a power-grid foundation model capable of predicting and controlling power flows in real time at speeds tens of times faster than existing systems. Once commercialized, this technology is expected to dramatically reduce grid instability caused by the expansion of renewable energy and significantly lower national power operation costs. It will also prevent blackout incidents, thereby enhancing public safety and industrial productivity, and will contribute to achieving RE100 goals. In the long term, we plan to evolve this solution into a platform that can be used not only by power-sector companies but also by local governments and public institutions. Professor Hongseok Kim’s Networking for Intelligence Computing and Energy LAB conducts convergent research on AI computing and energy/power-system optimization. Focusing on physics-informed AI, the lab designs AI accelerator hardware and develops power-grid optimization algorithms that span both software and hardware. In particular, it has established its technical expertise by publishing papers continuously in top energy-related journals—such as IEEE Transactions on Power Systems (IEEE TPWRS), IEEE Transactions on Industrial Informatics (IEEE TII), Applied Energy, and Energies—on topics including AI-based power/grid optimization and energy trading.
2025.06.04
Professor Sung-Wan Hong Appointed as Korea Representative of the IEEE ISSCC Technical Program Committee Prof. Sung-Wan Hong from the Department of Electronic Engineering at Sogang University has been appointed as the Korea Representative of the Technical Program Committee (TPC) for the International Solid-State Circuits Conference (ISSCC), organized by the Institute of Electrical and Electronics Engineers (IEEE).Held annually in February in San Francisco, USA, ISSCC is widely recognized as the world’s most prestigious conference in the semiconductor field and is often referred to as the "Olympics of Semiconductors." Since its inception in 1954, the conference has served as a global platform where more than 4,000 semiconductor engineers gather to share cutting-edge research and discuss the future of the semiconductor industry.The selection of papers to be presented, as well as the planning of lectures and discussion sessions, is overseen by 13 Technical Program Committees (TPCs), each composed of distinguished researchers from academia and industry with proven achievements.Currently, there are a total of 24 active TPC members from Korea, including 8 from Samsung Electronics, 1 from SK hynix, 5 from KAIST, 3 from Seoul National University, and 1 each from Sogang University, DGIST, GIST, UNIST, Korea University, Hanyang University, and Kwangwoon University.Professor Hong began his role as a TPC member in 2024 and has now been appointed as the Korea Representative. In this capacity, he will preside over the Korean TPC meetings and press briefings, foster interactions with representatives from other countries, and contribute to the advancement of semiconductor technologies.
2025.04.07
Prof. Sua Bae Awarded 2025 Young Researcher Grant by the National Research Foundation of Korea Dr. Sua Bae from the Department of Electronic Engineering at Sogang University has been selected for the 2025 Young Researcher Grant, awarded by the National Research Foundation of Korea under the Ministry of Science and ICT. Her project, titled "Development of an At-Home Transcranial Focused Ultrasound System for Repetitive Brain Disease Treatment," will span three years, from March 2025 to February 2028, with total funding of 680 million KRW. As the population continues to age, the number of patients with chronic neurological disorders—such as Alzheimer’s disease and Parkinson’s disease—and those with malignant brain tumors is steadily increasing. These conditions require long-term, repetitive treatments, which can place a significant time and financial burden on patients, particularly those with limited mobility. Elderly individuals or residents of remote areas often face difficulties accessing regular medical care, making consistent treatment challenging. This research aims to introduce a new paradigm for brain disease treatment using focused ultrasound technology. By addressing the limitations of conventional MRI-guided focused ultrasound systems—which are often costly, time-intensive, and restricted to hospital settings—the project seeks to develop a patient-centered, at-home treatment device that significantly improves accessibility and efficiency. The team is targeting procedures that require frequent intervention, such as blood-brain barrier opening and enhancement of cerebrospinal fluid circulation, and is working on real-time monitoring technologies that account for individual skull acoustics and patient-specific physiological responses. Key objectives include the development of sensing and monitoring systems capable of detecting brain responses in real time, as well as adaptive control algorithms that automatically configure safe and consistent treatment conditions. The project also aims to build a compact treatment platform suitable for use outside of clinical environments, along with an intuitive user interface that patients and caregivers can easily operate. This multidisciplinary research combines expertise in medical devices, neuroscience, and artificial intelligence. The at-home treatment approach is expected to enhance patients‘ quality of life, improve treatment adherence, and reduce overall healthcare costs.
2025.03.27
Young Investigator Interview at Focused Ultrasound Foundation The Focused Ultrasound Foundation, a leading organization in the field of medical focused ultrasound, actively supports research and technological advancements worldwide. Recently, the foundation featured Dr. Sua Bae from the Department of Electronic Engineering at Sogang University as a "Young Investigator," highlighting her research accomplishments and contributions to the field. Dr. Bae's research centers on focused ultrasound (FUS) technology for blood-brain barrier (BBB) opening, exploring its potential in treating neurological diseases. She played a key role in an Alzheimer’s disease clinical trial, developing a real-time ultrasound-based monitoring technique to enhance treatment precision. Additionally, she contributed to multi-session focused ultrasound treatment studies for pediatric brain tumors, refining treatment monitoring methods. In 2024, Dr. Bae joined the Department of Electronic Engineering, becoming the first female faculty member in Sogang University's School of Engineering. Beyond her research, she is deeply committed to education and mentorship, striving to inspire and support female students pursuing careers in engineering. Newsletter Link: https://www.fusfoundation.org/posts/young-investigator-profile-sua-bae-phd/
2025.03.19
Professor Kang Suk-ju’s Research Team Publishes Paper in Prestigious International Journal IEEETransactions on Instrumentation and Measurement ▲ (From left) Professor Kang Suk-Ju, master’s students Hwang Ye-eun and Song Min-seo from the Department of Electronic Engineering Professor Kang Suk-ju’s research team from the Department of Electronic Engineering (including master’s students Hwang Ye-eun and Song Min-seo) has published a paper in the prestigious international journal IEEE Transactions on Instrumentation and Measurement (TIM) after conducting joint research with the CSE team at the Semiconductor Research Institute of Samsung Electronics. In the paper, titled “SO-Diffusion: Diffusion-based Depth Estimation from SEM Images and OCD Spectra,” the research team introduces a new model for predicting semiconductor structures using semiconductor images captured by a scanning electron microscope (SEM) and optical critical dimension (OCD) spectra. Notably, the team developed a CNN-based spectrum encoder (SEFO) to effectively preprocess the OCD spectra and applied it to a diffusion-based network with SEM images, improving the accuracy of semiconductor structure prediction. As a result, the proposed model using SEM images and OCD spectra significantly outperformed existing models in predicting semiconductor depth. Hwang Ye-eun, a master’s student who participated in the research, said, “It is a great honor to have my paper published in IEEE TIM during my master’s course.” She added, “Thanks to the support from Samsung Electronics’ CSE team and the guidance of my professor, we were able to achieve excellent results. As semiconductor research is advancing rapidly, I hope this study serves as a foundation for various follow-up studies.” The proposed algorithm was developed in response to the industry’s recent trend of increasing miniaturization and complexity of semiconductor structures. By providing more precise measurement data when analyzing SEM semiconductor images, this research is expected to contribute to the effective reconstruction of 3D semiconductor structures. ▲ Overall structure of the SO-Diffusion network proposed in the paper ▶ Paper Title: SO-Diffusion: Diffusion-based Depth Estimation from SEM Images and OCD Spectra▶ Journal: IEEE Transactions on Instrumentation and Measurement▶ Authors: Hwang Ye-eun (First author, Sogang University), Song Min-seo (Sogang University), Ma Ah-mi (Samsung Electronics CSE), Kim Gyu-hwan (Samsung Electronics CSE), Jang Gyu-baek (Samsung Electronics CSE), Jung Jae-hoon (Samsung Electronics CSE), and Kang Suk-ju (Corresponding author, Sogang University)
2025.03.19
A paper from AIRLAB accepted to IEEE ICRA’25 From left, Gi Don Han, Jeongwoo Park, and Advisor Prof. Changjoo Nam A research paper from AI Robotics Lab (directed by Prof. Changjoo Nam) from the Department of Electronic Engineering has been accepted to the International Conference on Robotics and Automation (ICRA 2025), one of the top conferences in robotics and automation. Organized by IEEE, ICRA is the most prestigious international conference in the robotics field and is scheduled to take place from May 19 to 23 at the Georgia World Congress Center in the United States. The research was led by Ki Don Han, a master's graduate (currently at Samsung Electronics), with contributions from Jeongwoo Park, a Ph.D. candidate. The paper, titled "Stop-N-Go: Search-based Conflict Resolution for Motion Planning of Multiple Robotic Manipulators," presents a novel approach to motion planning in environments with multiple robotic manipulators. In industrial settings such as factories and warehouses, multiple robotic manipulators often work together on processes such as assembly, welding, painting, and packaging. However, as these robots move simultaneously, they risk colliding with each other. One common approach to solving this problem is to plan all robots' movements in a unified configuration space. While this method considers all robots' movements together, it becomes computationally intractable as the number of robots increases, often failing to find feasible solutions. On the other hand, decoupled planning, where each robot's path is planned independently, is computationally efficient but frequently leads to trajectory conflicts. The search algorithm for conflict resolution and the environments for experiments To address this issue, Professor Nam's team proposed a new method that inserts pauses into individually planned trajectories to resolve conflicts. Using the A* algorithm, their approach minimizes the number of stops while reducing the total task completion time. By allowing some robots to stop temporarily, others can move without collisions, ensuring smooth and efficient motion planning. This technique is expected to significantly enhance the efficiency of multi-robot systems operating in shared spaces. Moreover, its applications extend beyond industrial settings to logistics, healthcare, and service robotics, where collaborative robots are increasingly in demand.
2025.02.03
전영준 석박통합과정(지도교수 홍성완), 반도체 설계 올림픽 ‘ISSCC 2025’ 논문 채택 ▲(왼쪽부터) 전영준 석박통합과정, 홍성완 전자공학과 교수 전자공학과 전영준 석박사통합과정(지도교수 홍성완)이 세계 최고 권위의 반도체 학회 ‘국제고체회로학회(International Solid-State Circuits Conference, 이하 ISSCC) 2025’에서 논문이 채택되었다. ISSCC는 1954년 처음 개최된 회로 분야 최고 국제학술대회로, 반도체 회로 분야 학회 중 가장 높은 권위와 큰 규모를 자랑하며 이른바 ‘반도체 설계 올림픽’으로 불린다. 해당 논문의 제목은 “A Sub-1V, 50mV Dropout LDO using Pseudo-Impedance Buffer with Phase-Margin Improvement Design”이다. 전영준 석박사통합과정생은 반도체 공정 기술의 발전에 맞춰 낮은 입력 전압 조건에서 동작하는 Analog Low Dropout Regulator(ALDO)를 설계하였다. 본 논문은 Rail-to-Rail Pseudo Impedance(RRPB) 구조를 제시하여, 1V 이하의 입력 전압에서 최대 300mA 로드 전류를 제공하면서도 50mV의 낮은 dropout voltage를 갖는 높은 효율을 갖는 LDO를 설계하였다. 이번 연구 성과는 기존 낮은 입력 전압에서 동작하는 Digital Low Dropout Regulator(DLDO)의 스위칭 노이즈 문제를 해결한 구조로, 고정밀 저잡음 전원이 필요한 시스템에서 효과적으로 적용될 수 있을 것으로 기대된다.
2024.10.16