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Seongbo Park, Integrated M.S.-Ph.D. (Advisor: Prof. Gilcho Ahn), Paper Accepted to TCAS-I 2026 ▲ (From left) Professor Gilcho Ahn, Integrated M.S.-Ph.D. Minsoo Kim Park Sung-Bo, an integrated M.S./Ph.D. student in the Mixed-Signal Circuit Design Laboratory, Department of Electronic Engineering, under the supervision of Prof. Kil-Choo Ahn, has had a paper accepted for publication in IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I), a prestigious international journal in the field of analog circuit design. IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I) is an international journal covering the theory, design, and implementation of analog, digital, and mixed-signal circuits and systems. It publishes research results in a broad range of areas, including integrated circuit design, data converters, sensor interfaces, signal-processing circuits, and various circuit- and system-level applications. The paper, entitled “A ±50-A Shunt-Based Current Sensor With ±0.2% Gain Error From −40 °C to 125 °C,” proposes a temperature-compensation technique based on PTAT (Proportional-to-Absolute-Temperature) and tunable CTAT (Complementary-to- Absolute-Temperature) characteristics to compensate for the temperature-dependent resistance variation of a PCB-trace shunt resistor. The proposed current sensor operates without complex individual temperature calibration by using a single batch calibration together with a one-point gain trim at room temperature. It achieves a gain error within ±0.2% over a temperature range of −40 °C to 125 °C and a current range of ±50 A. In addition, a low-power ΔΣ ADC directly digitizes the shunt voltage, enabling the implementation of an integrated current-sensing system for accurate current measurement.
2026.09.11
Sogang University Selected to Develop Core AI Technologies for Korea's Next-Generation Power System Operations ▲ Professor Hongseok Kim Sogang University Professor Hongseok Kim's research team has joined a five-year, KRW 29.5 billion (government-funded) national AI-EMS project (2026–2030) to develop next-generation AI technologies for Korea's power grid.Led by the Korea Power Exchange (KPX), the project aims to transform the national Energy Management System (EMS) using AI for more secure, efficient, and reliable grid operation.Professor Kim's team is responsible for two of the project's core technologies: AI-based AC Optimal Power Flow (AI AC-OPF)and AI-based Unit Commitment (AI UC), which serve as the computational engine of modern power system operations. By integrating physics-based AIwith advanced optimization, the team seeks to achieve real-time, trustworthy decision-making while significantly accelerating computation.Despite not having a traditional electrical engineering department, Sogang University is playing a leading role in one of Korea's most strategic national AI infrastructure projects, demonstrating its strengths in AI, optimization, GPU computing, and physics-informed machine learning. The research is expected to contribute not only to Korea's AI-driven energy transition but also to the future of intelligent power grid technologies worldwide.
2026.07.23
Battery Usage-Agnostic Multi-Task Diagnostics Using Contrastive Learning and Knowledge-guided Voltage Relaxation ▲ (From left) Jihun Jeon, Hojin Cheon, Minsu Kim, Hyungseok Seo, and Prof. Hongseok Kim A research team from the Department of Electronic Engineering at Sogang University, including Jihun Jeon, Hojin Cheon, Hyungseok Seo, and Prof. Hongseok Kim, has published their paper in the prestigious energy journal Journal of Energy Storage (JCR IF 9.8, 2026). The study proposes a usage-agnostic battery diagnostic framework that leverages voltage relaxation signals to simultaneously estimate capacity, state of health (SOH), and cathode materials through a multi-task learning approach.By incorporating a knowledge-guided equivalent circuit model (KG-ECM) and supervised contrastive learning, the framework learns a shared and discriminative representation for multiple diagnostic tasks. Experimental results demonstrate significant improvements over conventional methods, achieving an RMSE of 0.0026 (single-task) and 0.0108 (multi-task), along with 94.6% SOH classification accuracy and 99.6% cathode identification accuracy. This work highlights the potential of integrating multi-task learning and contrastive learning for reliable and practical battery diagnostics in real-world EV and ESS applications.
2026.03.31
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