Image: Professors and awardees Top row (from left): Professor Jae-Joon Kim, Professor Taesup Moon Bottom row (from left): Ph.D. Candidate Hyeseong Jeon, Ph.D. Candidate Dohoon Kim Dohoon Kim, a Ph.D. candidate in the Mechanical Intelligence and Data Science Lab (advised by Professor Taesup Moon), and Hyeseong Jeon, a Ph.D. candidate in the Very-Large-Scale Integration (VLSI) Lab (advised by Professor Jae-Joon Kim), both in the Department of Electrical and Computer Engineering at Seoul National University, were selected as final Winners of the Qualcomm Innovation Fellowship Korea (QIFK) 2025. The results were announced at the final event held on November 27. QIFK is a scholarship and research support program organized by Qualcomm for graduate students in Korea, designed to identify and support outstanding research in the field of AI through research funding and fellowships. More than 120 research submissions were received for this year’s program, from which 15 were ultimately selected as Winners. Hyeseong Jeon proposed a fine-tuning methodology for quantized models aimed at enabling efficient inference in task-specific large language models (LLMs). Departing from the conventional “quantization-then-fine-tuning” paradigm, the proposed approach performs quantization concurrently with fine-tuning. This method was shown to maintain high model accuracy while significantly improving inference speed. Image: Overview of Hyeseong Jeon’s research Dohoon Kim introduced a novel learning architecture that enables the parallel acquisition of multiple types of domain knowledge and their efficient integration and utilization. The proposed framework achieves superior performance with substantially lower computational cost compared to existing parameter-efficient fine-tuning methods. Image: Overview of Dohoon Kim’s research Image: Group photo of the Winners Source: https://ece.snu.ac.kr/ece/news?md=v&bbsidx=57154 Translated by: Changhoon Kang, English Editor of the Department of Electrical and Computer Engineering, changhoon27@snu.ac.kr...

SNU ECE Professor Woo Young Choi’s research team named to the 2025 National R&D Top 100 Achievements Reliability breakthrough via 3D NEM memory integration in CMOS interconnect layers Proposition of next-generation ultra-low-power, high-reliability semiconductor device platform ▲ Professor Woo Young Choi’s research team, College of Engineering, Seoul National University The College of Engineering at Seoul National University announced that the 3D-integrated CMOS–NEM memory technology developed by Professor Woo Young Choi’s research team in the Department of Electrical and Computer Engineering has been selected for the 2025 National Research and Development (R&D) Top 100 Achievements. Prof. Choi’s team successfully addressed the long-standing reliability challenges that have hindered the practical adoption of NEM devices by introducing a novel approach that directly integrates nanoelectromechanical (NEM) memory devices three-dimensionally within CMOS interconnect layers previously used only passively, while preserving the intrinsic advantages of NEM technology, including ultra-low power consumption, zero leakage current, and abrupt switching behavior. In particular, the core achievement selected for inclusion in the 2025 National R&D Excellent Achievements Top 100 is a NEM memory device featuring a Torsional-Via-Assisted (TVA) anchor structure that allows controlled torsional motion. This design effectively disperses mechanical stress concentration arising from repeated operation, experimentally demonstrating approximately a fivefold improvement in durability and stable operational characteristics compared to conventional structures. The technological significance of this work was formally recognized through its selection as the cover article of the December 2024 issue of IEEE Electron Device Letters, a leading international journal in the field. Notably, the proposed structure leverages vias already used in standard CMOS back-end interconnect processes, enabling a dramatic enhancement in reliability without additional area overhead or process cost. Furthermore, the team demonstrated the feasibility of implementing physically unclonable functions (PUFs) and associative memory using NEM memory devices, with these results published as cover articles in the July and September 2025 issues of Advanced Intelligent Systems, respectively. ▲ Electron microscope image of the via-anchor-based 3D CMOS–NEM memory structure and corresponding journal cover 2025 National R&D Top 100 Achievements Article Link: https://biz.chosun.com/science-chosun/science/2025/12/22/YTF3XQS275GMLPJOJXXX62WNEU/?utm_source=naver&utm_medium=original&utm_campaign=biz Source: https://ece.snu.ac.kr/ece/news?md=v&bbsidx=57141 Translated by: Changhoon Kang, English Editor of the Department of Electrical and Computer Engineering, changhoon27@snu.ac.kr...

At this year’s ICT Paper Competition, innovative research across a broad range of fields—including AI semiconductors, neuromorphic computing, generative AI, mobility, VR/AR, large language model (LLM) systems, and next-generation displays—were selected as award-winning entries. The winning papers were chosen through a comprehensive evaluation based on originality of ideas, theoretical rigor, experimental validation, performance assessment, and potential future impact. Jae Seung Woo (Seoul National University) The Grand Prize was awarded to Jae Seung Woo for his research on ultra-fast, low-power synaptic learning implemented using a 3-transistor (3T) embedded NOR flash memory architecture based on a 28 nm CMOS process. The proposed structure alleviates bottlenecks in conventional memory-based neural networks while enabling stable weight modulation and high energy efficiency at the single-cell level. By demonstrating improvements in both process compatibility and performance, the work received high recognition for its strong applicability to future AI semiconductor and neuromorphic systems. Hyoseok Lee (Korea Advanced Institute of Science and Technology) The Excellence Award recipients Hyoseok Lee and Sohwi Lim identified the fundamental cause of artifacts and quality degradation in existing Latent Diffusion Inverse Solvers, which stems from unstable reverse-diffusion dynamics. To address this issue, their paper proposes a Measurement-Consistent Langevin Corrector (MCLC) that reduces distribution mismatch at each time step. This research presents a new direction that substantially improves both the stability and quality of LDM-based zero-shot inverse solvers. Juhee Heo (Sookmyung Women’s University) Another Excellence Award recipient, Juhee Heo, presented a highly contemporary and impactful study by integrating quantum convolutional neural networks (QCNNs) with reinforcement learning (PPO) to jointly consider detection, transmission, reliability, and freshness. In addition, the proposed predictive-based (proactive) information delivery framework for enhancing Cooperative Adaptive Cruise Control (CACC) safety offers a meaningful research direction with strong potential for further studies in future 6G-based intelligent transportation infrastructures. Johnghyun Ko (Seoul National University) The Distinguished Award recipient Jonghyun Ko was recognized for research that proposes a new direction for generative AI hardware by implementing both probabilistic sampling and deterministic computation within a single device using HfO₂-based ferroelectric tunnel junctions. By realizing latent-space sampling at the hardware level, the study is expected to have significant academic and technological impact on next-generation intelligent semiconductor research, considering its creativity and scalability. Minhyuk Kim (Kyung Hee University) Distinguished Award recipients Minhyuk Kim and Junhyeong Shim addressed the fundamental trade-off in VR streaming between high-resolution delivery and increased encoding latency by leveraging user attention prediction. Rather than relying solely on conventional foveated streaming approaches that consider only gaze location, their work introduces a novel design framework based on attention-probability-driven grid merging and adaptive resolution allocation, greatly enhancing the feasibility of real-world system implementation. Jeongwoo Kim (Daegu Gyeongbuk Institute of Science and Technology) Distinguished Award recipients Jeongwoo Kim and Jaehun Lee reexamined caching strategies for large language model service systems. Existing approaches—such as exact-match, prefix, and semantic caching—are inefficient due to neglecting query semantics or relying on traditional heuristics. Their study proposes a centroid-based caching method to efficiently manage redundant queries, along with a cache replacement strategy that accounts for semantic locality and dynamically adjusts cache hit rates to balance accuracy and latency under varying workloads. Hyunwook Cho (Pohang University of Science and Technology) Distinguished Award recipients Hyunwook Cho, Donghyuk Kim, Yonggon Park, Seunghoon Oh, Sangbu Yoon, and Jaeyong Lee presented an innovative approach to addressing the ECC decoding bottleneck encountered during tiny-read operations in SSDs by reusing Locally Correctable Codes (LCC). Achieving more than a 60% reduction in read latency without requiring additional hardware modifications, the work was highly praised for both its creativity and practicality. Hyunsu Jung (Kyungpook National University) Distinguished Award recipient Hyunsu Jung proposed a geometric-phase-based varifocal lens optical system that enables control over virtual content depth in AR devices. The system supports real-time, full-color AR images with multiple polarizations and depths, effectively addressing the vergence-accommodation conflict. The study includes concrete models and experimental demonstrations for full-color implementation, while minimizing the number of switching elements required for variable depth control. Soeun Lee (Yonsei University) Finally, Distinguished Award recipients Soeun Lee, Seokgyu Hong, Juhyun Lee, and Yongseon Hwang presented a study aimed at resolving the mobility–reliability trade-off of LTPO-grade oxide driving TFTs through a dual-channel structure combining ALD-IGO and sputtered IGZO. The work demonstrates high industrial impact and strong potential for extension to next-generation high-resolution, low-power display backplane devices, with a high level of completeness in both process development and analytical methodology. Source: https://m.etnews.com/20251216000203 Translated by: Changhoon Kang, English Editor of the Department of Electrical and Computer Engineering, changhoon27@snu.ac.kr...

(From left) Professor Woo Young Choi and researcher Jaemin Yeom of the ECE Department at Seoul National University A paper authored by researchers Jaemin Yeom, Jae Seung Woo, and Jin Wook Lee from the Three-Dimensional Integration & Device Lab (TIDL) led by Professor Woo Young Choi has been selected as the cover article of the January 2026 Issue of IEEE Electron Device Letters (EDL). Founded in 1980, EDL is recognized as one of the world’s most influential journals, publishing original and significant contributions in the theory, modeling, design, performance, and reliability of semiconductor devices. Details of the paper selected as the cover article for this issue of EDL are as follows. January 2026 Issue (First Author: Jaemin Yeom): The study proposes a capacitive synapse architecture in which two ferroelectric capacitors operate as a differential pair, addressing the low sensing margin issue inherent to ferroelectric capacitors while enabling the implementation of ternary synaptic weights. (This research was supported by the Next-Generation Intelligence Semiconductor Foundation of the Ministry of Science and ICT.) Source: https://ece.snu.ac.kr/ece/news?md=v&bbsidx=57119 Translated by: Changhoon Kang, English Editor of the Department of Electrical and Computer Engineering, changhoon27@snu.ac.kr...

Yeongtak Oh, a Ph.D. candidate in the Data Science & AI Laboratory (advised by Professor Sungroh Yoon) of Seoul National University’s Department of Electrical and Computer Engineering, has been selected as a Winner in the Qualcomm Innovation Fellowship Korea (QIFK) 2025, announced at the final event held on November 27. QIFK is a scholarship and research support program organized by Qualcomm for graduate students in Korea, designed to identify and support outstanding research in AI through dedicated funding and scholarships. More than 120 submissions were received in this year’s edition, from which 15 were ultimately selected as Winners. Oh’s research proposes the world’s first post-training methodology for personalizing multimodal large language models (LLMs) based on reinforcement learning. The approach demonstrates significantly superior generalization performance compared to existing post-training techniques, particularly in image captioning tasks involving complex scenes where multiple concepts coexist within a single image. Image: Overview of the proposed methodology Image: Ph.D. candidate Yeongtak Oh Image: Group photo of the Winners Image: Ph.D. candidate Yeongtak Oh delivering his presentation Source: https://ece.snu.ac.kr/ece/news?md=v&bbsidx=57099 Translated by: Changhoon Kang, English Editor of the Department of Electrical and Computer Engineering, changhoon27@snu.ac.kr...

Professor Jungsuek Oh of the Department of Electrical and Computer Engineering at Seoul National University has been selected for the Technology category of the 2025 Samsung Future Technology Development Program. In recent years, Prof. Oh has led research that integrates AI with radio technology to address major industrial challenges. The excellence of his research group has been widely recognized through distinctions such as the Samsung Electronics DX Division Head IT Innovation Award. The Samsung Future Technology Development Program is a nonprofit research funding initiative launched by Samsung Electronics in 2013, with a total endowment of 1.5 trillion KRW. The program aims to advance fundamental science, drive innovation in industrial technologies, address pressing societal challenges through science and technology, and cultivate world-class scientific talent in Korea. It supports creative frontier research in fundamental science, the foundation of scientific and technological progress; materials science, which underpins manufacturing; and ICT and convergence technologies, which enable industrial advancement and the creation of new markets. Prof. Oh will conduct a four-year research and development project titled “Implementation and Performance Verification of an Ultra-Dense 6G MIMO Antenna-DPD Integrated System Based on Probabilistic Inverse-Design AI Models.” Project Overview: For next-generation 6G communications, the Upper-Mid Band (7-24 GHz) spectrum is drawing increasing attention. However, this band faces key limitations: lower data rates compared to mmWave 5G and degraded coverage relative to existing Sub-6GHz systems. To address these challenges, active research is underway on ultra-dense MIMO systems, which maximize communication capacity and coverage by packing a greater number of antennas within a given aperture. Yet, in such extremely dense array environments, antennas are positioned so closely that coupling increases sharply, and the limited physical area forces components for isolation, matching and Envelope Correlation Coefficient (ECC) control to be placed in very close proximity. This results in strong interdependence among design variables and lengthy design cycles, since performance improvements rely heavily on structural modifications. To overcome these limitations, the proposed research seeks to develop a probabilistic inverse-design model based on generative AI techniques, such as diffusion models, that can effectively model the vast design space and complex nonlinear relationships inherent to ultra-dense MIMO arrays. Nonetheless, severe coupling and limited area impose unavoidable practical performance limitations, making it difficult to achieve high levels of isolation and matching conditions. These constraints introduce uncertainty in securing optimal performance for MIMO systems integrated with Digital Predistortion (DPD). Moreover, conventional DPD methods—that inadequately account for dynamic operation conditions—struggle to provide optimized performance when applied to ultra-dense antenna arrays. As such, this project aims to establish an AI-driven antenna-DPD design framework to address the practical performance limitations encountered in extreme ultra-dense MIMO environments. Through this framework, the research seeks to develop cost-efficient, high-data-rate MIMO communication systems based on ultra-dense antenna architectures and to explore novel structural design possibilities that conventional approaches have been unable to reach. Source: https://ece.snu.ac.kr/ece/news?md=v&bbsidx=57047 Translated by: Changhoon Kang, English Editor of the Department of Electrical and Computer Engineering, changhoon27@snu.ac.kr...

Hansol Seo, a Ph.D. candidate under the supervision of Professor Jeonghun Kwak in the Department of Electrical and Computer Engineering at Seoul National University, received the Silver Prize at the 2025 Samsung Display Industry-Academia Collaboration Technical Paper Competition. Since its launch in 2018, the competition has aimed to promote the dissemination of research achievements in the field of display technology and to strengthen collaboration between industry and academia. In this year’s edition, a total of 182 papers were submitted, from which one Grand Prize, five Gold Prizes, six Silver Prizes, and six Bronze Prizes were awarded. Seo’s research focuses on the surface stabilization and high-resolution patter ning of quantum dots, utilizing a mechanism in which ligand attachment and crosslinking occur through ultraviolet exposure at specific wavelengths. Source: https://ece.snu.ac.kr/ece/news?md=v&bbsidx=57016 Translated by: Changhoon Kang, English Editor of the Department of Electrical and Computer Engineering, changhoon27@snu.ac.kr...

A research team from Professor Seong-Cheol Kim’s laboratory in the Department of Electrical and Computer Engineering at Seoul National University—consisting of Jihye Kim, Soram Kim, and Sechan Oh—won the President’s Award from the Institute of Information & Communications Technology Planning & Evaluation (IITP) at “ICT Challenge 2025,” organized by the Ministry of Science and ICT and IITP. ICT Challenge 2025 is a competition in which teams of three master’s or doctoral students participating in one of the following government-supported programs—▲Information Technology Research Center Program, ▲ICT Creative Consilience Program, and ▲Innovative Human Resource Development for Local Intellectualization Program—present and demonstrate practical and creative research ideas in their respective fields of study. Now in its 7th year since its launch in 2019, the competition attracted a record 206 teams (618 participants) from 81 research centers across 38 universities nationwide. Under the theme “Imaginations of Future Talent Become Reality”, participants showcased innovative ideas in various fields, including ▲Artificial Intelligence (AI) and Software (SW), ▲Smart Devices (including AI semiconductors), ▲Digital Convergence, and ▲Cybersecurity. Following preliminary rounds, mentoring sessions with employees from sponsoring companies (Amazon Korea and Kakao), and a final evaluation stage, 16 teams were ultimately selected as award recipients. Prof. Seong-Cheol Kim’s research team won the IITP President’s Award for their project titled “Real-Time Three-Dimensional Mapping and Aerial Monitoring System through UAM Collaboration,” and received a cash price of 5 million KRW. Source: https://ece.snu.ac.kr/ece/news?md=v&bbsidx=57001 Translated by: Changhoon Kang, English Editor of the Department of Electrical and Computer Engineering, changhoon27@snu.ac.kr...