https://iris-lab.skku.edu/tag/processing-in-memory/ processing-in-memory Wowchemy (https://wowchemy.com)en-usTue, 18 Aug 2026 00:00:00 +0000 https://iris-lab.skku.edu/media/icon_hub30d19cd1ec39a1dd8652017ce0a280f_82173_512x512_fill_lanczos_center_3.png https://iris-lab.skku.edu/tag/processing-in-memory/ https://iris-lab.skku.edu/post/faculty_kangeun_jeon/ Tue, 18 Aug 2026 00:00:00 +0000 https://iris-lab.skku.edu/post/faculty_kangeun_jeon/ <div style="display: flex; gap: 0.5rem; margin-bottom: 1.5rem;"> <img src="kejeon.jpg" alt="Prof. Kang Eun Jeon" style="width: calc(50% - 0.25rem); aspect-ratio: 1 / 1; object-fit: cover; object-position: 50% 30%;"> <img src="dgist.jpg" alt="DGIST Campus" style="width: calc(50% - 0.25rem); aspect-ratio: 1 / 1; object-fit: cover;"> </div> <p>IRIS Lab에서 박사후연구원으로 함께했던 전강은 박사님이 2026년 8월 18일 DGIST 전기전자컴퓨터공학과 조교수로 부임하셨습니다.</p> <p>전강은 박사님은 홍콩과학기술대학교(HKUST)에서 전자공학 학사 및 전자컴퓨터공학 박사 학위를 취득한 후, 2022년 12월부터 2025년 8월까지 IRIS Lab에서 박사후연구원으로 재직하였습니다. 이후 2025년 9월부터 KAIST AI대학원에서 박사후연구원으로 연구를 이어왔습니다.</p> <p>주요 연구 분야는 Efficient AI와 Processing-in-Memory (PIM)로, 인메모리 컴퓨팅 하드웨어의 특성을 고려한 Quantization, Pruning, Weight Mapping 등 SW-HW Co-design을 통해 AI 모델의 연산 및 메모리 효율을 높이는 연구를 수행해 왔습니다. 최근에는 이러한 연구를 생성형 AI로 확장하여, 효율적인 추론을 위한 Flexible &amp; Adaptive Model Compression 연구를 진행하고 있습니다.</p> <p>그동안 ICCV, NeurIPS, ICCAD, DATE, ISLPED 등 주요 국제학회 및 저널에 다수의 연구 성과를 발표하였으며, 삼성전자 종합기술원(SAIT)과의 인메모리 컴퓨팅 공동연구 및 산업체와의 협력을 통해 연구 성과의 실제 시스템 적용에도 힘써 왔습니다.</p> <p>오랜 기간 IRIS Lab의 구성원으로 함께 연구했던 전강은 박사님의 교수 임용을 진심으로 축하드리며, 앞으로 DGIST에서 펼쳐갈 연구와 교육 활동을 응원합니다.</p> <p>Kang Eun Jeon, a former postdoctoral researcher at IRIS Lab, joined the Department of Electrical Engineering and Computer Science at DGIST as an Assistant Professor on August 18, 2026.</p> <p>Kang Eun received his B.S. in Electronic Engineering and Ph.D. in Electronic and Computer Engineering from the Hong Kong University of Science and Technology (HKUST). He subsequently joined IRIS Lab as a postdoctoral researcher from December 2022 to August 2025, and continued his research at the KAIST Graduate School of AI from September 2025.</p> <p>His research primarily focuses on Efficient AI and Processing-in-Memory (PIM), with particular emphasis on SW-HW co-design techniques including quantization, pruning, and weight mapping that account for the characteristics of in-memory computing hardware. More recently, he has expanded his research toward Flexible &amp; Adaptive Model Compression for efficient generative AI inference.</p> <p>His work has been published in leading journals and conferences including ICCV, NeurIPS, ICCAD, DATE, and ISLPED. He has also collaborated with Samsung Advanced Institute of Technology (SAIT) on in-memory computing and worked with industry partners to translate efficient AI research into practical systems.</p> <p>Congratulations to Kang Eun on his faculty appointment at DGIST. We wish him continued success in his research and teaching endeavors!</p>