Congratulations! Joo-Young Kim is awarded Research prize in Research Category of Outstanding Faculty Awards in Commemoratino of the 53rd Founding Anniversary It is based on the selection results of faculty members who have excelled in performance or made significant contributions to the school’s development
Read MoreCongratulations! Joo-Young Kim is awarded KAIST Q-Day Faculty Special Awards in S (technology value creation) category KAIST shall confer special awards to faculty members who have contributed to creating a campus atmosphere that welcomes questions in accordance with the QAIST new culture strategy, and with outstanding achievements in creative education/research
Read MoreCongratulations! We have a paper accepted to IEEE Custom Integrated Circuits Conference (CICC), 2024 “A 38.5TOPS/W Point Cloud Neural Network Processor with Virtual Pillar and Quadtree-based Workload Management for Real-Time Outdoor BEV Detection” Sukbin Lim, Jaehoon Heo, Jinho Yang, Joo-Young Kim
Read MoreCongratulations! We have a paper accepted to Journal of Solid-State Circuits (JSSC), 2024 “EPU: An Energy-Efficient Explainable AI Accelerator with Sparsity-free Computation and Heat Map Compression/Pruning” Junsoo Kim, Seunghee Han, Geonwoo Ko, Ji-Hoon Kim, Changha Lee, Taewoo Kim, Chan-Hyun Youn, and Joo-Young Kim
Read MoreCongratulations! We have a paper accepted to Asia and South Pacific Design Automation Conference , 2024 “ACane: An Efficient FPGA-based Embedded Vision Platform with Accumulation-as-Convolution Packing for Autonomous Mobile Robots ” Jinho Yang, Sungwoong Yune, Sukbin Lim, Donghyuk Kim, and Joo-Young Kim
Read MoreCongratulations! We have a paper accepted to IEEE/ACM International Symposium on Microarchitecture, 2023 “Strix: An End-to-End Streaming Architecture with Two-Level Ciphertext Batching for Fully Homomorphic Encryption with Programmable Bootstrapping” Adiwena Putra, Prasetiyo, Yi Chen, John Kim, and Joo-Young Kim
Read MoreCongratulations! We have a paper accepted to IEEE/ACM International Conference on Computer-Aided Design, 2023 “PRIMO: A Full-Stack Processing-in-DRAM Emulation Framework for Machine Learning Workloads” Jaehoon Heo, Yongwon Shin, Sangjin Choi, Sungwoong Yune, Jung-Hoon Kim, Hyojin Sung, Youngjin Kwon, and Joo-Young Kim
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