Distinguished Design Award2022 Asian Solid-State Circuits Conference (A-SSCC) Student Design Contest / November 2022 Design : An Efficient Unsupervised Learning-based Monocular Depth Estimation Processor with Partial-Switchable Systolic Array Architecture in Edge Devices Awardee : Wonhoon Park, Dongseok Im, Hankyul Kwon, and Hoi-Jun Yoo

Best Live Demo Award2022 IEEE International Conference on Artificial Intelligence Circuits and Systems / June 2022 Design : A DNN Training Processor for Rubust Object Detection with Real-World Environmental Adaptation Awardee : Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, and Hoi-Jun Yoo

Best Paper Award2022 IEEE International Conference on Artificial Intelligence Circuits and Systems / June 2022 Design : HNPU-V2: A 0.95 mJ/frame DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation Awardee : Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, and Hoi-Jun Yoo

Outstanding Paper Award2022 IEEE Custom Integrated Circuits Conference / April 2022 Design : An 0.92 mJ/frame High-quality FHD Super-resolution Mobile Accelerator SoC with Hybrid-precision and Energy-efficient Cache Awardee : Zhiyong Li, Sangjin Kim, Dongseok Im, Donghyeon Han, and Hoi-Jun Yoo

Distinguished Design Award2021 Asian Solid-State Circuits Conference Student Design Contest / November 2021 Design : An Energy-efficient Deep Reinforcement Learning FPGA Accelerator for Online Fast Adaptation with Selective Mixed-precision Re-training Awardee : Wooyoung Jo, Juhyoung Lee, Seunghyun Park, and Hoi-Jun Yoo

Best Paper Award2021 The Neural Systems and Applications Technical Committee of the IEEE Circuits and Systems Society Design : A 64.1mW Accurate Real-Time Visual Object Tracking Processor with Spatial Early Stopping on Siamese Network Awardee : Soyeon Kim, Sangjin Kim, Sangyeob Kim, Donghyeon Han, and Hoi-Jun Yoo

Best Design Award2020 Asian Solid-State Circuits Conference Student Design Contest / November 2020 Design : An Energy-Efficient GAN Accelerator with On-Chip Training for Domain Specific Optimization Awardee : Soyeon Kim, Sanghoon Kang, Donghyeon Han, Sangyeob Kim, Sangjin Kim, and Hoi-Jun Yoo

Gold PrizeThe 26th Humantech Paper Award / February 2020 Design : GANPU: A 135TFLOPS/W Multi-DNN Training Processor for GANs with Speculative Dual-Sparsity Exploitation Awardee : Sanghoon Kang

Demo Award2019 Demonstration Session Certificate of Recognition (ISSCC 2020) / February 2020 Design : LNPU: A 25.3TFLOPS/W Sparse Deep-Neural-Network Learning Processor with Fine-Grained Mixed Precision of FP8-FP16 Awardee : Jinsu Lee

Best Paper Award2019 Best Paper Award(KAIST-Samsung Electronics) / August 2019 Design : UNPU: A 50.6TOPS/W unified deep neural network accelerator with 1b-to-16b fully-variable weight bit-precision Awardee :Jinmook Lee