| 2026 | DATE | MX-SAFE: Versatile Inference-and Training-Proof Microscaling Format with On-the-Fly Exponent and Mantissa Bit Allocation. | Dahoon Park, Jahyun Koo, Sangwoo Hwang, Jaeha Kung |
| 2026 | HPCA | GustavSNN: Unleashing the Power of Gustavson's Algorithm on SNN Acceleration with Column-Parallel Tick-Batch Dataflow. | Sangwoo Hwang, Donghun Lee, Jahyun Koo, Jaeha Kung |
| 2025 | ASPDAC | RISC-V Driven Orchestration of Vector Processing Units and eFlash Compute-in-Memory Arrays for Fast and Accurate Keyword Spotting. | Gunil Kang, Dahoon Park, Hojin Lee, Sangwoo Jung, Jiyong Park, Jung Gyu Min, Youngjoo Lee, Jaeha Kung |
| 2025 | DATE | FlexENM: A Flexible Encrypting-Near-Memory with Refresh-Less eDRAM-Based Multi-Mode AES. | Hyunseob Shin, Jaeha Kung |
| 2025 | ICCD | Dissecting and Re-Architecting 3D NAND Flash PIM Arrays for Efficient Single-Batch Token Generation in LLMS. | Yongjoo Jang, Sangwoo Hwang, Hojin Lee, Sangwoo Jung, Donghun Lee, Wonbo Shim, Jaeha Kung |
| 2025 | ISCA | FlexNeRFer: A Multi-Dataflow, Adaptive Sparsity-Aware Accelerator for On-Device NeRF Rendering. | Seock-Hwan Noh, Banseok Shin, Jeik Choi, Seungpyo Lee, Jaeha Kung, Yeseong Kim |
| 2025 | ISLPED | CAM-CIM: A Hybrid Compute-in-Memory Using Content-Addressable Memory with Subword Split Mapping for Reduced ADC Resolution. | Sangwoo Jung, Hojin Lee, Yejin Lee, Jiyong Park, Dahoon Park, Hyunseob Shin, Jong-Hyeok Yoon, Jaeha Kung |
| 2025 | ISLPED | Jack Unit: An Area- and Energy-Efficient Multiply-Accumulate (MAC) Unit Supporting Diverse Data Formats. | Seock-Hwan Noh, Sungju Kim, Seohyun Kim, Daehoon Kim, Jaeha Kung, Yeseong Kim |
| 2025 | ISLPED | RIMIX: RISC-V Core with MIXed-Precision SIMD Instruction Extensions Supported by Oracle-Assisted Sub-Network Search for Efficient TinyML. | Jiyong Park, Dahoon Park, Yeeun Hong, Jaeha Kung |
| 2024 | ASPLOS | NDPipe: Exploiting Near-data Processing for Scalable Inference and Continuous Training in Photo Storage. | Jungwoo Kim, Seonggyun Oh, Jaeha Kung, Yeseong Kim, Sungjin Lee |
| 2024 | DAC | OPAL: Outlier-Preserved Microscaling Quantization Accelerator for Generative Large Language Models. | Jahyun Koo, Dahoon Park, Sangwoo Jung, Jaeha Kung |
| 2024 | ISCAS | A Ready-to-Use RTL Generator for Systolic Tensor Arrays and Analysis Using Open-Source EDA Tools. | Jooyeon Lee, Donghun Lee, Jaeha Kung |
| 2023 | DAC | DBPS: Dynamic Block Size and Precision Scaling for Efficient DNN Training Supported by RISC-V ISA Extensions. | Seunghyun Lee, Jeik Choi, Seock-Hwan Noh, Jahyun Koo, Jaeha Kung |
| 2022 | ICCD | LightNorm: Area and Energy-Efficient Batch Normalization Hardware for On-Device DNN Training. | Seock-Hwan Noh, Junsang Park, Dahoon Park, Jahyun Koo, Jeik Choi, Jaeha Kung |
| 2021 | BMVC | ZeBRA: Precisely Destroying Neural Networks with Zero-Data Based Repeated Bit Flip Attack. | Dahoon Park, Kon-Woo Kwon, Sunghoon Im, Jaeha Kung |
| 2021 | ISCAS | Adaptive Input-to-Neuron Interlink Development in Training of Spike-Based Liquid State Machines. | Sangwoo Hwang, Junghyup Lee, Jaeha Kung |
| 2019 | DAC | Peregrine: A Flexible Hardware Accelerator for LSTM with Limited Synaptic Connection Patterns. | Jaeha Kung, Junki Park, Sehun Park, Jae-Joon Kim |
| 2019 | ISLPED | Similarity-Based LSTM Architecture for Energy-Efficient Edge-Level Speech Recognition. | Junseo Jo, Jaeha Kung, Sunggu Lee, Youngjoo Lee |
| 2019 | ISLPED | WMixNet: An Energy-Scalable and Computationally Lightweight Deep Learning Accelerator. | Sangwoo Jung, Seungsik Moon, Youngjoo Lee, Jaeha Kung |
| 2018 | DATE | The CAMEL approach to stacked sensor smart cameras. | Saibal Mukhopadhyay, Marilyn Wolf, Mohammed Faisal Amir, Evan Gebhardt, Jong Hwan Ko, Jaeha Kung, Burhan Ahmad Musassar |
| 2018 | DATE | Maximizing system performance by balancing computation loads in LSTM accelerators. | Junki Park, Jaeha Kung, Wooseok Yi, Jae-Joon Kim |
| 2017 | DATE | Adaptive weight compression for memory-efficient neural networks. | Jong Hwan Ko, Duckhwan Kim, Taesik Na, Jaeha Kung, Saibal Mukhopadhyay |
| 2017 | IJCNN | On-chip training of recurrent neural networks with limited numerical precision. | Taesik Na, Jong Hwan Ko, Jaeha Kung, Saibal Mukhopadhyay |
| 2017 | ISCA | A Programmable Hardware Accelerator for Simulating Dynamical Systems. | Jaeha Kung, Yun Long, Duckhwan Kim, Saibal Mukhopadhyay |
| 2016 | IJCNN | ReRAM Crossbar based Recurrent Neural Network for human activity detection. | Yun Long, Eui Min Jung, Jaeha Kung, Saibal Mukhopadhyay |
| 2016 | ISCA | Neurocube: A Programmable Digital Neuromorphic Architecture with High-Density 3D Memory. | Duckhwan Kim, Jaeha Kung, Sek M. Chai, Sudhakar Yalamanchili, Saibal Mukhopadhyay |
| 2016 | ISLPED | Dynamic Approximation with Feedback Control for Energy-Efficient Recurrent Neural Network Hardware. | Jaeha Kung, Duckhwan Kim, Saibal Mukhopadhyay |
| 2015 | ISLPED | A power-aware digital feedforward neural network platform with backpropagation driven approximate synapses. | Jaeha Kung, Duckhwan Kim, Saibal Mukhopadhyay |
| 2011 | DAC | Thermal signature: a simple yet accurate thermal index for floorplan optimization. | Jaeha Kung, Inhak Han, Sachin S. Sapatnekar, Youngsoo Shin |