Tae Jun Ham, Seonghak Kim, and Sung Jun Jung, Young H. Oh, Yeonhong Park, Yoon Ho Song, Junghoon Park, Sanghee Lee, Kyoung Park, Jae W. Lee, and Deog-Kyoon Jeong, "A3: Accelerating Neural Network Attention Mechanism with Approximation", 26th IEEE International Symposium on High Performance Computer Architecture (HPCA), San Diego, California, February 2020.
Shine Kim, Jonghyun Bae, Hakbeom Jang, Wenjing Jin, Jeonghun Gong, Seungyeon Lee, Tae Jun Ham, and Jae W. Lee, "SSDStreamer: Specializing I/O Stack for Large-Scale Machine Learning", IEEE Micro, September/October 2019.
Young H. Oh, Quan Quan, Daeyeon Kim, Seonghak Kim, Jun Heo, Jaeyoung Jang, Sung Jun Jung, and Jae W. Lee, "A Portable, Automatic Data Quantizer for Deep Neural Networks", IEEE International Conference on Parallel Architectures and Compilation Techniques (PACT-27), Limassol, Cyprus, November 2018.
Channoh Kim, Jaehyeok Kim, Sungmin Kim, Dooyoung Kim, Namho Kim, Gitae Na, Young H. Oh, Hyeon Gyu Cho, and Jae W. Lee, "Typed Architectures: Architectural Support for Lightweight Scripting", 22nd ACM Architectural Support for Programming Languages and Operating Systems (ASPLOS), Xi'an, China, April 2017.
Doo Young Kim, Jin Min Kim, Hakbeom Jang, Jinkyu Jeong, and Jae W. Lee, "A Neural Network Accelerator for Mobile Application Processors", IEEE Transactions on Consumer Electronics, 61(4), November 2015.
NAND 플래시 기반 심층신경망 학습 시스템, 연구재단, 2020.3-2023.2
뉴럴 프로세싱 시스템 연구, 삼성전자, 2017.11-2020.10
Beyond Limit, 삼성전자, 2018.11-2021.10

" Tensor Virtualization Technique to Support Efficient Data Reorganization for CNN Accelerators," DAC 2020 (to appear)
"A Novel CNN(Convolutional Neural Network) Accelerator That Enables Fully-pipelined Execution of Layers," ICCD 2019
"Fast Performance Estimation and Design Space Exploration of Manycore-based Neural Processors," DAC 2019
"C-GOOD: C-code Generation Framework for Optimized On-device Deep Learning," ICCAD 2018
"Joint Optimization of Speed, Accuracy, and Energy for Embedded Image Recognition Systems," DATE 2018
단말용 뉴럴 프로세서 시뮬레이션 및 소프트웨어 최적화 기술,  삼성종합기술원, 2016. 12 - 2020. 10
MIDAP (Memory-In-the DAtapath Processor) 뉴럴 프로세서의 성능 개선 연구, 삼성전자, 2018.5 - 2020.4
이종 하드웨어 가속기를 포함하는 모바일 플랫폼을 위한 시스템 수준의 딥 러닝 추론 최적화 기법, 삼성전자, 2018.3 - 2018.12

Hawkware: Network Intrusion Detection based on Behavior Analysis with ANNs on an IoT Device, Design Automation Conference (DAC), Jul 2020
DADE: a fast data anomaly detection engine for kernel integrity monitoring, The Journal of Supercomputing, Aug 2019
Real-Time Anomalous Branch Behavior Detection with a GPU-inspired Engine for Machine Learning Models, Design Automation and Test in Europe (DATE), Mar 2019
An SoC Architecture for Learning-Based Online Anomaly Detection on ARM, Design Automation Conference (DAC) WIP, Jun 2018
Mimicry Resilient Program Behavior Modeling with LSTM based Branch Models, DEEP LEARNING AND SECURITY WORKSHOP, May 2018
Behavior-based Malware Detection in HW support, 1억, 삼성전자
AI 포렌식 빅데이터 기반 지능형 보안 위협 분석, 8500만, 서울특별시
Embedded 시스템에서의 (AI 기반) 공격탐지 및 데이터 전송 솔루션, 1억, 삼성전자

"Partitioning Compute Units in CNN Acceleration for Statistical Memory Traffic Shaping,"  D. Jung, S. Lee, W. Rhee, and J. Ahn, IEEE Computer Architecture Letters, Vol. 17, No. 1, 2018
뉴럴 프로세싱 시스템 연구, 삼성전자, 2017/11-2020/10
복합 심층학습 응용분야를 위한 가속기 구조 연구, 삼성미래기술육성재단, 2017/12-2019/11

"FlexLearn: Fast and Highly Efficient Brain Simulations Using Flexible On-Chip Learning", Eunjin Baek, Hunjun Lee, Youngsok Kim, and Jangwoo Kim, ACM/IEEE International Symposium on Microarchitecture (MICRO), Oct 2019
"MnnFast: A Fast and Scalable System Architecture for Memory-Augmented Neural Networks", Hanhwi Jang, Joonsung Kim, Jae-Eon Jo, Jaewon Lee, and Jangwoo Kim, ACM/IEEE International Symposium on Computer Architecture (ISCA), Jun 2019
"Flexon: A Flexible Digital Neuron for Efficient Spiking Neural Network Simulations"
Dayeol Lee, Gwangmu Lee, Dongup Kwon, Sunghwa Lee, Youngsok Kim, and Jangwoo Kim, ACM/IEEE International Symposium on Computer Architecture (ISCA), Jun 2018
"μLayer: Low Latency On-Device Inference Using Cooperative Single-Layer Acceleration and Processor-Friendly Quantization", Youngsok Kim, Joonsung Kim, Dongju Chae, Daehyun Kim, and Jangwoo Kim, ACM European Conference on Computer Systems (EuroSys), Mar 2019
"FIDR: A Scalable Storage System for Fine-Grain Inline Data Reduction with Efficient Memory Handling", Mohammadamin Ajdari, Wonsik Lee, Pyeongsu Park, Joonsung Kim, and Jangwoo Kim, ACM/IEEE International Symposium on Microarchitecture (MICRO), Oct 2019
인공지능 가상머신: 이종 인공지능의 동시, 고속, 독립 실행을 위한 컴퓨터 구조/삼성미래기술육성사업/2019.6-2022.5
이종 스파이크 뉴런 기반의 인간 두뇌 규모 시뮬레이션을 위한 프로세서 및 시스템 개발/한국연구재단/2017.3-2021.2
대규모 뉴럴 프로세싱을 위한 FPGA 기반의 확장형 시스템 개발/삼성전자/2017.11-2020.10