Hunjun Lee (이헌준) Department of Computer Science Hanyang University 222 Wangsimni-ro, Seongdong-gu, Seoul, South Korea Bldg. ITBT Room 405-2 Email: hunjunlee@hanyang.ac.kr [dblp]

I am currently an assistant professor for the Department of Computer Science at Hanyang University.

Before joining Hanyang University, I was a post-doc researcher at Seoul National University.
I worked on designing a scalable computer architecture for brain-computer interfacing.

Before working as a post-doc researcher, I earned my Ph.D degree from Seoul National University under the supervision of Prof. Jangwoo Kim.
During my Ph.D., I focused on designing a brain simulation accelerator and analog-based process-in-memory architecture.
I also earned my BS degree from Seoul National University.

Research Interests

• Computer Architecture
• Brain-Computer Interface
• AI and Neuromorphic Computer Architecture
• Process-in-Memory Architecture

Invited Talks

• Computer Architecture for the Brain in Silico, in Vivo, and in Vitro presented at Samsung Advanced Institute of Technology (SAIT), May 9th, 2024
• An Extreme Energy-Efficient In-Memory DNN Acceleration Using 3D NAND Flash presented at Electronics and Telecommunications Research Institute (ETRI), March 13th, 2023
• Next-Generation Computer Architecture for Brain-Inspired Computing presented at Seoul National University AI Summer Camp, August 3rd, 2022
  Talk Link

Publications

1 denotes (co-)first authorship.
* denotes (co-)correspondence.

• Accurate and High-Throughput Analog-Digital DNN Acceleration using Sub-Network Scheduling
  Jintae Kim, Byoungjun Jeong, Changdae Kim, Narae Ryu, Eunji Pak, and Hunjun Lee^*
  Computer Architecture Letters, Feb. 2026.
  
  PIM Machine Learning Architecture
  

• TierX: A Simulation Framework for Multi-tier BCI System Design Evaluation and Exploration
  Seunghyun Song, Yeongwoo Jang, Daye Jung, Kyungsoo Park, Donghan Kim, Gwangjin Kim, Hunjun Lee, Jerald Yoo, and Jangwoo Kim
  Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 (ASPLOS) , Mar. 2026.
  
  BCI Machine Learning Architecture
  

• Efficient Image Super-Resolution Using Dynamic Quality Control with Recursive Model Structures
  Inho Lee, Jaemin Park, Seunghwan Lee, Tae Hyun Kim, Jiwon Seo, Hunjun Lee, and Yongjun Park
  IEEE Access , Jun. 2025.
  
  Machine Learning
  

• A Learning-Optimized Large-Scale Brain-Computer Interface
  Yeongwoo Jang, Daye Jung, Seunghyun Song, Hunjun Lee^*, and Jangwoo Kim
  Proceedings of the 52rd IEEE/ACM International Symposium on Computer Architecture (ISCA), Jun. 2025.
  
  BCI Machine Learning Architecture
  

• Rearchitecting a Neuromorphic Processor for Spike-Driven Brain-Computer Interfacing
  Hunjun Lee¹, Yeongwoo Jang, Daye Jung, Seunghyun Song, and Jangwoo Kim
  Proceedings of the 57th IEEE/ACM International Symposium on Microarchitecture (MICRO), Oct. 2024.
  Paper Code
  BCI Neuromorphic Architecture
  

• 3D-FPIM: An Extreme Energy-Efficient DNN Acceleration System Using 3D NAND Flash-Based In-Situ PIM Unit
  Hunjun Lee¹, Minseop Kim¹, Dongmoon Min, Joonsung Kim, Jongwon Back, Honam Yoo, Jong-Ho Lee, and Jangwoo Kim
  Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture (MICRO), Oct. 2022.
  Paper Code
  PIM Machine Learning Architecture
  

• NeuroSync: A Scalable and Accurate Brain Simulation System Using Safe and Efficient Speculation
  Hunjun Lee¹, Chanmyeong Kim¹, Minseop Kim, Yujin Chung, and Jangwoo Kim
  Proceedings of the 28th IEEE International Symposium on High-Performance Computer Architecture (HPCA), Apr. 2022.
  Paper Short Talk Link Long Talk Link Code
  Neuromorphic Architecture
  

• UC-Check: Characterizing Micro-operation Caches in x86 Processors and Implications in Security and Performance
  Joonsung Kim, Hamin Jang, Hunjun Lee, Seungho Lee, and Jangwoo Kim
  Proceedings of the 54th IEEE/ACM International Symposium on Microarchitecture (MICRO), Oct. 2021.
  Paper Code
  Security Architecture
  

• An Accurate and Fair Evaluation Methodology for SNN-Based Inferencing with Full-Stack Hardware Design Space Explorations
  Hunjun Lee¹, Chanmyeong Kim, Seungho Lee, Eunjin Baek, and Jangwoo Kim
  Neurocomputing, Sep 2021.
  Paper
  Neuromorphic Machine Learning Architecture
  

• NeuroEngine: A Hardware-based Event-driven Simulation System for Advanced Brain-inspired Computing
  Hunjun Lee¹, Chanmyeong Kim¹, Yujin Chung, and Jangwoo Kim
  Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), Apr 2021.
  Paper Short Talk Link Long Talk Link
  Neuromorphic Architecture
  

• FlexLearn: Fast and Highly Efficient Brain Simulations Using Flexible On-Chip Learning
  Eunjin Baek¹, Hunjun Lee¹, Youngsok Kim, and Jangwoo Kim
  Proceedings of the 52nd ACM/IEEE International Symposium on Microarchitecture (MICRO), Oct 2019.
  Paper Short Talk Link
  Neuromorphic Architecture
  

Education

• Ph.D., Electrical and Computer Engineering, Seoul National University
  • Mar. 2018 – Aug. 2023
• B.S., Electrical and Computer Engineering, Seoul National University
  • Mar. 2014 – Feb. 2018

Academic Services

Journal Review

• 2025: IEEE TC, IEEE CAL ISCA (LPC),
• 2024: IEEE TC, ACM TACO, IEEE CAL
• 2023: IEEE TC, ACM TACO, IEEE CAL
• 2022: Parallel Computing

Honors and Awards

• Global Ph.D. Fellowship (글로벌 박사 펠로우십)
  • National Research Foundation of Korea (NRF)
  • Mar. 2019 – Aug. 2023

Teaching Experience

• Graduate
  • SCE0004: Software Optimization (2025F)
• Undergraduate
  • ITE2031: Computer Architecture (2026S)
  • ELE4029: Compiler Design (2025F)
  • ITE2031: Computer Architecture (2025S)
  • ELE4029: Compiler Design (2024F)