Professor

Soo-Mook Moon

Professor
Department of Electrical and Computer Engineering
Seoul National University
1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
 
E-mail: smoon at snu.ac.kr
URL: https://altair.snu.ac.kr/smoon
Phone: +82-2-880-1814
Secretary: Park, So-Jin (phone: +82-2-880-2646)

Areas of Interests

  • Compiler and virtual machine optimization
  • AI Research (Federated Learning, Graph Neural Networks, Shortcut Learning, AI4Code)
  • Blockchain (State Optimization, Security and Privacy) 

Soo-Mook Moon leads the Virtual Machine and Optimization (VM&O) Laboratory in the Department of Electrical and Computer Engineering at Seoul National University. VM&O Lab. is researching blockchains, compiler and platform optimizations, and a few AI topics.

Selected Publications over the Last 10 Years

  • “Ethane: Debloating State Data using Compact Trie for Account-based Blockchain” Junmo Lee, Jaehun Kim, Jiyong Youn, Soo-Mook Moon, The 21st European Conference on Computer Systems (EuroSys 2026)
  • “BugSweeper: Function-Level Detection of Smart Contract Vulnerabilities Using Graph Neural Networks” Uisang Lee, Changhoon Chung, Junmo Lee, Soo-Mook Moon, 2026 AAAI conference on artificial intelligence (AAAI 2026). (Oral)
  • “Shortcut Features as Top Eigenfunctions of NTK: A Linear Neural Network Case and More”, Jinwoo Lim, Suhyun Kim, Soo-Mook Moon, 39th Conference on Neural Information Processing Systems (NeurIPS 2025) (Spotlight)
  • “RouTEE: Secure, Scalable, and Efficient Off-Chain Payments using Trusted Execution Environments”, Junmo Lee, Seongjun Kim, Sanghyeon Park, Soo-Mook Moon, the 39th Annual Computer Security Applications Conference (ACSAC 2024)
  • “Trie-Hashimoto: State Trie-Based Proof-of-Work Mining for Optimizing Blockchain Storage”, Jae-Yun Kim, Junmo Lee, Soo-Mook Moon, IEEE ACCESS, Vol. 12, 2024
  • “BRAIN: Blockchain-based Inference and Training Platform for Large-Scale Models”, Sanghyeon Park, Junmo Lee, Soo-Mook Moon, IEEE ACCESS, Vol. 12, 2024
  • “DEPTHFL: DEPTHWISE FEDERATED LEARNING FOR HETEROGENEOUS CLIENTS”, Minjae Kim , Sangyoon Yu, Suhyun Kim, Soo-Mook Moon. The 11th International Conference on Learning Representations. (ICLR 2023).
  • “Solving PBQP-based Register Allocation using Deep Reinforcement Learning”, Minsu Kim , Jeong-Keun Park , Soo-Mook Moon. 2022 International Symposium on Code Generation and Optimization (CGO 2022)
  • “Ethanos: Efficient Bootstrapping for Full Nodes on Account-based Blockchain“, Jae-Yun Kim, Junmo Lee, Yeonjae Koo, Sanghyeon Park, Soo-Mook Moon. 2021 European Conference on Computer Systems (EuroSys 2021)
  • “Irregular Register Allocation for Translation of Test-pattern Programs“, Minsu Kim , Jeong-Keun Park , Soo-Mook Moon. ACM Transactions on Architecture and Code Optimization, Volume 18 , Issue 1. January 2021
  • “PerDNN: Offloading Deep Neural Network Computations to Pervasive Edge Servers“, Hyuk-Jin Jeong, Hyeon-Jae Lee, Kwang Yong Shin, Yong Hwan Yoo, Soo-Mook Moon. 40th IEEE International Conference on Distributed Computing Systems (ICDCS 2020)
  • “ShadowTutor: Distributed Partial Distillation for Mobile Video DNN Inference“, Jae-Won Chung, Jae-Yun Kim, Soo-Mook Moon. The 49th International Conference on Parallel Processing (ICPP 2020)
  • “Snapshot-based Loading Acceleration of Web Apps with Nondeterministic JavaScript Execution“, ​JiHwan Yeo, ChangHyun Shin, and Soo-Mook Moon. The 2019 World Wide Web Conference (WWW 2019)
  • “Seamless Offloading of Web App Computations From Mobile Device to Edge Clouds via HTML5 Web Worker Migration“, Hyuk-Jin Jeong, Chang Hyun Shin, Kwang Yong Shin, Hyeon-Jae Lee, Soo-Mook Moon. The ACM Symposium on Cloud Computing 2019 (SoCC 2019)
  • “Accelerating Web Application Loading with Snapshot of Event and DOM Handling“, ​JiHwan Yeo, JinSeok Oh, and Soo-Mook Moon. The 28th International Conference on Compiler Construction (CC 2019)
  • “Output-based Intermediate Representation for Translation of Test-pattern Programs“, Minsu Kim, Jeong-Keun Park, S. Kim, I. Yang, H. Jung and Soo-Mook Moon. 2019 International Conference on Compilers, Architectures and Synthesis For Embedded Systems (CASES 2019)
  • “IONN: Incremental Offloading of Neural Network Computations From Mobile Devices to Edge Servers“, Hyuk-Jin Jeong, Hyeon-Jae Lee, Chang Hyun Shin, and Soo-Mook Moon. The ACM Symposium on Cloud Computing 2018 (SoCC 2018)
  • “Web Application Migration with Closure Reconstruction“, Jin-Woo Kwon and Soo-Mook Moon, The 2017 World Wide Web conference (WWW 2017)

Awards

  • IBM Faculty Partnership Awards   September, 2000
    A total of about 100 IBM Faculty Partnership Awards were given worldwide this year (2000/2001), including all research areas. The description of the IBM Faculty Partnership Awards states: “Candidates must have an outstanding reputation for contributions in his or her field(s), or for the case of junior faculty, show unusual promise.”
  • LG Group R&D Awards   March, 2012
    LG Group
  • Best Teacher Award   2024, 2022, 2002
    College of Engineering, Seoul National University
  • Best Teacher Award   2023, 2021, 2019, 2018
    School of Electrical and Computer Engineering, Seoul National University

Current and Previous Industry Projects

  • LLVM-based Optimization of Mobile platform and GPUs (Samsung Electronics) 
  • LaTTe and VLaTTe: Optimized Java VM JIT compilers for RISCs and VLIWs (IBM T. J. Watson Research Center)
  • Translation of DRAM Test-Pattern Programs for Automated Test Equipment (Samsung Electronics)
  • Optimizations for Android Dalvik Virtual Machines for Multicores (Samsung Electronics)
  • Instruction scheduling for In-Order Superscalar Processors (Sun Microsystems)
  • Java Just-in-Time Compilation for Instruction-level Parallelism on EPIC Architectures (Intel)
  • Enhanced Pipelinine Scheduling for EPIC Architectures (HP-Intel IPF University Grants Program)
  • Enhanced Pipeline Scheduling for IPF with Cache Optimizations (Gelato at UIUC for HP)
  • Just-in-Time Compilation for Mobile JavaScript Engines (Samsung Electronics)
  • Java Optimization for Digital TVs and Blu-ray Disc Players (LG Electronics)
  • Optimizing Compilers for CalmRISC 8/16/32-bit microcontrollers (Samsung Electronics)

Biographical Sketch

Soo-Mook Moon received his Ph.D at the University of Maryland, College Park, in 1993. During 1992-1993, he worked at IBM Thomas J. Watson Research Center where he developed the IBM VLIW compiler. During 1993-1994, he was a software design engineer at the Hewlett-Packard Company in California Language Lab where he contributed to the development of an optimizing compiler for the PA-RISC CPUs. Since 1994, he has been with the faculty of the Seoul National University in the Department of Electrical and Computer Engineering where he is now a full professor. Professor Moon visited IBM T. J. Watson research center as a visiting scientist during the summer of 1997. He was with Sun Microsystems in 2002-2003 as a visiting professor. He led the LG-SNU platform center during 2012-2015, which collaborated with LG electronics on the optimization of LG webOS platform. In addition to platform research, he has recently expanded into blockchain and AI researches. He is a recepient of IBM faculty award in 2000 and LG group’s R&D award in 2012.