Efficient Computing Lab.

The Efficient Computing Laboratory (ECL) is a part of Department of AI at UST ETRI Campus. Gajeong-ro 218, Yuseong-gu, Daejoen South Korea.

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7-416 ETRI, Gajeong-ro 218,Yuseong-gu123, Daejeon, South Korea

Welcome to the Efficient Computing Lab. We focus on energy efficiency, system optimization, user experience, and sustainable tech solutions. Our research interests are the followings:

• Model Compression: Enhancing machine learning models’ efficiency through techniques like pruning, quantization, and knowledge distillation for better performance in resource-limited settings.
• AI Compiler: Developing optimized AI compilers to reduce computational power, energy use, and execution time, improving efficiency and sustainability.

For detailed research areas and insights into graduate life, please refer to the following slides. Students interested in pursuing graduate studies are encouraged to contact me directly after following the application instructions provided in the slides.

You can reach me at: leejaymin_at_etri_dot_re_dot_kr.

News

Apr 29, 2025 Our paper was accepted at IJCAI (NRF BK21 IF 4):tada:
Apr 22, 2025 Our paper was accepted at LCTES (NRF BK21 IF 2):tada:
Feb 21, 2025 Our paper was accepted at Sensors Journal (IF: 3.4, JCR24 Top 30.92%, Q2):tada:
Dec 17, 2024 Our paper was selected as a Distinguished Paper in the 1st International Conference on Artificial Intelligence Computing and Systems (AICompS) 2024:sparkles:
Dec 15, 2024 “QuantuneV2” was accepted at Future Generation Computer Systems Journal (IF: 6.2, JCR23 Top 9.4%, Q1):tada:
Nov 14, 2024 Our paper received Best Paper Award in 2024 IeMeK, held at Jeju in 13–16 Nov. 2024:sparkles:
Nov 8, 2024 Two papers was accepted at AIcompS 2024. Congratulations:tada:

Selected Publications

2025

  1. IJCAI
    Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to Giant
    Jemin Lee, Sihyeong Park, Jinse Kwon, Jihun Oh, and Yongin Kwon*
    In International Joint Conferences on Artificial Intelligence (IJCAI) 2025, To appear, NRF BK21 IF: 4, Acceptance Rate 19.3% (1042 papers accepted out of 5404 submitted)., Aug 2025
    PDF Code
  2. LCTES
    Multi-Level Machine Learning-Guided Autotuning for Efficient Code Generation on a Deep Learning Accelerator
    JooHyoung Cha, Munyoung Lee, Jinse Kwon, Jemin Lee, and Yongin Kwon
    In The 26th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES) 2025, To appear, NRF BK21 IF: 2, Acceptance Rate 38% (16 papers accepted out of 42 submitted)., Jun 2025
    PDF

2022

  1. ECCV
    CPrune: Compiler-informed model pruning for efficient target-aware DNN execution
    T. Kim, Yongin Kwon, Jemin Lee, Taeho Kim, and Sangtae Ha
    In European Conference on Computer Vision (ECCV), pp.651–667, Oct. 23-27, 2022, NRF BK21 IF: 2, Acceptance Rate 28% (1,650 papers accepted out of 5,803 submitted)., Oct 2022
    PDF Code

2020

  1. IEEE TMC
    PASS: Reducing redundant notifications between a smartphone and a smartwatch for energy saving
    Jemin Lee, Uichin Lee, and Hyungshin Kim
    IEEE Transactions on Mobile Computing,(impact factor: 5.538, JCR20: Top 17%, telecommunications rank #16 out of 91), ISSN: 1536-1233, doi: https://doi.org/10.1109/TMC.2019.2930506, Nov 2020
    PDF Code

2019

  1. MobiCom
    Fire in your hands: Understanding thermal behavior of smartphones
    Soowon Kang, Hyeonwoo Choi, Sooyoung Park, Chunjong Park, Jemin Lee, Uichin Lee, and Sung-Ju Lee
    In The 25th Annual International Conference on Mobile Computing and Networking, pp. 1-16, Los Cabos, Mexico, 21-25 Oct. 2019, NRF BK21 IF: 4, Acceptance Rate 19% (55 papers accepted out of 290 submitted)., Oct 2019
    PDF Website