News

• Apr.2024: One paper and two poster accepted at Mobisys 2024!
• Feb.2024: I am attending A3 Foresight Workshop 2024 held in Kyoto Japan! I'm going to to present my work FLex&Chill!
• Jan.2024: I am attending KHCI 2024! I'm going to to present our paper AttFL in SIGCHI top-conference papers session!
• Jan.2024: I am visiting Keio (SFC) University (Japan) as a vistiting researcher to share my works and discuss future joint-research!
• Jan.2024: Sungmin and my project on designing a low-resource, parameter-free time-series classification via a compressor won the Best Project Award in the Inter-university Alliance for Future Vehicular Technology (I4FT)!
• Oct.2023: I am attending IMWUT/Ubicomp 2023 in Cancun, Mexico! I am going to present our paper AttFL!
• Aug.2023: My work with JaeYeon and Sungmin on designing a personalized federated learning framework for mobile and embedded sensing systems is accepted to PACM IMWUT and will be presented at ACM UbiComp 2023!
• Jun.2023: I am attending ACM Mobisys 2023 in Helsinki, Finland! I am going to present my demo on demonstrating index-based attacks on collaborative inference systems!
• Apr.2023: My work with JaeYeon on designing an effective and self-evaluating deep model for arrhythmia detection is accepted to the Artificial Intelligence in Medicine journal!
• Feb.2023: I presented my work-in-progress, "Intriguing Properties of Max-Pooling Indices" at the A3 Foresight Workshop held in Incheon!

Bio

My name is Kichang Lee. I am an integrated M.S./Ph.D. student at Embedded Intelligent Systems(EIS) Lab under the supervision of Prof.JeongGil Ko.
My primary research interests lie in machine learning (ML) and deep learning (DL) applied to mobile and embedded systems, with a particular focus on federated learning.
Recently, I've been delving into intelligent clinical and healthcare systems, as well as exploring security issues within deep learning models and systems.
I received my B.S. degree from the school of integrated technology at Yonsei University.

Education

• Yonsei University, Seoul
• Ph.D. student in School of Integrated Technology
• Advisor: Prof. JeongGil Ko
• Mar.2022 - Present


• Yonsei University, Seoul
• B.S. in School of Integrated Technology
• Mar.2019 - Feb.2022 (one year early graduation)

Research Interests

• Federated Learning
• Efficient Federated Learning
• Secure Federated Learning
• Self-Supervised Federated Learning
• Security/Privacy in Intelligent Systems
• Intelligent Systems for Medical and Clinical Systems and Applications
• Evidential and Explainable Artificial Intelligence
• Human Centered Embedded/Mobile Systems and Applications

Publications

Journal Papers

• "AttFL: A Personalized Federated Learning Framework for Time-series Mobile and Embedded Sensor Data Processing"
  JaeYeon Park, Kichang Lee, Sungmin Lee, Mi Zhang, JeongGil Ko.
  Proceedings of the ACM (PACM) on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Volume 6, Issue 3, September 2023. (Also to be presented at ACM UbiComp 2023) [pdf]
  Federated Learning AI Mobile


• "Self-Attention LSTM-FCN Model for Arrhythmia Classification and Uncertainty Assessment"
  JaeYeon Park, Kichang Lee, Noseong Park, Seng Chan You, JeongGil Ko.
  Artificial Intelligence in Medicine, 2023. (IF=7.011, JCR IF TOP 25%) [pdf]
  Medical AI

Conference Papers

• "Anonymized Submission"
  Kichang Lee, Jonghyuk Yun, Jaeho Jin, Jun Han, JeongGil Ko.
  The Network and Distributed System Security (NDSS) Symposium, 2025. (Submitted) [preprint available on request]
  Security AI Mobile


• "Anonymized Submission"
  Jiwon Chae, Kichang Lee
  ACSP Annual Conference, 2024. (Submitted)
  HCI Mobile


• "Coronary Artery Disease Prediction Using Treadmill Test ECG: Exploiting Pre-training via Temporal Invariant Contrastive Learning"
  Kichang Lee, Dajung Boo, JeongGil Ko, Seng Chan You.
  Apr, 2024. (in submission)
  Medical AI


• "FLex&Chill: Improving Local Federated Learning Training with Logit Chilling"
  Kichang Lee, Songkuk Kim, JeongGil Ko.
  Jan, 2024. (in submission) [arXiv preprint]
  Federated Learning AI


• "PowDew: Detecting Counterfeit Powdered Food Products using a Commodity Smartphone"
  Jonghyuk Yun, Kyusik Lee, Kichang Lee, Bangjie Sun, Jaeho Jeon, JeongGil Ko, Inseok Hwang, Jun Han.
  ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys) 2024. Tokyo, Japan. (NRF-listed Top CS Conference) [To appear]
  Acceptance Rate: 16.3% (46 of 263)
  Mobile Security


• "AttFL: A Personalized Federated Learning Framework for Time-series Mobile and Embedded Sensor Data Processing"
  JaeYeon Park, Kichang Lee, Sungmin Lee, Mi Zhang, JeongGil Ko.
  ACM International Joint Conference on Pervasive and Ubiquitous Computing (ACM UbiComp) 2023. Cancun, Mexico. (NRF-listed Top CS Conference) [pdf]
  Federated Learning AI Mobile

Demo / Poster / Workshop/ WiP Abstract

• "Poster: Towards Counterfeit Powdered Food Products Detection using a Commodity Smartphone"
  Jonghyuk Yun, Kyusik Lee, Kichang Lee, Bangjie Sun, Jaeho Jeon, JeongGil Ko, Inseok Hwang, Jun Han.
  ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys) 2024. Tokyo, Japan. [To appear]
  Mobile Security
• "Poster: A Memory Efficient Parameter-free Time-series Classification via gzip"
  Kichang Lee*, Sungmin Lee*, JeongGil Ko. (* Equally contributing authors)
  ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys) 2024. Tokyo, Japan. [To appear]
  AI Mobile
• "Demo: Exploiting Indices for Man-in-the-Middle Attacks on Collaborative Unpooling Autoencoders"
  Kichang Lee, Jonghyuk Yun, Jun Han, JeongGil Ko.
  ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys) 2023. Helsinki, Finland. [pdf]
  Security AI Mobile

Project Experiences

• Designing Foundation Model For Electrocardiogram ▼

  • Medical AI
  • Duration: 2023.8 ~ Present
  • Role: Leading Researcher
  • Partners: Yonsei Severance Hospital
  • Experiences
  • Self-supervised learning for time-series data analysis
  • Designing and implementation of deep learning model for treadmill test (TMT) electrocardiogram
  • Designing and implementation of contrastive learning algorithm for electrocardiogram

• Development of AI-based customized mapping algorithm and 3D printing-based electrode-coupled microstructure for drug delivery for cochlear implant hearing rehabilitation ▼

  • Medical AI
  • Duration: 2022.3 ~ Present
  • Role: Researcher
  • Partners: Ajou University Hospital ENT
  • Experiences
  • Analysis of COTS cochlear implant tuning programs
  • Machine learning for predicting patient prognosis
  • Designing and implementing machine learning based future mapping and speech and hearing assessment results for cochlear implant patients

• Designing unsupervised learning methods for analyzing underwater acoustic data in the Arctic Ocean ▼

  • AI
  • Duration: 2022.8 ~ Present
  • Role: Researcher
  • Partners: Korea Polar Research Institute (KOPRI)
  • Experiences
  • Audio signal processing
  • Designing and implementation of unsupervised anomaly detection algorithm for audio data

Honors and Awards

• Best Project Award, Inter-university Alliance for Furture vehicular Technology (I4FT), Winter ▼

  • Yonsei University
  • January 2024

• Grand Prize, 1st National Competition for the Entrepreneurship of Disabled/Non-disabled College Students.
  (제1회 전국 장애·비장애 대학생 창업경진대회 대상) ▼

  • Korea National University of Welfare
  • February 2022

• Best Poster Award, Yonsei School of Integrated Technology Consilience Research Conference, 2021. ▼

  • School of Integrated Technology, Yonsei University
  • December 2021

• Full Scholarship. ▼

  • School of Integrated Technology, Yonsei University
  • 2019-2021

Academic Service

• TPC member. TBD
• Session orgnizer. TBD
• Reviewer. CSCW (2024), ICT Express (2024), IMWUT/Ubicomp (2024)

Talks

• FLex&Chill: Improving Local Federated Learning Training with Logit Chilling
  A3 Foresight Workshop (THE 7TH WORKSHOP ON INTELLIGENT IOT FOR EMPOWERING THE PEOPLE'S LIFESTYLE AND WELL-BEING) , Kyoto, Japan. — Feb, 28, 2024
• AttFL: A Personalized Federated Learning Framework for Time-series Mobile and Embedded Sensor Data Processing
  (Invited) SIGCHI-sponsored Top Conference Session, HCI Korea 2024, South Korea. — Jan, 25, 2024
• AttFL: A Personalized Federated Learning Framework for Time-series Mobile and Embedded Sensor Data Processing
  ACM International Joint Conference on Pervasive and Ubiquitous Computing (ACM UbiComp), Cancun, Mexico. — Oct, 12, 2023
• Demo: Exploiting Indices for Man-in-the-Middle Attacks on Collaborative Unpooling Autoencoders
  ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys), Helsinki, Finland. — Jun, 20, 2023
• Intriguing Properties of Max-Pooling Indices
  A3 Foresight Workshop (THE 5TH WORKSHOP ON INTELLIGENT IOT FOR EMPOWERING THE PEOPLE'S LIFESTYLE AND WELL-BEING) , Incheon, Republic of Korea. — Feb, 15, 2023
• Introduction to AI Systems: From theory to deployment
  (Invited) Daegun AI Innovation Lab Make-a-thon , Daegu, Republic of Korea. — Aug, 3, 2022

Teaching Experience

• Teaching Assistant
• Advanced Programming (IIT1001-1), (Spring 2024)
• Software Project (IIT4202-1), (Fall 2023)
• Understanding The World With Data (YCS1012-1), (Spring 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022)
• Computational Thinking and SW Programming (YCS1001-2), (Spring 2022, Fall 2021, Spring 2021)
• Tutor*
• Mathematics for Economics I (ECO1101), Fall 2020
• Signals and Systems (IIT2005), Fall 2020
• Advanced Algorithm (IIT2001), Fall 2020

Skills

• Languages : Python, C, C++
• Others : Matlab