News

Bio

I am a Ph.D. student at Embedded Intelligent Systems(EIS) Lab under the supervision of Prof.JeongGil Ko and jointly advised by Prof.Songkuk Kim.
From Aug 2024, I am visiting Singapore Management University (SMU) as a visiting researcher, working with Prof. Rajesh Krishna Balan.
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.

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

In submission preprints

• [Pre4] "Tazza: Shuffling Neural Network Parameters for Secure and Private Federated Learning"
  Kichang Lee, Jaeho Jin, JaeYeon Park, JeongGil Ko.
  Dec, 2024. (In submission) [arXiv preprint]
  Security Federated Learning AI/ML Mobile


• [Pre3] "DeTrigger: A Gradient-Centric Approach to Backdoor Attack Mitigation in Federated Learning"
  Kichang Lee, Yujin Shin, Jonghyuk Yun, Jun Han, JeongGil Ko.
  Nov, 2024. (In submission) [arXiv preprint]
  Security Federated Learning AI/ML


• [Pre2] "Analyzing the Impact of the Automatic Ball-Strike System in Professional Baseball: A Case Study on KBO League Data"
  Kichang Lee, Kyungsik Han, JeongGil Ko.
  July, 2024. (Under review) [arXiv preprint]
  Sports Analytics HCI


• [Pre1] "Improving Local Training in Federated Learning via Temperature Scaling"
  Kichang Lee, Songkuk Kim, JeongGil Ko.
  May, 2024. (in submission) [arXiv preprint]
  Federated Learning AI/ML

Journal Papers

• [J5, 2025] "A Smartphone to the Rescue: Detecting Counterfeit Powdered Food Products"
  Jonghyuk Yun, Kyusik Lee, Kichang Lee, Bangjie Sun, Jaeho Jeon, JeongGil Ko, Inseok Hwang, Jun Han.
  GetMobile: Mobile Computing and Communications, Volume 28, Issue 4, 2025. [pdf], (Invited Paper)
  Mobile Security


• [J4, 2025] "GMT: Gzip-based Memory-efficient Time-series Classification"
  Kichang Lee*, Sungmin Lee*, JaeYeon Park, JeongGil Ko. (*Equally Contributing Co-first Authors)
  ICT Express, 2025. (IF=4.1, JCR IF TOP 23.0%) [pdf]
  AI/ML Mobile


• [J3, 2025] "Mind Your Indices! Index Hijacking Attacks on Collaborative Unpooling Autoencoder Systems"
  Kichang Lee, Jonghyuk Yun, Jaeho Jin, Jun Han, JeongGil Ko.
  Internet of Things, 2025. (IF=6.0, JCR IF TOP 11.4%) [pdf]
  Security AI/ML Mobile


• [J2, 2023] "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/ML Mobile


• [J1, 2023] "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 21.72%) [pdf]
  Medical AI/ML

Conference Papers

• [C4, 2024] "Effective Heterogeneous Federated Learning via Efficient Hypernetwork-based Weight Generation"
  Kichang Lee*, Yujin Shin*, Sungmin Lee, You Rim Choi, Hyung-Sin Kim, JeongGil Ko. (*Equally Contributing Co-first Authors)
  ACM Conference on Embedded Networked Sensor Systems (ACM SenSys) 2024, Hangzhou, China. (NRF-listed Top CS Conference) [arXiv], [pdf]
  Acceptance Rate: 18.5% (58 of 313)
  Federated Learning Mobile AI/ML


• [C3, 2024] "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.
  Korean Society of Medical Informatics (KOSMI) Spring Conference, 2024. Seoul, Republic of Korea [pdf]
  Best Poster Award 🏆🎉
  Medical AI/ML


• [C2, 2024] "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) [pdf] [project website]
  Acceptance Rate: 16.3% (46 of 263)- Best Paper Award 🏆🎉
  Mobile Security


• [C1, 2023] "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/ML Mobile

Demo / Poster / Workshop/ WiP Abstract

• [Abs1, 2024] "Measuring Visual Stimuli in Urban Environment Using Eye-tracking Through VR"
  Jiwon Chae, Jaemin Lee, Kichang Lee
  ACSP Annual Conference, 2024. Seattle, USA [pdf]
  HCI Mobile


• [P2, 2024] "Poster: A Memory Efficient Parameter-free Time-series Classification via gzip"
  Kichang Lee*, Sungmin Lee*, JeongGil Ko. (*Equally Contributing Co-first Authors)
  ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys) 2024. Tokyo, Japan. [pdf]
  Best Poster Runner-Up Award 🏆🎉
  AI/ML Mobile


• [P1, 2024] "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. [pdf] [project website]
  Mobile Security


• [D1, 2023] "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/ML Mobile

Project Experiences

• Monitoring and Evaluating the Performance of Olympic-level Swimmers ▼

  • Sports Analytics AI Mobile
  • Duration: 2024.8 ~ Present
  • Role: Researcher
  • Partners: Singapore Management University, Singapore Aquatics
  • Experiences
  • Implementing ubiquitous monitoring system for athletes
  • Designing and implementation of ECG-based sleep quality estimation algorithms and systems
  • Designing and implementation of pose evaluation system for gym exercise

• Designing Private Evidential and Explainable Federated Learning Framework for Medical AI ▼

  • Federated Learning AI Medical
  • Duration: 2024.4 ~ Present
  • Role: Leading Researcher
  • Partners: Tel Aviv University
  • Experiences
  • Implementing privacy attack algorithms of federated learning
  • Designing and implementation of evidential and explainable AI algorithms for federated learning
  • Designing and implementation of defense algorithms against data leakage attacks in federated learing for cross-silo medical AI applications

• Designing Foundation Model For Electrocardiogram ▼

  • Medical AI
  • Duration: 2023.8 ~ 2024.8
  • 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 ~ 2023.8
  • 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

• 2024 Research Highlight. ▼

  • Research Highlight
  • ACM SIGMOBILE.
  • Jan 2025
  • [link1], [link2]

• Excellence Prize, 2nd Coding Literature Festival (제2회 코딩문학제 우수상) 2024. Korea. ▼

  • Excellence Prize (Top 0.38%; 13 of 3425)
  • Sparta Coding Club.
  • Sep 2024
  • [link (in Korean)]

• Visiting Scholar, Singapore Management University (SMU) 2024-2025. Singapore. ▼

  • Visiting Research Student Program
  • Topic: Monitoring and evaluating the performance of Olympic-level swimmers using computer vision technology.
  • Singapore Management University.
  • Aug 2024-Feb 2025
  • [link (in Korean)]

• Best Poster Award, KOSMI 2024. Seoul, Korea. ▼

  • "Coronary Artery Disease Prediction Using Treadmill Test ECG: Exploiting Pre-training via Temporal Invariant Contrastive Learning"
  • Korean Society of Medical Informatics (KOSMI) Spring Conference.
  • June 2024
  • [link (in Korean)]

• Best Paper Award, ACM MobiSys 2024. Tokyo, Japan. ▼

  • "PowDew: Detecting Counterfeit Powdered Food Products using a Commodity Smartphone"
  • ACM International Conference on Mobile Systems, Applications, and Services.
  • June 2024
  • [link (in Korean)]

• Best Poster Runner-Up Award, ACM MobiSys 2024. Tokyo, Japan. ▼

  • "Poster: A Memory Efficient Parameter-free Time-series Classification via gzip"
  • ACM International Conference on Mobile Systems, Applications, and Services.
  • June 2024
  • [link (in Korean)]

• Visiting Scholar, Keio University 2024. Japan. ▼

  • Visiting Researcher
  • Keio University.
  • Jan 2024

• 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
  • [link (in Korean)]

• 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. IEEE Transactions on Mobile Computing (2024, 2025), CSCW (2024), ICT Express (2024), IMWUT/Ubicomp (2024), ACM CHI (2025)

Talks

• HeartQuake: Accurate low-cost non-invasive ECG monitoring using bed-mounted geophones.
  1st SCIS Industry Day, Singapore Management University, Singapore - Sep, 30, 2024
• What Do Ph.D. Students Do? - Research Advice for Youth Researchers.
  (Invited) Youth Scholar Training Project, 2024. Daegu, Republic of Korea. - Jul, 13, 2024
• Coronary Artery Disease Prediction Using Treadmill Test ECG: Exploiting Pre-training via Temporal Invariant Contrastive Learning
  Korean Society of Medical Informatics (KOSMI), 2024. Seoul, Republic of Korea. - Jun, 20, 2024
• Poster: A Memory Efficient Parameter-free Time-series Classification via gzip
  ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys), Tokyo, Japan. — Jun, 4, 2024
• 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