Sungmin Lee 이성민

Sungmin Lee, a Ph.D. student at

Embedded Intelligent Systems (EIS) Lab

Department of Integrated Technology

College of Computing

Yonsei University

Contact

i.am.sungmin.lee [at] yonsei.ac.kr
i.am.sungmin.lee [at] gmail.com

Bio

I am a Ph.D. student working with Prof. JeongGil Ko. My research interest spans vision-based real-time 3D environment understanding, AI-driven sensor data analysis and AI-driven sensor network security.

Education

Ph.D. student, 2020-Present, School of Integrated Technology, Yonsei University, Seoul, Korea
- Advisor: Prof. JeongGil Ko
B.Eng., 2018-2020, School of Integrated Technology, Yonsei University, Seoul, Korea
- One year early graduation

Publications

JaeYeon Park, Kichang Lee, Sungmin Lee, Mi Zhang, JeongGil Ko. "AttFL: A Personalized Federated Learning Framework for Time-series Mobile and Embedded Sensor Data Processing", ACM UbiComp 2023.
Sungmin Lee, Hyungi Kim, Kyung Won Lee, Eun Su Kim, Hyung-Mo Kim, Hyungsoon Im, Hyun C Yoon, JeongGil Ko, Eunha Kim. "Indolizine-based fluorescent compounds array for noninvasive monitoring of glucose in bio-fluids using on-device machine learning", Dyes and Pigments 2023
Sungmin Lee, Hyungi Kim, Jun Sik Min, Eunsu Kim, Junwon Choi, JeongGil Ko, Eunha Kim. "Fluorescent sensor array for high-precision pH classification with machine learning-supported mobile devices". Dyes And Pigments 2021

Project experiences

Usage Pattern-based Virtual Clustering and Utility Optimization Techniques for Building-scale Air Solutions

- Duration: 2023.05 - 2023.12
- Role: Leading Researcher
- Partners:
  - LG Electronics (Home Appliances & Air Solutions), Korea
- Experiences:
  - Self-supervised clustering on unlabeled time-series data
  - HVAC zone clustering

Smart, Attack-Resistant Internet of Things Networks (STACK)

- Duration: 2021.03 - 2024.02
- Role: Researcher
- Partners:
  - Korea, Republic of
    - KETI, SNU, Security Platform
  - Sweden
    - RISE, Husqvarna, LumenRadio, ASSA ABLOY
  - Romania
    - BEIA
- Experiences:
  - Building AI model for Flooding Attack Detection in RPL networks
  - Implementing FDTLS with Contiki-NG

Low-latency 3D XR Object Transmission Platform Development for Vehicular HUDs

- Duration: 2021.03 - 2023.02
- Role: Researcher
- Partners:
  - EPITONE, Korea
- Experiences:
  - 3D Pointcloud Compression
  - Visual-based Pose refinement

Teaching experiences

Software Project (Undergraduate), Yonsei Univ, Fall 2023
Advanced Algorithms (Undergraduate), Yonsei Univ, Fall 2021
Advanced Programming (Undergraduate), Yonsei Univ, Spring 2021

Awards and Honors

Best Project Award, Inter-university Alliance for Furture vehicular Technology(I4FT), Yonsei, Summer&Winter 2023
Full Scholarship, School of Integrated Technology, Yonsei University, 2018-2020