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Sangchul Lee

Korea University · 工学

研究室紹介

Professor Sangchul Lee's research lab specializes in interdisciplinary systems engineering with a focus on dynamic modeling, signal processing, and environmental systems. The lab develops advanced modeling and estimation techniques for complex mechanical and mechatronic systems, including multibody dynamics, vehicle transmission systems, and robotic manipulators. It also investigates environmental sustainability through hydrological modeling and ecosystem service assessment, particularly in wetland-groundwater interactions and soil vulnerability. Additionally, the lab explores explainable AI in audio and image analysis, emphasizing interpretability and human perception in AI-driven decision systems.

dynamic systems modelingdisturbance estimationenvironmental modelingexplainable AI (XAI)wetland-groundwater interaction

Research Overview

Papers
180
Total Citations
1,295
Papers (5y)
42
Primary Field
工学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
42total
2022
2023
2024
2025
2026
Citations per year (5y)
206total
20222023202420252026

Selected Papers

15
1
Article|74 citations·2022
Detecting Deepfake Voice Using Explainable Deep Learning Techniques
Suk-Young Lim, Dong‐Kyu Chae, Sangchul Lee
SJR Q2Applied SciencesOA

Fake media, generated by methods such as deepfakes, have become indistinguishable from real media, but their detection has not improved at the same pace. Furthermore, the absence of interpretability on deepfake detection models makes their reliability questionable. In this paper, we present a human perception level of interpretability for deepfake audio detection. Based on their characteristics, we implement several explainable artificial intelligence (XAI) methods used for image classification

Computer Vision and Pattern RecognitionComputer Science
2
Article|50 citations·2011
Test and error parameter estimation for MEMS — based low cost IMU calibration
Dongkyu Lee, Sangchul Lee, Sanghyuk Park, Sangho Ko
SJR Q2International Journal of Precision Engineering and Manufacturing
Aerospace EngineeringEngineering
3
Article|40 citations·1992
Explicit generalization of Lagrange's equations for hybrid coordinate dynamical systems
Sangchul Lee, John L. Junkins
SJR Q1Journal of Guidance Control and Dynamics

An explicit generalization of the classical Lagrange's equations (for discrete coordinate dynamical systems) to cover a large family of multibody hybrid discrete/distributed parameter systems is presented. The coupled system of ordinary and partial differential equations follows directly from spatial and time differentiation of various Lagrangian functional, whereas the boundary conditions are directly established from another explicit set of symbolic variational equations. Five illustrative exa

Control and Systems EngineeringEngineering
4
Article|29 citations·2010
Combined estimation method for inertia properties of STSAT-3
Dong Hoon Kim, Sungwook Yang, Dong-Ik Cheon, Sangchul Lee, Hwa-Suk Oh
SJR Q2Journal of Mechanical Science and Technology
Aerospace EngineeringEngineering
5
Article|27 citations·2018
Assessing the suitability of the Soil Vulnerability Index (SVI) on identifying croplands vulnerable to nitrogen loss using the SWAT model
Sangchul Lee, Ali M. Sadeghi, Gregory W. McCarty, Claire Baffaut, Sapana Lohani, Lisa F. Duriancik, Allen L. Thompson, In‐Young Yeo, Carlington W. Wallace
SJR Q1CATENAOA

Conservation practices are effective ways to mitigate non-point source pollutions, especially when implemented on critical source areas (CSAs) known as the areas contributing disproportionately high pollution loads. Although hydrologic models are promising tools to identify CSAs within agricultural landscapes, their application is limited to areas where data and modeling expertise are available. The Soil Vulnerability Index (SVI) developed by the USDA-Natural Resource Conservation Service (NRCS)

Water Science and TechnologyEnvironmental Science
6
Article|25 citations·2010
Sensorless torque estimation using adaptive Kalman filter and disturbance estimator
Sangchul Lee, Hyo‐Sung Ahn

This paper presents a stochastic estimation method and a signal processing based method for estimating disturbance torques without using any force sensors. The first method will address a robustness against measurement noises by estimating noise covariance. The second method will show several practical merits. By containing system models inside of the estimator, the total disturbance torque injected into the plant is estimated. The experimental results conducted using a master-slave manipulator

Control and Systems EngineeringEngineering
7
Article|21 citations·2014
A Systematic Approach for Dynamic Analysis of Vehicles With Eight or More Speed Automatic Transmission
Sangchul Lee, Yi Zhang, Dohoy Jung, Byungchan Lee
SJR Q2Journal of Dynamic Systems Measurement and Control

In this study, a dynamic model of a vehicle with eight or more speed automatic transmission (A/T) has been developed for the analysis of shift quality and dynamic behavior of the vehicle during shift events. Subsystem models for engine, torque converter, automatic transmission, drivetrain, transmission control unit (TCU), and vehicle are developed and integrated with signal information interface. The subsystems included in the model were carefully selected to improve the accuracy of the model by

Automotive EngineeringEngineering
8
Review|19 citations·2017
A review on volcanic gas compositions related to volcanic activities and non-volcanological effects
Sangchul Lee, Namhee Kang, Minji Park, Jin Yeon Hwang, Sung Hyo Yun, Hoon Young Jeong
SJR Q2Geosciences Journal
Global and Planetary ChangeEnvironmental Science
9
Article|17 citations·2024
Applications of geographically weighted machine learning models for predicting soil heavy metal concentrations across mining sites
Hye-Min Jeong, Younghun Lee, Byeongwon Lee, Euisoo Jung, Jai-Young Lee, Sangchul Lee
SJR Q1The Science of The Total Environment
Artificial IntelligenceComputer Science
10
Article|16 citations·2011
기후변화 시나리오에 따른 산림분포 취약성 평가
이상철, 최성호, 이우균, 박태진, 오수현, 김순아
한국산림과학회지

본 연구에서는 Intergovernmental Panel on Climate Change(IPCC) 기후변화 시나리오 A2와 B1에 따른 산림분포 취약성을 평가하였다. 산림분포 취약성은 한국형 산림 생태계 분포 모델 Thermal Analogy Groups(TAG) 의 산림분포예측 방법과 Hydrology Thermal Analogy Groups(HyTAG)에서 정의한 식생유형을 이용하여 기후 변화에 따른 잠재 식물상(Plant Functional Type: PFT)의 분포 변화를 기후변화 민감성과 적응성으로 나누어 평가되었다. 그 결과, 산림분포가 취약한 지역의 면적은 A2 시나리오에서 전체 국토 면적의 30.78%, B1에서는 2.81%로 나타났다. 행정구역별 취약성 평가 결과는 부산이 A2 시나리오에서 가장 취약하고 대구가 B1 시나리오에서 가장 큰 취약성을 나타냈다. 미래 발전 방향에 따라서 상이하게 구축된 시나리오 별 산림 분포 취약성 결과는 앞으로 산림 분야 적응대책수립에

11
Article|14 citations·2014
H ∞ and Sliding Mode Observers for Linear Time-Invariant Fractional-Order Dynamic Systems With Initial Memory Effect
Sangchul Lee, Yan Li, YangQuan Chen, Hyo‐Sung Ahn
SJR Q2Journal of Dynamic Systems Measurement and Control

The H∞ and sliding mode observers are important in integer-order dynamic systems. However, these observers are not well explored in the field of fractional-order dynamic systems. In this paper, the H∞ filter and the fractional-order sliding mode unknown input observer are developed to estimate state of the linear time-invariant fractional-order dynamic systems with consideration of proper initial memory effect. As the first result, the fractional-order H∞ filter is introduced, and it is shown th

Control and Systems EngineeringEngineering
12
Article|12 citations·2019
Enhancement of Agricultural Policy/Environment eXtender (APEX) Model to Assess Effectiveness of WetlandWater Quality Functions
Amirreza Sharifi, Sangchul Lee, Gregory W. McCarty, Megan Lang, Jaehak Jeong, Ali Sadeghi, Martin C. Rabenhorst
SJR Q1WaterOA

The Agricultural Policy/Environmental eXtender (APEX) model has been widely used to assess changes in agrochemical loadings in response to conservation and management led by US Department of Agriculture (USDA). However, the existing APEX model is limited in quantification of wetland water quality functions. This study improved the current model capacity to represent wetland water quality functions by addition of a new biogeochemical module into the APEX model. The performance of an enhanced APEX

Environmental ChemistryEnvironmental Science
13
Article|11 citations·2016
Rigid Body Inertia Estimation Using Extended Kalman and Savitzky-Golay Filters
Donghoon Kim, Sungwook Yang, Sangchul Lee
SJR Q2Mathematical Problems in EngineeringOA

Inertia properties of rigid body such as ground, aerial, and space vehicles may be changed by several occasions, and this variation of the properties influences the control accuracy of the rigid body. For this reason, accurate inertia properties need to be obtained for precise control. An estimation process is required for both noisy gyro measurements and the time derivative of the gyro measurements. In this paper, an estimation method is proposed for having reliable estimates of inertia propert

Aerospace EngineeringEngineering
14
Article|10 citations·2024
Comparative efficiency of the SWAT model and a deep learning model in estimating nitrate loads at the Tuckahoe creek watershed, Maryland
Jiye Lee, Dongho Kim, Seokmin Hong, Daeun Yun, Dohyuck Kwon, Robert L. Hill, Feng Gao, Xuesong Zhang, Kyung Hwa Cho, Sangchul Lee, Yakov Pachepsky
SJR Q1The Science of The Total Environment
Water Science and TechnologyEnvironmental Science
15
Article|9 citations·2023
Enhanced Trajectory Tracking via Disturbance-Observer-Based Modified Sliding Mode Control
Saad Jamshed Abbasi, Sangchul Lee
SJR Q2Applied SciencesOA

Trajectory tracking is a crucial aspect of controlling nonlinear systems and is an important area of research. Researchers have proposed several strategies to perform this task in the presence of perturbations, which are the sum of a system’s uncertainty, modeling errors, and external disturbances. Nonlinear systems, such as robot manipulators, have complex dynamics, and deriving their exact mathematical models is a tedious task. Therefore, the objective of this research is to design a model-fre

Control and Systems EngineeringEngineering

Research Areas

Aerospace EngineeringWater Science and TechnologyControl and Systems EngineeringInformation SystemsArtificial IntelligenceCivil and Structural Engineering

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