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Youngjib Ham

Seoul National University · 工学

研究室紹介

Professor Youngjib Ham's research lab specializes in digital twin technologies and data-driven infrastructure management, focusing on integrating real-time sensor data, UAV-based visual monitoring, and advanced analytics to enhance the resilience and efficiency of urban and building systems. The lab develops innovative methods for visual data analysis, thermal performance diagnostics, and personalized thermal comfort modeling using wearable sensors and machine learning. A key focus is on creating actionable insights for sustainable retrofitting and risk-informed decision-making in response to climate-related challenges.

digital twinthermal performanceUAV monitoringenergy retrofiturban resilience

Research Overview

Papers
127
Total Citations
3,168
Papers (5y)
65
Primary Field
工学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
65total
2022
2023
2024
2025
2026
Citations per year (5y)
787total
20222023202420252026

Selected Papers

15
1
Review|491 citations·2016
Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works
Youngjib Ham, Kevin Han, Jacob J. Lin, Mani Golparvar‐Fard
Visualization in EngineeringOA

Abstract Over the past few years, the application of camera-equipped Unmanned Aerial Vehicles (UAVs) for visually monitoring construction and operation of buildings, bridges, and other types of civil infrastructure systems has exponentially grown. These platforms can frequently survey construction sites, monitor work-in-progress, create documents for safety, and inspect existing structures, particularly for hard-to-reach areas. The purpose of this paper is to provide a concise review of the most

GeologyEarth and Planetary Sciences
2
Article|183 citations·2014
Mapping actual thermal properties to building elements in gbXML-based BIM for reliable building energy performance modeling
Youngjib Ham, Mani Golparvar‐Fard
SJR Q1Automation in Construction
GeologyEarth and Planetary Sciences
3
Article|177 citations·2020
Participatory Sensing and Digital Twin City: Updating Virtual City Models for Enhanced Risk-Informed Decision-Making
Youngjib Ham, Jaeyoon Kim
SJR Q1Journal of Management in Engineering

The benefits of a digital twin city have been assessed based on real-time data collected from preinstalled Internet of Things (IoT) sensors (e.g., traffic, energy use, air pollution, water quality) for managing the complex systems of cities, but the sensor-based reality information is likely insufficient to provide dynamic spatiotemporal information about physical vulnerabilities. Understanding cities’ current states of physical vulnerability can support city decision makers in analyzing associa

Media TechnologyEngineering
4
Article|137 citations·2022
Challenges, tasks, and opportunities in teleoperation of excavator toward human-in-the-loop construction automation
Jin Sol Lee, Youngjib Ham, Hangue Park, Jeonghee Kim
SJR Q1Automation in Construction
Radiological and Ultrasound TechnologyHealth Professions
5
Article|122 citations·2013
An automated vision-based method for rapid 3D energy performance modeling of existing buildings using thermal and digital imagery
Youngjib Ham, Mani Golparvar‐Fard
SJR Q1Advanced Engineering Informatics
GeologyEarth and Planetary Sciences
6
Article|101 citations·2021
AI-based risk assessment for construction site disaster preparedness through deep learning-based digital twinning
Mirsalar Kamari, Youngjib Ham
SJR Q1Automation in Construction
GeologyEarth and Planetary Sciences
7
Article|84 citations·2013
EPAR: Energy Performance Augmented Reality models for identification of building energy performance deviations between actual measurements and simulation results
Youngjib Ham, Mani Golparvar‐Fard
SJR Q1Energy and Buildings
GeologyEarth and Planetary Sciences
8
Article|67 citations·2020
Vision-based volumetric measurements via deep learning-based point cloud segmentation for material management in jobsites
Mirsalar Kamari, Youngjib Ham
SJR Q1Automation in Construction
Environmental EngineeringEnvironmental Science
9
Article|56 citations·2019
Automated content-based filtering for enhanced vision-based documentation in construction toward exploiting big visual data from drones
Youngjib Ham, Mirsalar Kamari
SJR Q1Automation in Construction
GeologyEarth and Planetary Sciences
10
Article|54 citations·2020
Physiological sensing-driven personal thermal comfort modelling in consideration of human activity variations
JeeHee Lee, Youngjib Ham
SJR Q1Building Research & Information

As one of the representative parameters for human energy metabolism, the metabolic rate has been considered as the significant factor for occupants’ thermal comfort analyses. Despite the importance of metabolic rate as a predictor of thermal comfort modelling, prior works rely on uncertain metabolic rate estimation without considering actual activity variations while occupying a building. This study aims at identifying the effect of metabolic rate on the thermal comfort models by proposing a rob

Building and ConstructionEngineering
11
Article|50 citations·2020
Probabilistic framework for assessing the vulnerability of power distribution infrastructures under extreme wind conditions
Seulbi Lee, Youngjib Ham
SJR Q1Sustainable Cities and Society
Environmental EngineeringEnvironmental Science
12
Article|46 citations·2014
3D Visualization of thermal resistance and condensation problems using infrared thermography for building energy diagnostics
Youngjib Ham, Mani Golparvar‐Fard
Visualization in EngineeringOA

Abstract Background Building deteriorations instigated by material degradations or moisture intrusions are the primary causes for energy inefficiency in many existing buildings. For choosing appropriate retrofits, it is important to carefully diagnose and analyze building areas in need of improvements. In addition to reliable sensing and analysis of as-is energy performance, an intuitive recording and visualization of energy diagnostic outcomes are also critical to effectively illustrate the as-

GeologyEarth and Planetary Sciences
13
Article|44 citations·2013
Automated Diagnostics and Visualization of Potential Energy Performance Problems in Existing Buildings Using Energy Performance Augmented Reality Models
Mani Golparvar‐Fard, Youngjib Ham
SJR Q1Journal of Computing in Civil Engineering

Quick and reliable identification of energy performance problems in buildings is a critical step in improving their efficiency. The current practice of building diagnostics typically involves nonintrusive data collection using thermal cameras. This requires large amounts of unordered and nongeo-tagged two-dimensional (2D) imagery to be manually analyzed at a later stage, which makes the analysis time-consuming and labor-intensive. Because of the absence of a benchmark for energy performance, ide

GeologyEarth and Planetary Sciences
14
Article|36 citations·2014
Three-Dimensional Thermography-Based Method for Cost-Benefit Analysis of Energy Efficiency Building Envelope Retrofits
Youngjib Ham, Mani Golparvar‐Fard
SJR Q1Journal of Computing in Civil Engineering

Recent research efforts to improve energy modeling and diagnostics for existing buildings have focused on devising methods based on digital photogrammetry or three-dimensional (3D) laser scanning and thermal imagery. Prior research has shown that fusing actual and expected 3D spatiothermal models provide valuable information for analyzing performance gaps. Until now, these methods have primarily focused on detecting and localizing potential performance problems without analyzing their associated

Building and ConstructionEngineering
15
Article|27 citations·2021
Large-Scale Visual Data–Driven Probabilistic Risk Assessment of Utility Poles Regarding the Vulnerability of Power Distribution Infrastructure Systems
Jaeyoon Kim, Mirsalar Kamari, Seulbi Lee, Youngjib Ham
SJR Q1Journal of Construction Engineering and Management

Inspecting and assessing existing utility poles has become increasingly important for reducing the vulnerability of power distribution infrastructure systems in disaster situations, which can enhance community resilience. Although vision-based systems have been applied to detect faults in power distribution infrastructures, little research currently exists on assessing component- and network-level failures of utility poles based on their geometric and environmental information. This paper aims t

Environmental EngineeringEnvironmental Science

Research Areas

Building and ConstructionGeologyMechanical EngineeringEnvironmental EngineeringRadiological and Ultrasound TechnologyCivil and Structural Engineering

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