Jangjae Lee is a Postdoctoral Research Fellow at the University of Houston working at the intersection of infrastructure resilience, climate risk, machine learning, and computer vision.
His work spans real-time power outage prediction, utility pole condition assessment with vision and LiDAR, and community resilience modeling using large-scale spatial and urban data.
Predicting climate-induced power outages, evaluating pole deterioration, and understanding community-level vulnerability through interpretable machine learning and spatial analytics.
Coastal utility pole inspection with Grounded SAM and LiDAR, extreme weather outage forecasting, and big-data-informed resilience assessment.
Department of Civil and Environmental Engineering
This section reflects the uploaded CV with professional appointments, education, and research direction aligned to the most current version.
Developing data-driven frameworks for infrastructure and community resilience assessment by integrating 311 service requests, LiDAR, machine vision, meteorological, and census data. Research includes infrastructure quality estimation, outage impact modeling, and field-based validation across multiple infrastructure systems.
Conducted national-scale power grid resilience analysis within the Grid Resilience Research group. Developed interpretable machine learning models for critical energy infrastructure systems and contributed to peer-reviewed publications on resilience enhancement.
Dissertation: ML-Based Decision Support: Modeling and Analysis of Power Outages in Texas Under Extreme Climate Conditions. Advisor: Dr. Stephanie G. Paal.
Thesis focused on seismic performance of exterior beam-column joint subassemblies reinforced with steel fibers.
Undergraduate training in architectural and structural engineering with strong foundations in design, analysis, and infrastructure systems.
Representative peer-reviewed work spanning outage forecasting, climate hazard modeling, and infrastructure analytics.
Lee, J., Zhang, Z., & Paal, S.G. · Computational Urban Science
Lee, J., Lee, S.M., Chinthavali, S., & Paal, S.G. · IEEE Access
Lee, J., Lee, S.M., Paal, S.G., & Chinthavali, S. · IEEE BigData 2024
Lee, J., & Paal, S.G. · IEEE BigData 2024
Lee, J., & Beck, A. · ASCE EMI Conference
Current and emerging projects include automated structural assessment and tilt measurement of coastal utility poles using Grounded SAM and LiDAR integration, integrated spatiotemporal assessment of infrastructure resilience and community vulnerability in Houston, and climate-informed outage forecasting using multi-source data.
Generalized and near-real-time prediction of electricity disruptions during winter storms and other hazardous climate events using meteorological, geographical, and socio-demographic inputs.
Automated assessment of utility pole deterioration and tilt angle estimation using computer vision, point cloud processing, semantic segmentation, and field-informed validation workflows.
Integrated spatiotemporal assessment of infrastructure resilience and community vulnerability through urban service requests, geospatial context, and interpretable data analytics.
Teaching and mentorship from the CV are reorganized here for clarity while preserving the substance of the original record.
A compact scan-friendly representation of the technical capabilities listed in the uploaded CV.