Sangkeun Matthew Lee

Senior Research Staff | Critical Infrastructure Resilience

Geospatial Science and Engineering Division | National Security Sciences Directorate
Oak Ridge National Laboratory | Oak Ridge, Tennessee

ORNL Profile  |  Google Scholar  |  ORCID  |  lees4 at ornl.gov

Website content updated September 2026

Professional Preparation

• KAIST, South Korea - B.S., Computer Science, 2004

• Seoul National University, South Korea - Ph.D., Computer Science and Engineering, 2012

Appointments

• Current - Senior Research Staff, Critical Infrastructure Resilience, Geospatial Science and Engineering Division, Oak Ridge National Laboratory

• 2015-present - Research staff member, Oak Ridge National Laboratory

• 2013-2015 - Postdoctoral Research Associate, Oak Ridge National Laboratory

Professional Experience

Sangkeun (Matt) Lee is a senior research staff member in the Critical Infrastructure Resilience Group at Oak Ridge National Laboratory (ORNL). He received his Ph.D. in Computer Science and Engineering from Seoul National University in 2012, joined ORNL as a postdoctoral research associate in 2013, and became a research staff member in 2015. He currently serves as Co-PI and Technical Lead for Enhancing Distribution Grid Anticipatory Resilience (EDGAR) and the U.S. Energy Dataspace, leading technical direction across grid-resilience analytics, governed energy-data sharing, geospatial interoperability, privacy-enhancing tools, secure analytics, and research-software delivery. His work connects large-scale graph and geospatial analysis, artificial intelligence, data engineering, and critical-infrastructure resilience for DOE sponsors, utilities, and research partners. His broader experience includes EAGLE-I, TASTI-GRID, GIA-DB, URBAN-NET, NAERM, building science, materials science, and medical informatics.

Selected Research and Development Projects

• EDGAR - Co-PI and Technical Lead for a grid-resilience platform integrating outage monitoring, weather and resilience analysis, and utility-facing decision support.

• U.S. Energy Dataspace - Co-PI and Technical Lead for governed energy-data discovery and sharing, identity and catalog interoperability, metadata and provenance, privacy-enhancing tools, secure analytics, and application integration.

• GIA-DB - Co-PI and Technical Lead for a secure data-sharing and analytics environment supporting Grid Resilience and Innovation Partnerships program analysis.

• TASTI-GRID - Technical contributions to weather and outage analytics, governed data products, and decision-support workflows for state and tribal grid-resilience investment planning.

• EAGLE-I - Data collection, standardization, analytics, and dissemination for historical and near-real-time U.S. power-outage information.

• URBAN-NET and CASCADE - Critical-infrastructure interdependency analysis, graph-based impact estimation, and offline-capable research software for cascading-risk analysis.

• Earlier cross-domain R&D - Data analytics and machine learning for building performance, high-temperature alloys, health analytics, and large-scale graph systems.

Synergistic Activities

• Co-organizer and IEEE BigData point of contact for the 6th International Workshop on Big Data and AI-Assisted Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD 2026).

• Organizer of the first through fourth BTSD workshops held with IEEE Big Data from 2019 through 2022.

• Program committee service, peer review, publication mentoring, and technical review across data science, artificial intelligence, and infrastructure-resilience research.

• Member of the IEEE.

Fields of Interest

• Power-grid and critical-infrastructure resilience, including outage, restoration, interdependency, and consequence analysis.

• Geospatial and spatiotemporal analytics, including H3-based integration, weather-risk analysis, and decision support across irregular service territories.

• Artificial intelligence and machine learning for scientific discovery, predictive analytics, research copilots, and human-reviewed agentic workflows.

• Large-scale graph and data analysis, including heterogeneous graphs, ranking, clustering, link analysis, path mining, and high-performance analytics.

• Governed data ecosystems, metadata and provenance, catalog interoperability, privacy-enhancing technologies, secure sharing, and semantic integration.

• Big-data systems and data engineering, including scalable ETL, database architectures, reproducible pipelines, and reusable analytical platforms.

Awards

• 2023 ORNL CSMD Distinguished Software Award

• 2023 IEEE IRI Best Poster Award

• 2016 R&D 100 Award

• 2013 Honorable Mention Poster Award, 1st ORNL Annual Postdoctoral Research Symposium

• 2011 Best Paper Award, PIKM 2011 in conjunction with CIKM

U.S. Copyright Registrations

• Clean Energy Innovation Ecosystems Discovery - Measuring Innovation through Data Analytics (MIDAS), Copyright No. 80000023

• URBAN-NET-TOOLKIT, Copyright No. 80000012

Research Platforms and Software

• EDGAR - Grid-resilience analytics and utility decision support.

• U.S. Energy Dataspace - Governed discovery, sharing, and integration of energy data and applications.

• GIA-DB - Secure data sharing, analytics, and reporting for GRIP program data.

• ASCENDS - Advanced data science tools for non-data scientists.

• VizBrick - Interactive authoring of Brick building metadata models.

• ORiGAMI - Graph analytics for medical innovation and hypothesis discovery; 2016 R&D 100 Award.

Media

• CCSD's Lee wins best poster for storm risk study

• Materials - Quelling corrosion

• ORNL researchers achieve explainable AI for alloy design

Selected Recent Publications

Updated from the Google Scholar profile and ORNL publication records through September 2026. Full lists: Google Scholar | ORNL Research Profile

2026

• Ahmad, N., Chinthavali, S., Tansakul, V., Lee, S. M., Morris, J., & Bhusal, N. (2026). Scalable and Secure Power Outage Data Reporting: A Hexagonal Geospatial Approach. 2026 IEEE/PES Transmission and Distribution Conference and Exposition. DOI

2025

• Bhusal, N., Chinthavali, S., Carvalhaes, T., Lee, S. M., & Ahmad, N. (2025). Integrated Metrics for County-Level Resilience Ranking Using Entropy and TOPSIS. IEEE Access, 13, 205439-205456. DOI

• Lee, S. M., Chinthavali, S., Bhusal, N., Lebakula, V., Morris, J., & Iyer, G. (2025). Evaluating Multi-Weather Impacts on the U.S. Power Grid Reliability. 2025 IEEE International Conference on Information Reuse and Integration and Data Science, 55-60. DOI

• Morris, J., Lee, S. M., Chinthavali, S., Bhusal, N., Ahmed, N., & Iyer, G. (2025). HexWeather: Hexagonal Spatial Data Aggregation for Weather-Driven Grid Resilience Analysis. 2025 IEEE International Conference on Information Reuse and Integration and Data Science, 67-72. DOI

• Lee, J., Lee, S., Chinthavali, S., & Paal, S. (2025). A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms. IEEE Access, 13, 139583-139603. DOI

2024

• Tabassum, A., Lee, S., Bhusal, N., & Chinthavali, S. (2024). Power Outage Forecasting for System Resiliency During Extreme Weather Events. 2024 IEEE International Conference on Big Data, 8849-8851.

• Lee, J., Lee, S. M., Paal, S. G., & Chinthavali, S. (2024). A Generalized Outage Prediction Model for Various Types of Extreme Climate Events in Texas. 2024 IEEE International Conference on Big Data, 4162-4166.

• Lee, S. M., Bose, A., Bhusal, N., & Chinthavali, S. (2024). Capturing Infrastructure Interdependencies for Power Outages Prediction During Extreme Events. 2024 IEEE International Conference on Big Data, 2152-2161.

• Bhusal, N., Lee, S. M., Bose, A., Chinthavali, S., Allen-Dumas, M. R., & Kuruganti, T. (2024). Estimating Critical Customer Outages Resulting from Extreme Hurricanes. 2024 Resilience Week, 1-8.

• Lee, S. M., Tabassum, A., Bhusal, N., Ahmad, N., & Chinthavali, S. (2024). A Comprehensive Model for Analyzing the Effects of Power Outages on Customers. 2024 Resilience Week, 1-5.

• Bose, A., Lee, S., Bhusal, N., & Chinthavali, S. (2024). Correlating Power Outage Spread with Infrastructure Interdependencies During Hurricanes. 2024 IEEE International Conference on Information Reuse and Integration for Data Science.

• Bhusal, N., Chinthavali, S., Tabassum, A., Lee, S. M., Carvalhaes, T., Ahmad, N., et al. (2024). Historical Power Outages of the United States and the Social Vulnerability Index. 2024 IEEE Power & Energy Society General Meeting, 1-5.

• Bhusal, N., Chinthavali, S., Carvalhaes, T., Lee, S. M., Ahmad, N., Tabassum, A., et al. (2024). Analysis of Historical Power Outages of the United States and the National Risk Index. 18th International Conference on Probabilistic Methods Applied to Power Systems.

• Bhusal, N., Lee, S. M., Stenvig, N., Chinthavali, S., & Kuruganti, T. (2024). Impact Study of Thunderstorms on the U.S. Power Grid Using Publicly Available Datasets. 2024 IEEE/PES Transmission and Distribution Conference and Exposition, 1-5.

• Brelsford, C., Tennille, S., Myers, A., Chinthavali, S., Tansakul, V., Denman, M., et al. (2024). A Dataset of Recorded Electricity Outages by United States County 2014-2022. Scientific Data, 11(1), 271.

• Jung, G. S., Choi, J. Y., & Lee, S. M. (2024). Active Learning of Neural Network Potentials for Rare Events. Digital Discovery, 3(3), 514-527.

Public Data Product

• EAGLE-I team, including Lee, M. (updated 2026). EAGLE-I Historic Outages 2014-2025. Oak Ridge National Laboratory. Public county-level power-outage data product. DOI