Sangkeun (Matt) M Lee Data Scientist (R&D Associate) Contact lees4@ornl.gov | 865.574.8858 All Publications A dataset of recorded electricity outages by United States county 2014–2022 Active learning of neural network potentials for rare events... Performance analysis and comparison of data-driven models for predicting indoor temperature in multi-zone commercial building... Predicting Power Outage During Extreme Weather with EAGLE-I and NWS Datasets Understanding the Computing and Analysis Needs for Resiliency of Power Systems from Severe Weather Impacts Sensor Incipient Fault Impacts on Building Energy Performance: A Case Study on a Multi-Zone Commercial Building... High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity... Analysis of Correlation between Cold Weather Meteorological Variables and Electricity Outages Real-time Multi-granular Analytics Framework for HIT Systems HPC Analytics of Fused Thermal Plants Data to Optimize Operating Envelope Incipient Sensor Fault Impacts on Building Performance Through HVAC Controls: A Pilot Study... Impacts of New Sensor Types for Selected Advanced Controls... COVID-19 Pandemic Ramifications on Residential Smart Homes Energy Use Load Profiles... Development of an Open-source Alloy selection and Lifetime assessment tool for structural components in CSP... Identification of Critical Infrastructure via PageRank... Efficient Contingency Analysis in Power Systems via Network Trigger Nodes... A machine learning approach to predict thermal expansion of complex oxides... Exploiting user activeness for data retention in HPC systems... DATA FUSION: A PROJECT UPDATE & PATHWAY FORWARD... Advanced Health Information Technology Analytic Framework and Application to Hazard Detection Data Analysis Approach for Large Data Volumes in a Connected Community... Toward Quantifying Vulnerabilities in Critical Infrastructure Systems Uncertainty Quantification of Machine Learning Predicted Creep Property of Alumina-Forming Austenitic Alloys... ScaleML: Machine Learning based Heap Memory Object Scaling Prediction... Small Angle Scattering Data Analysis Assisted by Machine Learning Methods Pagination Current page 1 Page 2 Page 3 Next page ›› Last page Last » Key Links ORCID Organizations Computing and Computational Sciences Directorate Computer Science and Mathematics Division Mathematics in Computation Section Discrete Algorithms Group
