Anika Tabassum Research Scientist Contact 865.341.3123 | TABASSUMA@ORNL.GOV All Publications Analysis of Historical Power Outages of the United States and the National Risk Index Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation Quantifying the Power System Resilience of the US Power Grid Through Weather and Power Outage Data Mapping Attention for Causal Relationship Discovery from Biological Neural Dynamics... Predicting Power Outage During Extreme Weather with EAGLE-I and NWS Datasets MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning... Li-ion Battery Material phase prediction through Hierarchical Curriculum Learning COVID-19 Pandemic Ramifications on Residential Smart Homes Energy Use Load Profiles... Efficient Contingency Analysis in Power Systems via Network Trigger Nodes Quantification of Energy Cost Savings through Optimization and Control of Appliances within Smart Neighborhood Homes Key Links Curriculum Vitae Organizations Computing and Computational Sciences Directorate Computer Science and Mathematics Division Mathematics in Computation Section Discrete Algorithms Group
