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Anika Tabassum

Research Scientist

Contact

TABASSUMA@ORNL.GOV

All Publications

Counter Data Paucity through Adversarial Invariance Encoding: A Case Study on Modeling Battery Thermal Runaway
Historical Power Outages of the United States and the Social Vulnerability Index
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

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Curriculum Vitae

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Computing and Computational Sciences Directorate
Computer Science and Mathematics Division
Mathematics in Computation Section
Discrete Algorithms Group

Related News

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CCSD’s Lee wins best poster for storm risk study

Research Highlight

Li-ion Battery Material Phase Prediction through Hierarchical Curriculum Learning

News

URBAN-NET infrastructure modeling tool to be incorporated into EAGLE-I
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