Journal article · IEEE TNNLS · 2020
Continuous Model Adaptation Using Online Meta-Learning for Smart Grid Application
A framework for adaptive prediction under shifting training and real-time data patterns, developed for a smart-grid application.
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Research written for systems in motion.
Peer-reviewed work and doctoral research on how deep learning systems can adapt continuously as data and operating conditions change.
- IEEE TNNLS
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Selected recordAdaptive intelligence,
Adaptive intelligence,
formally developed.
Doctoral thesis · University of Illinois Chicago
Continuous Model Adaptation Using Online Meta-Learning
Doctoral research spanning online meta-optimization, deep neural networks, and model learning under real-time change.
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Verified academic identity: 0000-0001-8538-2164.
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Read how online meta-learning connects to modern adaptive AI systems.
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