
About
Ghada Sokar is an Assistant Professor at Eindhoven University of Technology (TU/e) within the Department of Mathematics and Computer Science. Her research focuses on advancing machine learning techniques, particularly in continual learning, dynamic sparse training, and neural network optimization. She has contributed to over 17 research outputs since 2019, with notable work on algorithms to enhance model updates in neural networks and mitigate forgetting in continual learning scenarios.
Her expertise encompasses topics like deep reinforcement learning, sparsity optimization, and energy-efficient network architectures. She earned her PhD from TU/e in 2023 with a thesis titled 'Learning Continually Under Changing Data Distributions.'
Sokar has received the Best Paper Award at ALA 2022 for her collaborative work on sparse network techniques. Her research aligns with UN Sustainable Development Goals, emphasizing innovation in AI systems. While primarily affiliated with TU/e, her collaborative projects span international institutions, focusing on sparsity-driven machine learning applications.
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