Laith Abualigah

Laith AbualigahDr. Laith Abualigah is an Associate Professor at Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Jordan. He is also a distinguished researcher at the School of Computer Science, Universiti Sains Malaysia. His main researc interests focus on Arithmetic Optimization Algorithms (AOA), Bio-inspired Computing, Nature-inspired Computing, Swarm Intelligence, Artificial Intelligence, Meta-heuristic Modeling, as well as Optimization Algorithms, Evolutionary Computations, Information Retrieval, Text Clustering, Feature Selection, Combinatorial Problems, Optimization, Advanced Machine Learning, Big Data, and Natural Language Processing. Dr. Abualigah currently serves as Associate Editor of the Journal of Cluster Computing (Springer), the Journal of Soft Computing (Springer), and Journal of King Saud University - Computer and Information Sciences (Elsevier). Dr. Abualigah is the author of several books published by Springer, including Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering, Classification Applications with Deep Learning and Machine Learning Technologies, Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems, and Deep Learning Approaches for Spoken and Natural Language Processing. Read More Read Less

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Recent Advances in Structural Health Monitoring and Engineering Structures37 %
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Classification Applications with Deep Learning and Machine Learning Technologies37 %
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Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems37 %
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Classification Applications with Deep Learning and Machine Learning Technologies37 %
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Deep Learning Approaches for Spoken and Natural Language Processing37 %
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Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems37 %
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Deep Learning Approaches for Spoken and Natural Language Processing37 %
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Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering37 %
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Big Data Analytics Using Artificial Intelligence18 % NR
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Evolutionary Process for Engineering Optimization26 % NR
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Metaheuristic Optimization Algorithms12 % NR
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Classification Applications with Deep Learning and Machine Learning TechnologiesNR
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Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering3 % NR
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