Projects per year
Personal profile
Research Interests
Evolutionary Computation, Optimization, Data Science, Machine Learning, Neural Networks, Meta-heuristics, Robust optimization, multi-objective optimization, Feature selection.
Personal profile
Seyedali Mirjalili is an Associate Professor at Torrens University Center for Artificial Intelligence Research and Optimization and internationally recognized for his advances in nature-inspired Artificial Intelligence (AI) techniques. He is the author of more than 150 publications including five books, 100 journal articles, 20 conference papers, and 30 book chapters. With over 30,000 citations and H-index of 60, he is one of the most influential AI researchers in the world. From Google Scholar metrics, he is globally the most cited researcher in Optimization using AI techniques, which is his main area of expertise. He has been the keynote speaker of several international conferences and is serving as an associate editor of top AI journals including Neurocomputing, Applied Soft Computing, Advances in Engineering Software, Applied Intelligence, IEEE Access, and the Journal of Algorithms.
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Education/Academic qualification
Computer Science, PhD, Griffith University Queensland
Award Date: 1 Jan 2016
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Projects
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Research output
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A Comparative Study of Recent Multi-objective Metaheuristics for Solving Constrained Truss Optimisation Problems
Panagant, N., Pholdee, N., Bureerat, S., Yildiz, A. R. & Mirjalili, S., 2021, (Accepted/In press) In: Archives of Computational Methods in Engineering.Research output: Contribution to journal › Article › peer-review
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Advanced meta-heuristics, convolutional neural networks, and feature selectors for efficient COVID-19 X-ray chest image classification
El-Kenawy, E. S. M., Mirjalili, S., Ibrahim, A., Alrahmawy, M., El-Said, M., Zaki, R. M. & Eid, M. M., 2021, In: IEEE Access. 9, p. 36019-36037 19 p., 9360538.Research output: Contribution to journal › Article › peer-review
Open Access -
A hybrid Harris hawks-moth-flame optimization algorithm including fractional-order chaos maps and evolutionary population dynamics
Abd Elaziz, M., Yousri, D. & Mirjalili, S., Apr 2021, In: Advances in Engineering Software. 154, 102973.Research output: Contribution to journal › Article › peer-review
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An efficient approach for damage identification based on improved machine learning using PSO-SVM
Cuong-Le, T., Nghia-Nguyen, T., Khatir, S., Trong-Nguyen, P., Mirjalili, S. & Nguyen, K. D., 2021, (Accepted/In press) In: Engineering with Computers.Research output: Contribution to journal › Article › peer-review
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An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection
Abdel-Basset, M., Mohamed, R., Chakrabortty, R. K., Ryan, M. J. & Mirjalili, S., Mar 2021, In: Computers and Industrial Engineering. 153, 107078.Research output: Contribution to journal › Article › peer-review