Admission Inquiry

Prof. Seyedali Mirjalili

  • Adjunct Professor
  • Experience

    10+ years

  • Qualifications

    • Ph. D. Computer Science (Artificial Intelligence)

      01/04/2012 – 2/12/2016 (Griffith University, Brisbane, Australia)
      Thesis Title: Confidence-based Robust Multi-Objective Optimisation of Engineering Design Problems

    • M. Sc. Computer Science (Artificial Intelligence) 

      01/06/2009 – 01/08/2011 (Universiti Teknlologi Malaysia)
      Thesis Title: Hybrid Particle Swarm Optimization and Gravitational Search Algorithm for Multilayer Perceptron Learning 

    • B. Sc. Computer Engineering (Software)

      01/09/2003 – 01/07/2008 (Yazd University, Yazd, Iran)

      Thesis Title: 3D simulation of Autonomous Underwater Glider behaviour TEACHING
  • Ph.D

    Thesis Supervised

  • Awarded/ Completed-


  • Postgraduate

    Thesis Supervised

  • Awarded/ Completed-



  • 01S. Mirjalili, H. Faris, I. Aljarah “Evolutionary Machine Learning Techniques” Algorithms for Intelligent Systems, Springer, in-press
  • 02S. Mirjalili, “Nature-inspired Optimizers: Theories, Literature Reviews, and Applications” Studies in Computational Intelligence book series, Springer, in-press
  • 03S. Mirjalili, J. S. Dong, “Multi-Objective Optimization using Artificial Intelligence Techniques”, SpringerBriefs in Computational Intelligence, Springer, in-press
  • 04S. Saremi, S. Mirjalili, Optimization Algorithms for Hand Posture Estimation, Algorithms for Intelligent Systems, Springer, in-press
  • 05S. Mirjalili, “Evolutionary Algorithms and Neural Networks: Theory and Applications”, Vol. 780, Studies in Computational Intelligence book series, Springer, 2018

Journal Articles:



  • 01K. Muhammad, S. Khan, N. Kumar, J. Del Ser, S. Mirjalili, (2020). Vision-based personalized Wireless Capsule Endoscopy for smart healthcare: Taxonomy, literature review, opportunities and challenges. Future Generation Computer Systems, 2020, [Q1, IF 4.6].
  • 02I. Aljarah, M. Habib, H. Faris, N. Al-Madi, A. A. Heidari, M. Mafarja, M. Abd Elaziz, S. Mirjalili, (2020). A Dynamic Locality Multi-Objective Salp Swarm Algorithm for Feature Selection. Computers & Industrial Engineering, 106628, 2019, [Q1, IF 3.5
  • 03Q. Al-Tashi, S. J. Abdulkadir, H. M. Rais, S. Mirjalili, H. Alhussian, M. G. Ragab, A. Alqushaibi, (2020). Binary MultiObjective Grey Wolf Optimizer for Feature Selection in Classification. IEEE Access, 8, 106247-106263, 2020, [Q1, IF 3.5].
  • 04Q. Al-Tashi, A. J. Abdulkadir, H. M. Rais, S. Mirjalili, H. Alhussian, (2020). Approaches to Multi-Objective Feature Selection: A Systematic Literature Review. IEEE Access, 2020, [Q1, IF 3.5].
  • 05D. Yousri, S. Mirjalili, (2020). Fractional-order cuckoo search algorithm for parameter identification of the fractional-order chaotic, chaotic with noise and hyper-chaotic financial systems. Engineering Applications of Artificial Intelligence, 92, 103662, 2020, [Q1, IF 2.8]
  • 06T. A. A. Ali, Z. Xiao, S. Mirjalili, V. Havyarimana, V. (2020). Efficient design of wideband digital fractional order differentiators and integrators using multi-verse optimizer. Applied Soft Computing, 106340, 2020, [Q1, IF 3.9].
  • 07R. Guha, M. Ghosh, A. Chakrabarti, R. Sarkar, S. Mirjalili, (2020). Introducing clustering based population in Binary Gravitational Search Algorithm for Feature Selection. Applied Soft Computing, 106341, 2020, [Q1, IF 3.9].
  • 08S. M. J. Jalali, S. Ahmadian, A. Khosravi, S. Mirjalili, M. R. Mahmoudi, S. Nahavandi, (2020). Neuroevolution-based Autonomous Robot Navigation: A Comparative Study. Cognitive Systems Research, 2020, [Q2, IF 1.9]
  • 09D. Mokeddem, S. Mirjalili, (2020). Improved Whale Optimization Algorithm applied to design PID plus second-order derivative controller for automatic voltage regulator system. Journal of the Chinese Institute of Engineers, 1-12, 2020, [Q2, IF 0.6]
  • 10D. Yousri, M. Abd Elaziz, S. Mirjalili, (2020). Fractional-order calculus-based flower pollination algorithm with local search for global optimization and image segmentation. Knowledge-Based Systems, 105889, 2020, [Q1, IF 4.5].
  • 11L. Abualigah, M. Shehab, M. Alshinwan, S. Mirjalili, M. Abd Elaziz, (2020). Ant Lion Optimizer: A Comprehensive Survey of Its Variants and Applications. Arch. Comput. Methods Eng, 2020, [Q1, IF 6.7].
  • 12S. Li, H. Chen, M. Wang, A. A. Heidari, S. Mirjalili, (2020). Slime mould algorithm: A new method for stochastic optimization. Future Generation Computer Systems, 2020, [Q1, IF 4.6].
  • 13S. Gupta, K. Deep, S. Mirjalili, J. H. Kim, (2020). A Modified Sine Cosine Algorithm with Novel Transition Parameter and Mutation Operator for Global Optimization. Expert Systems with Applications, 113395, 2020, [Q1, IF 3.9].
  • 14S. Dhargupta, M. Ghosh, S. Mirjalili, R. Sarkar, (2020). Selective opposition based grey wolf optimization. Expert Systems with Applications, 113389, 2020, [Q1, IF 3.9].
  • 15A. Faramarzi, A., Heidarinejad, S. Mirjalili, A. H. Gandomi, (2020). Marine predators algorithm: A nature-inspired Metaheuristic. Expert Systems with Applications, 113377, 2020, [Q1, IF 3.9].
  • 16H. Faris, A. A. Heidari, A. Z Ala’M, M. Mafarja, I. Aljarah, M. Eshtay, S. Mirjalili, (2020). Time-varying hierarchical chains of salps with random weight networks for feature selection. Expert Systems with Applications, 140, 112898, 2020, [Q1, IF 3.9]
  • 17Q. V. Pham, S. Mirjalili, N. Kumar, M., Alazab, W. J. Hwang, (2020). Whale Optimization Algorithm with Applications to Resource Allocation in Wireless Networks. IEEE Transactions on Vehicular Technology, 2020, [Q1, IF 5.3]
  • 18H. M. Ridha, C. Gomes, H. Hizam, S. Mirjalili, (2020). Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system. Renewable Energy, 2020, [Q1, IF 5.4]
  • 19A. Faramarzi, M. Heidarinejad, B. Stephens, S. Mirjalili, (2020). Equilibrium optimizer: A novel optimization algorithm. Knowledge-Based Systems, 191, 105190, 2020, [Q1, IF 4.5].
  • 20H. Abderazek, A. R. Yildiz, S. Mirjalili, (2020). Comparison of recent optimization algorithms for design optimization of a cam-follower mechanism. Knowledge-Based Systems, 191, 105237, 2020, [Q1, IF 4.5].
  • 21M. Tubishat, N. Idris, L. Shuib, M. A. Abushariah, S. Mirjalili, (2020). Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection. Expert Systems with Applications, 145, 113122, 2020, [Q1, IF 3.9]
  • 22A. Saxena, R. Kumar, S. Mirjalili, (2020). A harmonic estimator design with evolutionary operators equipped grey wolf optimizer. Expert Systems with Applications, 145, 113125, 2020, [Q1, IF 3.9]


  • 01A. A. Heidari, S. Mirjalili, H. Faris, I. Aljarah, M. Mafarja, H. Chen, (2019). Harris Hawks optimization: Algorithm and applications. Future Generation Computer Systems, 97, 849-872, 2019, [Q1, IF 4.6].
  • 02A. M. Elaziz, S. Mirjalili (2019). A hyper-heuristic for improving the initial population of whale optimization algorithm. Knowledge-Based Systems, 172, 42-63, 2019, [Q1, IF 4.5].
  • 03H. Faris, S. Mirjalili, I. Aljarah, “Automatic selection of hidden neurons and weights in neural networks using grey wolf optimizer based on a hybrid encoding scheme”, International Journal of Machine Learning and Cybernetics, 1-20, 2019, [Q1, IF 2.6].
  • 04M. Taradeh, M. Mafarja, A. A. Heidari, H. Faris, I. Aljarah, S. Mirjalili, H. Fujita, “An evolutionary gravitational searchbased feature selection”, Information Sciences, 497, 219-239. [Q1, IF 4.8]
  • 05M Abdel-Basset, D El-Shahat, H Faris, S Mirjalili, A binary multi-verse optimizer for 0-1 multidimensional knapsack problems with application in interactive multimedia systems, Computers & Industrial Engineering, 132, 187-206, 2019, [Q1,IF 3.5 ]
  • 06AM Fathollahi-Fard, M Hajiaghaei-Keshteli, S Mirjalili, A set of efficient heuristics for a home healthcare problem, Neural Computing and Applications, 1-21, [Q1, IF 4.2]
  • 07I. Aljarah, H. Faris, S. Mirjalili, N. Al-Madi, A. Sheta, M. Mafarja, “Evolving neural networks using bird swarm algorithm for data classification and regression applications”, Cluster Computing, 1-29, 2019, [Q1, IF 1.6].
  • 08Q. Al-Tashi, S. J. Abdulkadir, H. M. Rais, S. Mirjalili, H. Alhussian, “Binary Optimization Using Hybrid Grey Wolf Optimization for Feature Selection”. IEEE Access, in press, 2019, [Q1, IF 3.5].
  • 09M. Mafarja, I. Aljarah, H. Faris, A. I. Hammouri, A. Z. Ala’M, S. Mirjalili, “Binary grasshopper optimisation algorithm approaches for feature selection problems”. Expert Systems with Applications, 117, 267-286, 2019, [Q1, IF 3.9]
  • 10I. Aljarah, M. Mafarja, A. A. Heidari, H. Faris, S. Mirjalili, “Clustering analysis using a novel locality-informed grey wolfinspired clustering approach”. Knowledge and Information Systems, 1-33, 2019, [Q1, IF 2.2]
  • 11N. Al-Madi, H. Faris, S. Mirjalili, “Binary multi-verse optimization algorithm for global optimization and discrete problems.” International Journal of Machine Learning and Cybernetics, 1-21, 2019, [Q1, IF 2.6]
  • 12A. A. Heidari, I. Aljarah, H. Faris, H. Chen, J. Luo, S. Mirjalili, “An enhanced associative learning-based exploratory whale optimizer for global optimization”, Neural Computing and Applications, 1-27, 2019, [Q1, IF 4.2]
  • 13M. A. Al-Betar, I. Aljarah, I., M. A. Awadallah, H. Faris, S. Mirjalili, “Adaptive β-hill climbing for optimization”. Soft Computing, 1-24, [Q2, IF 2.3]
  • 14B. Merikhi, S. M. Mirjalili, M. Zoghi, S. Z. Mirjalili, S. Mirjalili, “Radiation pattern design of photonic crystal LED optimized by using multi-objective grey wolf optimizer”. Photonic Network Communications, 1-10, 2019, [Q1, IF 6.3]
  • 15R. Abbassi, A. Abbassi, A. A. Heidari, S. Mirjalili, “An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models”. Energy Conversion and Management, 179, 362-372, 2019, 1-24, [Q3, IF 1.2]
  • 16I. Aljarah, M. Mafarja, A. A. Heidari, H. Faris, Y. Zhang, S. Mirjalili, “Asynchronous accelerating multi-leader salp chains for feature selection”. Applied Soft Computing, 71, 964-979, 2019, [Q1, IF 3.9]


  • 01S. Mirjalili, A. Lewis, J. S. Dong, “Confidence-based robust optimisation using multi-objective meta-heuristics”. Swarm and Evolutionary Computation, accepted 3/2018. [Q1, IF 3.8]
  • 02M. Abdel-Basset, G. Manogaran, G., D. El-Shahat, S. Mirjalili, “Integrating the whale algorithm with Tabu search for quadratic assignment problem: A new approach for locating hospital departments”. Applied Soft Computing, 73, 530-546, 2018,  [Q1, IF 3.9]
  • 03A. A. Heidari, H. Faris? I. Aljarah? S. Mirjalili, “An Efficient Hybrid Multilayer Perceptron Neural Network with Grasshopper Optimization”, Soft Computing, accepted 07/2018, [Q2, IF 2.3]
  • 04M. Mafarja, S. Mirjalili, “Hybrid binary ant lion optimizer with rough set and approximate entropy reducts for feature selection”, Soft Computing, accepted 6/2018, [Q2, IF 2.3]
  • 05M. Mafarja, I. Aljarah, A. A. Heidari, H. Faris, P. Fournier-Viger, X. Li, S. Mirjalili, “Binary Dragonfly Optimization for Feature Selection using Time-Varying Transfer functions”, Knowledge-based Systems, accepted 07/2018, [Q1, IF 4.5]
  • 06M. Abdel-Basset, G. Manogaran, L. Abdel-Fatah, S. Mirjalili, “An improved nature inspired meta-heuristic algorithm for 1D bin packing problems”, Personal and Ubiquitous Computing, accepted 3/2018. [Q1, IF 1.9
  • 07G. G. Tejani, V. J. Savsani, V. K. Patel, S. Mirjalili, “An improved heat transfer search algorithm for unconstrained optimization problems”, Journal of Computational Design and Engineering, accepted 2/2018, [Q2]
  • 08H. Al Nsour, M. Alweshah, A. I. Hammouri, H. Al Ofeishat, S. Mirjalili, “A Hybrid Grey Wolf Optimiser Algorithm for Solving Time Series Classification Problems”, Journal of Intelligent System, accepted 6/2018
  • 09H. Mehne, S. Mirjalili. “A parallel numerical method for solving optimal control problems based on whale optimization algorithm.”, Knowledge-Based Systems, 114-123 (151), 2018. [Q1, IF 4.5]
  • 10H. Faris, M. Mafarja, A. Heidari, I. Aljarah, A. Ala’M, S. Mirjalili, and H. Fujita. “An efficient binary Salp Swarm Algorithm with crossover scheme for feature selection problems”, Knowledge-Based Systems. 43-67 (154), 2018. [Q1, IF 4.5]
  • 11S. Shukri, H. Faris, I. Aljarah, S. Mirjalili, A. Abraham, “Evolutionary static and dynamic clustering algorithms based on multi-verse optimizer”, Engineering Applications of Artificial Intelligence, 54-66 (72), 2018. [Q1, IF 2.8]
  • 12A. M. Fathollahi-Fard, M. Hajiaghaei-Keshteli, and S. Mirjalili, "Multi-objective stochastic closed-loop supply chain network design with social considerations." Applied Soft Computing, 505-525 (71), 2018, [Q1, IF 3.9]
  • 13A. M. Fathollahi-Fard, M. Hajiaghaei-Keshteli, S. Mirjalili, “Hybrid optimizers to solve a tri-level programming model for a tire closed-loop supply chain network design problem”. Applied Soft Computing, 701-722 (70), 2018, [Q1, IF 3.9]
  • 14A. S. Sadiq, S. Khan, K. Z. Ghafoor, M. Guizani, S. Mirjalili, “Transmission power adaption scheme for improving IoV awareness exploiting: evaluation weighted matrix based on piggybacked information”. Computer Networks, 147-159 (137),2018. [Q1, IF 2.5]
  • 15S. Saremi, S. Mirjalili, A. Lewis, A. W. C. Liew, J. S. Dong, “Enhanced Multi-Objective Particle Swarm Optimisation for Estimating Hand Postures”, Knowledge-Based Systems, 175-195 (158), 2018, [Q1, IF 4.5]
  • 16A. S. Sadiq, B. Alkazemi, S. Mirjalili, N. Ahmed, S. Khan, I. Ali, A. K. Pathan, and K. Z. Ghafoor. “An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs”, IEEE Access, 29041-29053 (6), 2018. [Q1, IF 3.2]
  • 17M. Abdel-Basset, D. El-Shahat, I. El-henawy, S. Mirjalili, “A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem”, Future Generation Computer Systems, 129-145 (2018), [Q1, IF 3.9]
  • 18S. Saremi, S. Mirjalili, A. Lewis, “Vision-based Hand Posture Estimation using a New Hand Model Made of Simple Components”, Optik - International Journal for Light and Electron Optics, 15-24 (167), 2018 [Q2, IF 0.7]
  • 19I. Aljarah, A. Ala’M, H. Faris, M. A Hassonah, S. Mirjalili, H. Saadeh, “Simultaneous Feature Selection and Support Vector Machine Optimization Using the Grasshopper Optimization Algorithm”, Cognitive Computation, 478-495 (10), 2018 [Q1, IF 3.4]


  • 01S. Mirjalili, A. H. Gandomi, S. Z. Mirjalili, S. Saremi, H. Faris, S. M. Mirjalili, “Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems”, Advances in Engineering Software, in-press, 163-191 (114), 2017 [Q1, IF 3.0]
  • 02S. Mirjalili, P. Jangir, S. Z. Mirjalili, S. Saremi, I. N. Trivedi, “Optimization of problems with multiple objectives using the multi-verse optimization algorithm”, Knowledge-based Systems, 2017, in-press, 50-71 (134), 2017 [Q1, IF 4.5]
  • 03M. Mafarja, I. Aljarah, A. Heidari, A. I Hammouri, H. Faris, A. Ala’M, S. Mirjalili, “Evolutionary Population Dynamics and Grasshopper Optimization Approaches for Feature Selection Problems”, Knowledge-based Systems, 2017, 25-45 (145), 2017 [Q1, IF 4.5]
  • 04G. G. Tejani, V. J. Savsani, V. K. Patel, S. Mirjalili, “Truss optimization with natural frequency bounds using improved symbiotic organisms search”, Knowledge-based Systems, 2018, 162-178 (143), 2017 [Q1, IF 4.5]
  • 05S. M. Mirjalili, B. Merikhi, S. Z. Mirjalili, M. Zoghi, S. Mirjalili, “Multi-objective versus single-objective optimization frameworks for designing photonic crystal filters”, Applied Optics, 56(34), 94444-9451, 2017. [Q2, IF 1.6
  • 06M. Mafarja, S. Mirjalili. “Whale Optimization Approaches for Wrapper Feature Selection” Applied Soft Computing, 2017, 441-453 (62). 2017 [Q1, IF 3.9]
  • 07H. Faris, I. Aljarah, M. A. Al-Betar, S. Mirjalili, “Grey wolf optimizer: a review of recent variants and applications”, Neural Computing and Applications, 413–435 (30), 2017. [Q1, IF 4.2]
  • 08S. Z. Mirjalili, S. Mirjalili, S. Saremi, H. Fatis, H. Aljarah, “Grasshopper optimization algorithm for multi-objective optimization problems”, Applied Intelligence, 805–820 (40), 2017. [Q3, IF 1.9]
  • 09S. Mirjalili, A. H. Gandomi, “Chaotic gravitational constants for the gravitational search algorithm”, Applied Soft Computing, 2017, 53 (407-419). [Q1, IF 3.9]
  • 10S. Mirjalili, P. Jangir, S. Saremi, “Multi-objective Ant Lion Optimizer: A multi-objective optimization algorithm for solving engineering problems”, Applied Intelligence, 2017, 46(1), 79–95. [Q3, IF 1.9]
  • 11S. Saremi, S. Mirjalili, A. Lewis, “Grasshopper Optimisation Algorithm: Theory and Application”, Advances in Engineering Software, 30-47 (105) 2017, [Q1, IF 3.0]
  • 12M. M. Mafarja, S. Mirjalili, “Hybrid whale optimization algorithm with simulated annealing for feature selection”, Neurocomputing, 302-312 (18), 2017. [Q1, IF 3.3]
  • 13H. Faris, I. Aljarah, S. Mirjalili, “Improved monarch butterfly optimization for unconstrained global search and neural network training”, Applied Intelligence, 2017, in-press. [Q3, IF 1.9]
  • 14H. Faris, M. A. Hassonah, A. Z. Ala’M, S. Mirjalili, I. Aljarah, “A multi-verse optimizer approach for feature selection and optimizing SVM parameters based on a robust system architecture”, Neural Computing and Applications, 2017, in-press, accepted 12/2017. [Q1, IF4.2]
  • 15M. A. T. Mohammed, A. S. Sadiq, R. A. Arshah, F. Ernawan, S. Mirjalili, “Soft Set Decision/Forecasting System Based on Hybrid Parameter Reduction Algorithm”. Journal of Telecommunication, Electronic and Computer Engineering, 9(2-7), 143-148.
  • 16D. Das, A. Sadiq, S. Mirjalili, A. Noravizah, “Hybrid Clustering-GWO-NARX neural network technique in predicting stock price”, Journal of Physics: Conference Series, 2017, 892(1), 12–25


  • 01S. Mirjalili, A. Lewis, “The Whale Optimization Algorithm”, Advances in Engineering Software, 2016, 95, 51-67. [Q1, IF 3.0]
  • 02S. Mirjalili, “Moth-Flame Optimization Algorithm: A Novel Nature-inspired Heuristic Paradigm”, Knowledge-Based Systems, 2016, 89, 228-249.[Q1, IF 4.5]
  • 03S. Mirjalili, “Dragonfly Algorithm: A New Meta-heuristic Optimization Technique for Solving Single-objective, Discrete, and Multi-objective Problems”, Neural Computing and Applications, 2016, 27 (4), 1053-1073. [Q1, IF 4.1]
  • 04S. Mirjalili, A. Lewis, “Obstacles and difficulties for robust benchmark problems: A novel penalty-based robust optimisation method”, Information Sciences, 2016, 328, 485–509. [Q1, IF 4.8]
  • 05S. Mirjalili, S. Saremi, S. M. Mirjalili, L. Coelho, “Multi-objective grey wolf optimizer: A novel algorithm for multi-criterion optimization”, Expert Systems with Applications, 2016, 47, 106-119. [Q1, IF 3.9]
  • 06S. Mirjalili, “SCA: A Sine Cosine Algorithm for Solving Optimization Problems”, Knowledge-based Systems, 2016, 96, 120-133. [Q1, IF 4.5]
  • 07S. Mirjalili, S. M. Mirjalili, A. Hatamlou, “Multi-Verse Optimizer: a nature-inspired algorithm for global optimization”, Neural Computing and Applications, 2016, 27 (2), 495-513. [Q1, IF 4.2]
  • 08G. Wang, H. E. Che, S. Mirjalili, “Three-dimensional path planning for UCAV using an improved bat algorithm”, Aerospace Science and Technology, 2016, 49, 231-238, 2016, [Q1, IF 2.0]
  • 09I. Aljarah, H. Faris, S. Mirjalili, “Optimizing Connection Weights in Neural Networks using the Whale Optimization Algorithm”, Soft Computing, 1-15 (22) 2016, [Q2, IF 3.5]
  • 10I. Aljarah, H. Faris, S. Mirjalili, N. Al-Madi, “Training radial basis function networks using biogeography-based optimizer”, Neural Computing and Applications, 529–553 (29) 2016, [Q1, IF 4.2]
  • 11H. Faris, I. Aljarah, S. Mirjalili, Training feedforward neural networks using multi-verse optimizer for binary classification problems, Applied Intelligence, 2016, 45(2), 322–332. [Q3, IF 1.9]
  • 12H. Faris, I. Aljarah, N. Al-Madi, S. Mirjalili, Optimizing the Learning Process of Feedforward Neural Networks Using Lightning Search Algorithm, International Journal on Artificial Intelligence Tools, 2016, 25(06), 1-32, [Q4, IF 0.6]


  • 01S. Mirjalili, A. Lewis, Confidence measure: “A novel metric for robust meta-heuristic optimisation algorithms”, Information Sciences, 2015, 317, 114–142. [Q1, IF 4.8]
  • 02S. Mirjalili, A. Lewis, “Novel frameworks for creating robust multi-objective benchmark problems”, Information Sciences, 2015, 300, 158–192. [Q1, IF 4.8]
  • 03S. Mirjalili, A. Lewis, “Hindrances for robust multi-objective test problems”, Applied Soft Computing, 2015, 35, 333-348, [Q1, IF 3.9]
  • 04S. Mirjalili, “How effective is the Grey Wolf optimizer in training multi-layer perceptrons”, Applied Intelligence, 2015, 43, 150-161. [Q3, IF 1.9]
  • 05S. Mirjalili, “Shifted robust multi-objective test problems”, Structural and Multidisciplinary Optimization, 2015, 52, 217-226, [Q1, IF 2.3]
  • 06S. Mirjalili, “The Ant Lion Optimizer”, Advances in Engineering Software, 2015, 83, 80-98. [Q1, IF 3.0]
  • 07S. M. Mirjalili, S. Mirjalili, S. Z. Mirjalili, “How to design photonic crystal LEDs with artificial intelligence techniques”, 2015, Electronics Letters, 51, 1437-1439. [Q3, IF 0.9]
  • 08B. Javidy, A. Hatamlou. S. Mirjalili, “Ions motion algorithm for solving optimization problems”, Applied Soft Computing,2015, 32, 72-79, [Q1, IF 3.9]


  • 01S. Mirjalili, S. M. Mirjalili, A. Lewis, “Let A Biogeography-Based Optimizer Train Your Multi-Layer Perceptron”, Information Sciences, 2014, 269, 188–209. [Q1, IF 4.8]
  • 02S. Mirjalili, S. M. Mirjalili, A. Lewis, “Grey Wolf Optimizer”, 2014, Advances in Engineering Software, 69, P. 46-61,[Q1, IF 3.0, Cited 1200+]
  • 03S. Mirjalili, A. Lewis, “Novel Performance Metrics for Robust Multi-objective Optimization Algorithms”, Swarm and Evolutionary Computation, 2014, 21, 1-23, 2014. [Q1, IF 3.8]
  • 04S. Mirjalili, S. M. Mirjalili, X. Yang, “Binary Bat Algorithm”, Neural Computing and Applications, 2014, 25, 663-681. [Q1, IF 4.2]
  • 05S. Mirjalili, G.-G. Wang, L. S. Coelho, “Binary optimization using hybrid particle swarm optimization and gravitational search algorithm” Neural Computing and Applications, 2014, 25, 1423-1435. [Q1, IF 4.2]
  • 06S. Mirjalili, A. Lewis, “Adaptive gbest-guided gravitational search algorithm”, Neural Computing and Applications, 2014, 25, 1569-1584. [Q1, IF 4.2]
  • 07S. M. Mirjalili, S. Mirjalili, A. Lewis, “A novel Multi-objective Optimization Framework for designing photonic crystal waveguides”, Photonics Technology Letters, 2014, 26(2), 146-149. [Q2, IF 2.3]
  • 08S. M. Mirjalili, S. Mirjalili, “Oval-shaped-hole photonic crystal waveguide Design by MoMIR framework”, Photonics Technology Letters, 2014, 26, 2446-2449. [Q2, IF 2.3]
  • 09S. M. Mirjalili, S. Mirjalili, A. Lewis, K. Abedi, “A Tri-objective Particle Swarm Optimizer for Designing line defect Photonic Crystal Waveguides”, Photonics and Nanostructures - Fundamentals and Applications, 2014, 12(2), 152-163. [Q3, IF 1.7]
  • 10S. Saremi, S. Mirjalili, A. Lewis, “Biogeography-based optimisation with chaos”, Neural Computing and Applications, 2014, 25, 1077-1097. [Q2, IF 4.2]
  • 11S. Saremi, S. Mirjalili, A. Lewis, “How Important Is A Transfer Function in Discrete Heuristic Algorithms”, Neural Computing and Application, 2014, 26, 625-640, [Q1, IF 4.2]
  • 12A. S. Sadiq, K. A. Bakar, K. Z. Ghafoor, J. Lloret, S. Mirjalili, “A smart handover prediction system based on curve fitting model for Fast Mobile IPv6 in wireless networks”, International Journal of Communication Systems, 2014, 27, 969-990.[Q3, IF 1.0]


  • 01S. Mirjalili, T. Rawlings, J. Hettenhausen, A, Lewis, “A comparison of multi-objective optimisation metaheuristics on the 2D airfoil design problem” ANZIAM journal, 2013, 54, C345-C360. [Q2, IF 1.1]
  • 02S. Mirjalili, A. Lewis, A. S. Sadiq, “Autonomous Particles Groups for Particle Swarm Optimization, The Arabian Journal for Science and Engineering”, 2013, 39(6), 4683-4697. [Q3, IF 0.8]
  • 03S. M. Mirjalili, K. Abedi, S. Mirjalili, “Optical Buffer Performance Enhancement Using Particle Swarm Optimization in RingShape-Hole Photonic Crystal Waveguide”, Optik - International Journal for Light and Electron Optics, 2013,124(123),5989-5993. [Q4, IF 0.8]
  • 04S. Mirjalili, A. Lewis, “S-shaped versus V-shaped transfer functions for binary Particle Swarm Optimization”, Swarm and Evolutionary Computation, 2013, 9, 1-14. [Q1, IF 3.8]
  • 05S. Saremi, S. Mirjalili, “Integrating Chaos to Biogeography-Based Optimization Algorithm”, International Journal of Computer and Communication Engineering, 2013, 2(6), 655-658.


  • 01S. Mirjalili, S. Z. Mohd Hashim, H. Moradian Sardroudi, “Training feedforward neural networks using hybrid particle swarm optimization and gravitational search algorithm”, Applied Mathematics and Computation, 2012, 218, 11125-11137. [Q1, IF 1.7]
  • 02S. Mirjalili, S. Z. Mohd Hashim, “BMOA: Binary Magnetic Optimization Algorithm”, International Journal of Machine Learning and Computing, 2012, 2(3), 204-208

Conference Papers: 


  • 01S. Mirjalili, A. Lewis “Benchmark Function Generators for Single-Objective Robust Optimisation Algorithms”. In Decision Science in Action, 13-29, 2019.


  • 01S. Saremi, S. Mirjalili, A. Lewis, A. W. Liew, “Let’s consider two objectives when estimating hand postures”, 30th Australian Joint Conference on Artificial Intelligence, 2017, 119-130
  • 02M. Majdi, Mafarja, M. Eleyan, D. Abdullah, S. Mirjalili, “S-Shaped vs. V-Shaped Transfer Functions for Ant Lion Optimization Algorithm in Feature Selection Problem.” Proceedings of the International Conference on Future Networks and Distributed Systems. ACM, 2017


  • 01S. Saremi, S. Mirjalili, A. Lewis, “How effective are meta-heuristics for recognizing hand gestures”, IEEE congress on Evolutionary Computation (CEC), 2016, 104-111
  • 02H. Faris, I. Aljarah, S. Mirjalili, P. A. Castillo, J. J. Merelo, “EvoloPy: An Open-source Nature-inspired Optimization Framework in Python”, 8th International Joint Conference on Computational Intelligencel, 2016, 171 – 177 


  • 01S. Mirjalili, A. Lewis, “A Reliable and Computationally Cheap Approach for Finding Robust Optimal Solutions”, Genetic and Evolutionary Computation Conference (GECCO), 2015, 1439-1440.
  • 02S. Mirjalili, A. Lewis, “Multi-objective Optimization of Marine Propellers”, Procedia Computer Science, 2015, 51, 22472256. 


  • 01S. Saremi, S. M. Mirjalili, S. Mirjalili, “Unit cell topology optimization of line defect photonic crystal waveguide”, Procedia Technology, 2014, 174-179. 
  • 02S. Saremi, S. M. Mirjalili, S. Mirjalili, “Chaotic krill herd optimization algorithm”, Procedia Technology, 2014, 12, 180-185. 


  • 01S. M. Mirjalili, K. Abedi, S. Mirjalili, “Slow light Properties Optimization in line defect photonic crystal waveguide using Particle Swarm Optimization” ICOP, vol. 1, 2013. [in Farsi]
  • 02V. Abedifar, M. Eshghi, S. Mirjalili, and S. M. Mirjalili, “An Optimized Virtual Network Mapping Using PSO in Cloud Computing”, ICEE, 2013


  • 01T. Rawlins, A. Lewis, J. Hettenhausen, S. Mirjalili, “Interactive k-means clustering for investigation of optimisation solution data”, 16th Biennial Computational Techniques and Applications Conference, 2012
  • 02S. M. Mirjalili, K. Abedi, S. Mirjalili, “Light property and optical buffer performance enhancement using Particle Swarm Optimization in Oblique Ring-Shape-Hole Photonic Crystal Waveguide”, Photonics Global Conference (PGC), 2012
  • 03J. Hettenhausen, A. Lewis, T. Kipouros, T. Rawlins, S. Mirjalili, “Interactive Multi-Objective Particle Swarm Optimisation for Computational Fluid Dynamics Applications”, 16th Biennial Computational Techniques and Applications Conference, 2012
  • 04I. Muzafar, M. Zakaria, A. Abidin, J.  Juliani, A. Lit, S. Mirjalili, N. Nordin, M. Saaid. "Magnetic optimization algorithm approach for travelling salesman problem.", World Academy of Science, Engineering and Technology, 62 (2012): 13931397. 


  • 01S. Mirjalili, A. Safa Sadiq, “Magnetic Optimization Algorithm for Training Multi Layer Perceptron”, published in IEEE International Conference on Industrial and Intelligent Information (ICIII 2011), Indonesia, 2011, 2, 42-46.
  • 02S. Mirjalili, S.Z. Mohd Hashim, G. Taherzadeh, S.Z. Mirjalili, S. Amini, “A Study of Different Transfer Functions for Binary Version of Particle Swarm Optimization”, International Conference on Genetic and Evolutionary Methods (GEM 2011), Las Vegas, USA, 2011, 169-174. 
  • 03G. Taherzadeh, R. Karimi, A. Ghobadi, P. Vahdani, S. Mirjalili, “Categorizing Global and local features of On-line signature verification using DTW and Fuzzy logic”, International Conference on Genetic and Evolutionary Methods (GEM 2011), 2011.


  • 01S. Mirjalili, S.Z. Mohd Hashim, “A New Hybrid PSOGSA Algorithm for Function Optimization”, IEEE International Conference on Computer and Information Application (ICCIA 2010), China, 2010, 374-377. 

Book Chapters:

  • 01S. Mirjalili, A. H. Gandomi, “Gravitational Search Algorithm with Chaos”, in Handbook of Neural Computation, Elsevier, 2017, 1-32.  
  • 02H. Faris, I. Aljaraha, S. Mirjalili, “Evolving Radial Basis Function Networks using Moth-Flame Optimizer” in Handbook of Neural Computation, Elsevier, 2017.
  • 03A. S. Sadiq, H. Faris, A. Z. Ala'M, S. Mirjalili, K. Z. Ghafoor. “Fraud Detection Model Based on Multi-Verse Features Extraction Approach for Smart City Applications”. In Smart Cities Cybersecurity and Privacy, Elsevier, 241-251, 2019
  • 01Assessor and panel member, Social sciences and humanities, Czech Science Foundation ?         Assessor, Applied and Engineering Sciences (AES), Dutch Research Council (NWO)
  • 02Senior Member of IEEE
  • 03Reviewer in over 100 journals with 1500+ completed assignments and 100+ editorial records
  • 04Visiting researcher in National University of Singapore, Monash Malaysia, University Technology Petronas, University Technology Malaysia, and National Taiwan University 
  • 05Attendee in 20 research-related professional development sessions at Griffith University  
  • 06Attendee in two leadership workshops, Torrens University Australia, 2019 and 2020 
  • 07Conference committee of 10 international (e.g. CEC, WCCI, and ANTS) 
  • 08Special session committee and chair in CEC, WCCI, and SSCI conferences
  • 09Chair of paper presentation sessions in two international conferences, 2017 and 2018
  • 10Course Advisory Committee, Torrens University Australia, Leaders Institute, and Griffith University  
  • 11Member of Australian Computer Science 
  • 12Research instructor in Udemy with 6,000+ students
  • 13Contributor in Mathworks website with over 60 algorithms and 2,000+ downloads per month
  • 14Two invited seminars National Taiwan University of Science and Technology 2020, (sponsored) 
  • 15One invited keynote speech in Prince Sultan University, Saudi Arabia, 2020, (sponsored)
  • 16One invited talk, University Technology Petronas, Malaysia, 2019, (sponsored)
  • 17Two invited talks, National University of Singapore, 2019, (sponsored)
  • 18One invited talk, University of Queensland, 2018
  • 19One invited talk, Monash Malaysia, 2018
  • 20Three invited keynote speeches in India: IIT Roorkee in 2016, Vellore Institute of Technology in 2018, and IIT Indore in 2020  (sponsored)


  • 2020: Internal grant, COVID-19 Pan Uni project, Torrens University Australia: $25,000 (AUD)
  • 2019: Internal grant, Business faculty, Torrens University Australia: $10,000 (AUD)
  • 2016: Early Career Researcher Seed Grant – IIIS, Griffith University - $4,000 (AUD)
  • 2019: Reflective Intelligence Amplification: Tackling Wicked Problems Through Dynamic Search Space Exploration, AI Singapore, administered by NUS in Singapore, $100,000 (SGD)
  • 2016: An efficient flood forecasting approach based on Whale Optimisation Algorithm, administered by University Malaysia Pahang (UMP) in Malaysia - $13,000 (AUD)
  • 2012: PhD tuition fee and scholarship award: AUD $75,000

Awards and Honours

  • 1% highly-cited researcher, Web of Science, 2019 (Computer Science), 2020 (Computer Science and Engineering)
  • Pro-Vide Chancellor Research Excellence Award, Torrens University Australia, 2020
  • Pro-Vice Chancellor Research Special Award, Torrens University Australia, 2019
  • Teaching Excellence Award, Griffith College, 2019
  • First, second, and third most-cited articles of all time in Q1 journal of Advances in Engineering Software
  • The most-cited article of all time in Q1 journal of Neural Computing and Applications  
  • Best Paper Award, Soft Computing and Problem Solving conference, Liverpool, 2019
  • Top reviewer (rank first) in Computer Science, Computer Science category, Publons, 2019
  • Top reviews (rank 3rd) in the world in Publons, 2019
  • The Australian: Rising Star (ranked first in the Engineering and Computer Science) in Australia, 2019 
  • Courier Mail: Nomination and finalist for Queensland Pride of Australia, 2019
  • Student Research impact award and Best Student Paper award in AI, IIIS, Griffith University 2016
  • Awarded three Matlab Central Challenge Coins for being an outstanding contributor from 2015 to 2017
  • Griffith University Postgraduate student scholarship, 2012-2016
  • First class honours, master of Computer Science, Universiti Teknologi Malaysia (UTM), 2011
  • Nomination for the university academic excellence awards, Universiti Teknologi Malaysia (UTM), 2011 

Research Interest

  • Machine Learning 
  • Evolutionary algorithm
  • Optimization  
  • Data Science 
  • Robust optimization  
  • Swarm Intelligence
  • Multi-objective optimization  
  • Computational Intelligence

Other Relevant Skills And Certificates

  • Python, R, Java, C, C++, C#, Matlab, LaTeX