Seyed Jalaleddin Mousavirad

Postdoktor|Postdoc

Bakgrund

Seyed Jalaleddin Mousavirad (in short: Jalal) is currently a Postdoctoral researcher at Mid Sweden University, located in Sundsvall, Sweden. Previously, he served as a Research Fellow at the University of Beira Interior in Portugal, where he was actively involved in the European project called GreenStamp. This project focused on advancing AI-based sustainable practices and technologies for Android Apps.
Jalal obtained his PhD in Computer Engineering, specializing in Artificial Intelligence, from the University of Kashan in Iran. Following his doctoral studies, he worked at the University of Tehran (2018-2019) and Azad University (2019-2020) as an instructor. Additionally, he served as an Assistant Professor at the Faculty of Engineering at Hakim Sabzevari University in Iran.
With a strong research background, Jalal has made significant contributions in the areas of pattern recognition, machine learning, image processing, and evolutionary computation. He has published six book chapters and over 100 papers in reputable academic journals and conferences.
Jalal's international research experiences also include visiting a world-class research group at Xi'an Jiaotong-Liverpool University in China, where he further expanded his knowledge and collaborations.
He has organized several special sessions at prestigious conferences such as the IEEE Congress on Evolutionary Computation (IEEE CEC) and the International Conference on the Applications of Evolutionary Computation (EvoApplications). Furthermore, Jalal has served as a guest editor for various journals, including Computational Intelligence and Neuroscience, Entropy, and Mathematical Biosciences and Engineering.
Jalal actively contributes to the academic community as a reviewer for more than 50 prestigious journals and conferences. Some notable publications he has reviewed include IEEE Transactions on Evolutionary Computation, IEEE Transactions Systems, Mans, and Cybernetics, IEEE Transactions on Cybernetics, IEEE Access, IEEE System Journal, IEEE Transactions on Consumer Electronics, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Mobile Computing, Journal of Visual Communication and Image Representation, Neural Networks, Expert Systems with Applications, Applied Soft Computing, Soft Computing, Knowledge-based Systems, Swarm and Evolutionary Computation, Information Sciences, Genetic Programming and Evolvable Machines, IEEE Sensor Letters, and Connection Science.

Forskningsområden

Image Processing and Computer Vision, Machine Learning, Evolutionary Computation, and Applied Artificial Intelligence

Övrigt

Google Scholar 

Researchgate 

Linkedin

Web of Science 

ORCID

Publikationer

Artiklar i tidskrifter
Konferensbidrag

Artiklar i tidskrifter

Al Bataineh, A. , Jalali, S. M. J. , Seyed Jalaleddin, M. , Yazdani, A. , Islam, S. M. S. & Khosravi, A. (2024). An efficient hybrid extreme learning machine and evolutionary framework with applications for medical diagnosis. Expert systems (Print), vol. 41: 4  

Moghadam, M. H. , Borg, M. , Saadatmand, M. , Seyed Jalaleddin, M. , Bohlin, M. & Lisper, B. (2024). Machine learning testing in an ADAS case study using simulation‐integrated bio‐inspired search‐based testing. Journal of Software, vol. 36: 5  

Mohammadigheymasi, H. , Tavakolizadeh, N. , Matias, L. , Mousavi, S. M. , Moradichaloshtori, Y. , Seyed Jalaleddin, M. & Fernandes, R. (2023). A data set of earthquake bulletin and seismic waveforms for Ghana obtained by deep learning. Data in Brief, vol. 47, ss. 108969-108969.  

Seyed Jalaleddin, M. , Rahmani, R. & Dolatabadi, N. (2023). A transfer learning based artificial neural network in geometrical design of textured surfaces for tribological applications. Surface Topography: Metrology and Properties, vol. 11: 2  

Seyed Jalaleddin, M. & Alexandre, L. A. (2023). Energy-aware JPEG image compression : A multi-objective approach. Applied Soft Computing, vol. 141  

Zabihzadeh, D. , Alitbi, Z. & Seyed Jalaleddin, M. (2023). Ensemble of loss functions to improve generalizability of deep metric learning methods. Multimedia tools and applications,  

Seyed Jalaleddin, M. , Schaefer, G. , Zhou, H. & Moghadam, M. H. (2023). How effective are current population-based metaheuristic algorithms for variance-based multi-level image thresholding?. Knowledge-Based Systems, vol. 272  

Bojnordi, E. , Seyed Jalaleddin, M. , Pedram, M. , Schaefer, G. & Oliva, D. (2023). Improving the Generalisation Ability of Neural Networks Using a Lévy Flight Distribution Algorithm for Classification Problems. New generation computing, vol. 41: 2, ss. 225-242.  

Oliva, D. , Ortega-Sanchez, N. , Navarro, M. A. , Ramos-Michel, A. , El-Abd, M. , Seyed Jalaleddin, M. & Nadimi-Shahraki, M. H. (2023). Segmentation of thermographies from electronic systems by using the global-best brain storm optimization algorithm. Multimedia tools and applications, vol. 82: 29, ss. 44911-44941.  

Oliva, D. , Martins, M. S. R. , Hinojosa, S. , Elaziz, M. A. , dos Santos, P. V. , da Cruz, G. & Seyed Jalaleddin, M. (2022). A hyper-heuristic guided by a probabilistic graphical model for single-objective real-parameter optimization. International Journal of Machine Learning and Cybernetics, vol. 13: 12, ss. 3743-3772.  

Rezaee, K. , Seyed Jalaleddin, M. , Khosravi, M. R. , Moghimi, M. K. & Heidari, M. (2022). An Autonomous UAV-Assisted Distance-Aware Crowd Sensing Platform Using Deep ShuffleNet Transfer Learning. IEEE transactions on intelligent transportation systems (Print), vol. 23: 7, ss. 9404-9413.  

Zabihzadeh, D. , Tuama, A. , Karami-Mollaee, A. & Seyed Jalaleddin, M. (2022). Low-rank robust online distance/similarity learning based on the rescaled hinge loss. Applied intelligence (Boston), vol. 53: 1, ss. 634-657.  

Seyed Jalaleddin, M. , Oliva, D. , Chakrabortty, R. K. , Zabihzadeh, D. & Hinojosa, S. (2022). Population-based self-adaptive Generalised Masi Entropy for image segmentation : A novel representation. Knowledge-Based Systems, vol. 245  

Seyed Jalaleddin, M. , Zabihzadeh, D. , Oliva, D. , Perez-Cisneros, M. & Schaefer, G. (2021). A Grouping Differential Evolution Algorithm Boosted by Attraction and Repulsion Strategies for Masi Entropy-Based Multi-Level Image Segmentation. Entropy, vol. 24: 1  

Esmaeili, L. , Seyed Jalaleddin, M. & Shahidinejad, A. (2021). An efficient method to minimize cross-entropy for selecting multi-level threshold values using an improved human mental search algorithm. Expert systems with applications, vol. 182  

Seyed Jalaleddin, M. , Ebrahimpour-Komleh, H. & Schaefer, G. (2020). Automatic clustering using a local search-based human mental search algorithm for image segmentation. Applied Soft Computing, vol. 96  

Seyed Jalaleddin, M. & Ebrahimpour-Komleh, H. (2020). Human mental search-based multilevel thresholding for image segmentation. Applied Soft Computing, vol. 97  

Seyed Jalaleddin, M. , Bidgoli, A. A. , Komleh, H. E. & Schaefer, G. (2019). A memetic imperialist competitive algorithm with chaotic maps for multi-layer neural network training. International Journal of Bio-Inspired Computation (IJBIC), vol. 14: 4, ss. 227-227.  

Seyed Jalaleddin, M. , Ebrahimpour-Komleh, H. & Schaefer, G. (2019). Effective image clustering based on human mental search. Applied Soft Computing, vol. 78, ss. 209-220.  

Seyed Jalaleddin, M. & Ebrahimpour-Komleh, H. (2017). Human mental search : a new population-based metaheuristic optimization algorithm. Applied intelligence (Boston), vol. 47: 3, ss. 850-887.  

Seyed Jalaleddin, M. & Ebrahimpour-Komleh, H. (2017). Multilevel image thresholding using entropy of histogram and recently developed population-based metaheuristic algorithms. Evolutionary Intelligence, vol. 10: 1-2, ss. 45-75.  

lehi, A. Y. , Seyed Jalaleddin, M. & Akbari, A. (2017). Pre-treatment of textile wastewaters containing Chrysophenine using hybrid membranes. Membrane Water Treatment, vol. 8: 1, ss. 89-112.  

Konferensbidrag

Seyed Jalaleddin, M. , Oliva, D. , Schaefer, G. , Moghadam, M. H. & El-Abd, M. (2024). A Novel Two-Level Clustering-Based Differential Evolution Algorithm for Training Neural Networks. I Lecture Notes in Computer Science.. S. 259--272.  

Ramos-Michel, A. , Navarro, M. A. , Oliva, D. , Morales-Castaneda, B. , Casas-Ordaz, A. , Valdivia, A. , Rodriguez-Esparza, E. & Seyed Jalaleddin, M. (2023). Improving Metaheuristic Algorithm Design Through Inequality and Diversity Analysis : A Novel Multi-Population Differential Evolution. I 2023 IEEE Symposium Series on Computational Intelligence (SSCI).. S. 1547--1552.  

Sidan uppdaterades 2023-10-06