Abido, Mohammad - Assistant professor, Department of Electrical Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia. Includes description of his research areas.
Carlisle, Anthony J. - Professor at Huntingdon College. Applying the PSO to Non-Stationary Environments.
Eberhart, Russell C. - One of the founders of particle swarm optimization. IEEE fellow
Engelbrecht, Andries P. - Computational Intelligence Research Group, University of Pretoria. Research is done in theoretical aspects of PSO and developing new improved PSO models.
Fukuyama, Yoshikazu - His research interests include application of intelligent systems to power systems and power systems analysis. Some of his papers can be downloaded from the website.
Hu, Xiaohui - Research focus is biomedical data analysis and computational intelligence, especially particle swarm optimization.
Lascari, Eleni - Personal information, publications, game theory, particle swarm, stochastic optimization, evolutionary algorithms
Li, Xiaodong - Swarm intelligence, Ant colony algorithms, Particle Swarm, Differential Evolution, Multi-agent simulation
Mohan, Chilukuri K. - Professor at Syracuse University, research interests include evolutionary algorithms and artificial neural networks.
Parsopoulos, Konstantinos - Ph.D., Department of Mathematics, University of Patras, Greece: Computational and Swarm Intelligence with Applications.
Shi, Yuhui - Researcher in Particle swarm optimization, fuzzy logic, evolutionary computation.
Sinclair, Mark C. - Research interests include telecommunications network design, evolutionary algorithms, bbject technology, software agents. you can find a java applet that shows how pso works.
Suganthan, P. N. - His research interests include particle swarm, evolutionary computation, pattern recognition, bioinformatics and neural networks.
van den Bergh, Frans - Researcher at South Africa, which is working on some enhancements to the basic Particle Swarm Optimizer
Xie, Xiao-Feng - Particle swarm optimization (PSO), differential evolution (DE) and hybrid algorithms, for optimization problems.
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