Amirghasemi, Mehrdad

Associate Research Fellow

  • Associate Research Fellow - SMART Infrastructure Facility, Faculty of Engineering and Information Sciences

Overview


Dr Amirghasemi is an early career researcher with a PhD in Computing and Information Technology. He holds a master’s degree, in Intelligent Systems Design, from Chalmers University of Technology, Gothenburg, Sweden. He obtained a GPA of 5 (out of 5) for his master studies and received a scholarship award to pursue his PhD studies in University of Wollongong. Along with having two years experience in software development industry, he has been teaching and tutoring several web technologies, web development, programming, and simulation subjects within the University of Wollongong.

Research Overview


  • The central theme of his research interests is the application of evolutionary computation and simulation in solving a board class of problems in industry and business, namely IoT, cloud computing, and Operations Research. In his PhD thesis, a parallel metaheuristic framework has been developed to tackle a class of combinatorial optimisation problems. The computational results indicated that the proposed parallel strategy is highly effective; reaching high-quality solutions in a very short amount of time.

     

    In addition to co-authoring several journal and conference papers, Dr Amirghasemi has also been involved in design and implementation of several cloud-based software solutions, within SMART IoT hub for several industrial and academic partners. These applications could be seen as tools to promote concepts such as collaborative urban design and meta-moderation of innovative ideas within an organization.

Selected Publications


Impact Story


Keywords


  • SMART, Evolutionary Computation, Ubiquitous computing, IoT, Optimisation / Parallel Computing.

Research Overview


  • The central theme of his research interests is the application of evolutionary computation and simulation in solving a board class of problems in industry and business, namely IoT, cloud computing, and Operations Research. In his PhD thesis, a parallel metaheuristic framework has been developed to tackle a class of combinatorial optimisation problems. The computational results indicated that the proposed parallel strategy is highly effective; reaching high-quality solutions in a very short amount of time.

     

    In addition to co-authoring several journal and conference papers, Dr Amirghasemi has also been involved in design and implementation of several cloud-based software solutions, within SMART IoT hub for several industrial and academic partners. These applications could be seen as tools to promote concepts such as collaborative urban design and meta-moderation of innovative ideas within an organization.

Selected Publications


Impact Story


Keywords


  • SMART, Evolutionary Computation, Ubiquitous computing, IoT, Optimisation / Parallel Computing.
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