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Research area(s)

• Dr Maziar Ghorbani’s research encompasses a broad range of cutting-edge areas in computer science and engineering. His work focuses on high-performance computing, where he explores innovative techniques and architectures for efficient distributed and parallel computing systems. He also specialises in large-scale simulations, particularly in agent-based and geospatial modelling, optimising these simulations to address complex systems.

• In the field of artificial intelligence, Dr Ghorbani integrates machine learning and computer vision techniques with sensor instrumentation and IoT systems, advancing the capabilities of automated sensing, data processing, and intelligent decision-making. This interdisciplinary approach enhances real-time data analysis and system performance across various applications.

• Dr Ghorbani is also deeply engaged in ensuring the accuracy and reliability of simulations through verification, validation, and uncertainty quantification methods. His research includes advanced simulation visualisation, where he utilises real-time 3D tools to enhance understanding and interpretation of simulation outcomes.

• Further, his expertise in high-level architecture (HLA) and distributed systems contributes to the optimisation of collaborative space simulations, facilitating large-scale and complex multi-agent environments. Dr Ghorbani’s work on interactive systems extends to robotics, real-time visualisation, and human-computer interactions, fostering developments in both scientific research and practical applications.

Research Interests

Dr Maziar Ghorbani's research interests lie at the forefront of artificial intelligence (AI), with a specific focus on generative AI and its transformative potential across various industries. He is also keenly interested in game engines and rendering technologies, exploring how these tools can be applied to enhance simulations and visualisation. Additionally, Dr Ghorbani has a deep interest in computer languages and programming, continually seeking to optimise computational efficiency and explore new paradigms in software development.