Vahid Saranirad serves as a Research Associate in Image & Vision Processing at Ulster University's School of Computing, Engineering and Intelligent Systems, based at the Derry~Londonderry campus. His academic role focuses on advancing computer vision and artificial intelligence through innovative computational frameworks. He completed his PhD in Computer Science at Ulster University in 2024 with the dissertation 'CDNA-SNN: a new spiking neural network for pattern classification using neuronal assemblies', supervised by McGinnity, Coyle, and Dora. His educational trajectory demonstrates deep specialization in neural computation. Saranirad's research centers on bioinspired artificial intelligence, with core expertise in spiking neural networks for pattern classification and industrial IoT systems. He bridges computational neuroscience with practical engineering, developing cloud-based frameworks using AWS for industrial automation while optimizing neural models through high-performance computing. His work uniquely integrates biological principles into machine learning architectures. Publication analysis (2021-2024) reveals an evolution from theoretical neural network innovations (DoB-SNN, Assembly-based STDP) toward applied industrial implementations (AWS IoT framework). This trajectory demonstrates increasing translational impact, with recent work emphasizing scalable solutions for real-world manufacturing and automation challenges. He actively collaborates within Ulster's Image & Vision Processing research group, contributing to interdisciplinary projects that connect neural computation with engineering applications. Current research directions indicate continued development of biologically plausible AI models for industrial computer vision systems.
