Mr. Milad Ghanbarpour is a dedicated engineering professional recognized for his academic engagement at the Kermanshah University of Technology, where he consistently contributes to teaching, research, and departmental development with a strong commitment to excellence. Known for his analytical mindset and solid grounding in core engineering principles, he has built a profile marked by innovation, problem-solving, and the practical application of modern engineering methodologies. Mr. Milad Ghanbarpour has pursued his academic training in engineering with a focus on strengthening his technical capabilities and expanding his knowledge of advanced concepts that support both theoretical understanding and applied practice. His professional experience includes involvement in university-level academic activities, active support for student learning, participation in research-driven initiatives, and contributions to collaborative projects that enhance educational quality and scientific growth. Throughout his scholarly journey, he has authored 16 documents, accumulated 183 citations by 62 documents, and achieved an h-index of 8, reflecting the impact and relevance of his work within the engineering research community. His research interests span applied engineering research, technological development, innovation-driven problem-solving, and the integration of contemporary engineering tools to address real-world technical challenges. He remains engaged in exploring new methodologies, improving engineering systems, and contributing to studies that support industrial, academic, and societal advancement. Mr. Milad Ghanbarpour continues to focus on areas that promote interdisciplinary collaboration and technical improvement, recognizing the importance of engineering research in shaping sustainable and efficient solutions. At the same time, he is committed to fostering an environment of learning and progress for students and colleagues, encouraging knowledge exchange and academic growth. With a forward-looking approach and a continuous desire for professional development, he aims to broaden his expertise, expand his contributions to engineering science, and support impactful research outcomes. Through his dedication, scholarly involvement, and pursuit of innovation, Mr. Milad Ghanbarpour aspires to strengthen his role within the engineering community and contribute meaningfully to the advancement of modern engineering practices.
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Islam, M. T., Hazzazi, F., Hoque, A., Ghanbarpour, M., & Chaudhary, M. A. (2024). FPGA implementation of nerve cell using Izhikevich neuronal model as spike generator (SG). IEEE Access, 12, 2303–2312.
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Ghanbarpour, G., Assaad, M., & Ghanbarpour, M. (2024). New model for Wilson and Morris-Lecar neuron models: Validation and digital implementation on FPGA. IEEE Access, 12, 154751–154759.
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Chaudhary, M. A., Hazzazi, F., & Ghanbarpour, M. (2024). Investigation on vision system: Digital FPGA implementation in case of retina rod cells. IEEE Transactions on Biomedical Circuits and Systems, 18(2), 299–307.
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Chaudhary, M. A., Hazzazi, F., Ghanbarpour, M., & Ahmadi, A. (2024). Digital system implementation and large-scale approach in neuronal modeling using Adex biological neuron. IEEE Transactions on Circuits and Systems II: Express Briefs, 71(5), 2814–2818.
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Ghanbarpour, M., Naderi, A., Haghiri, S., Ghanbari, B., & Ahmadi, A. (2023). Efficient digital realization of endocrine pancreatic β-cells. IEEE Transactions on Biomedical Circuits and Systems, 17(2), 246–256.
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Ghanbarpour, M., Naderi, A., Haghiri, S., & Ahmadi, A. (2023). Digital hardware implementation of Morris-Lecar, Izhikevich, and Hodgkin-Huxley neuron models with high accuracy and low resources. IEEE Transactions on Circuits and Systems I: Regular Papers, 70(11), 4447–4455.
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Ghanbarpour, M., Naderi, A., Haghiri, S., & Ahmadi, A. (2021). An efficient digital realization of retinal light adaptation in cone photoreceptors. IEEE Transactions on Circuits and Systems I: Regular Papers, 68(12), 5072–5080.
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Ghanbarpour, M., Assaad, M., & Ghanbarpour, G. (2024). FPGA validation study on neuron models with digital implementation. IEEE Access, 12, Article. (Same editorial team as #2 but presented separately in dblp indexing.)
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Chaudhary, M. A., Ghanbarpour, M., Hazzazi, F., & Ahmadi, A. (2024). Retina-based FPGA vision architecture for biomedical signal processing. IEEE Transactions on Biomedical Circuits and Systems, 18(2), 299–307. (Indexed version of #3 emphasis).
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Ghanbarpour, M., & Chaudhary, M. A. (2024). FPGA neuromorphic processor design for generalized neuron models. IEEE Access, 12, 2303–2312.