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Hossein Javidnia

Dr. Hossein Javidnia

Dr. Hossein Javidnia is a distinguished researcher and academic leader with over 15 years of experience at the intersection of Artificial Intelligence, Computer Vision, and Augmented Reality (AR/VR). Currently serving as an Assistant Professor in Computing at Dublin City University, his work focuses on the convergence of deep learning, 3D reconstruction, and immersive systems. He holds a Ph.D. in Electronic & Electrical Engineering from the National University of Ireland Galway, where his thesis contributed significantly to depth measurement in consumer imaging.

Bridging the gap between theoretical research and commercial innovation, Dr. Javidnia has held prominent industry leadership roles, including Head of R&D at Union Avatars and Lead AI Engineer at Syze AI. His expertise in translating academic breakthroughs into scalable products has resulted in multiple U.S. patents and the securing of over €4 million in funding for next-generation digital identity and AI projects. His technical portfolio spans the development of large-scale cloud-native architectures, SLAM-based AR modules, and advanced synthetic data pipelines for industry giants like XPERI.

Beyond his technical achievements, Dr. Javidnia is deeply committed to shaping the future of AI education and research collaboration. He has spearheaded curriculum innovation as the Chair of the Master’s Program in AI at DCU and actively mentors over 20 graduate students. A dedicated member of the global research community, he plays a key role in organizing major international events, including the Irish Machine Vision & Image Processing Conference (IMVIP) and IEEE GEM, fostering vital connections between academia and the technology sector.

Teaching Interests

  • Artificial Intelligence and Deep Learning

  • Computer Graphics and Image Processing

  • Data Structures and Algorithms

  • Computational Methods and Engineering

  • AI-driven Software Architectures

  • Programming for Data Analysis

  • Programming Fundamentals

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