Nima Shamandi

• KTP associate in Generative Computational Design, School of Engineering
• Email: nima.shamandi@merit.co.uk

Nima Shamandi is an interdisciplinary, data-driven designer with expertise at the intersection of Computational Design, Architecture, Data Analysis, and Artificial Intelligence. With a strong foundation in digital skills for sustainable transitions, he has developed innovative projects that combine data analysis, optimization algorithms, and generative AI to address contemporary challenges in design and construction.

His portfolio includes kinetic façade optimization, smart lighting IoT systems, spatial analysis for micro-mobility, and AI-driven cultural heritage analysis — notably his MSc thesis on leveraging generative AI models for the preservation and reinterpretation of Persian architectural heritage. He has extensive experience with multimodal AI models, computational workflows, and optimization algorithms such as Genetic Algorithms.

As a KTP Associate with Newcastle University, Nima applies his computational expertise to the industrialized construction sector, developing generative design methods and BIM-integrated workflows to support digital design and off-site construction. His work bridges academic research and industrial innovation, with a focus on automated design processes and performance optimization.

Nima earned his Master of Science in Digital Skills for Sustainable Societal Transitions from the Polytechnic University of Turin, where he explored the application of AI in sustainable design, data analysis, and smart systems. His research interests include AI-assisted design, generative methods, and cultural heritage technology, with a vision to advance sustainable and data-driven approaches in architecture and construction.

His technical skills include Python, Grasshopper, Rhino, Revit, QGIS, and Speckle, alongside applied experience with multimodal AI.