Mohammad Alfar

I am an architect, university instructor, and consultant working in architectural digital transformation, with a focus on BIM, computational design, and AI-informed learning systems.

My teaching and consulting practice centers on BIM methodologies and information-driven workflows, including ISO 19650, advanced Revit ecosystems, and model-based coordination strategies that connect design intent with data, planning, and decision-making across the project lifecycle.

Beyond BIM, my core interest lies in computational and algorithmic architectural thinking. I work with Dynamo, Grasshopper, and code-generated systems as tools to explore emergence, morphogenesis, and shape grammar, treating architecture as a dynamic process rather than a fixed object. Computation, in this sense, becomes a medium for experimentation: testing rules, constraints, and generative logics through which form, organization, and spatial narratives evolve.

I also teach architectural planning and project management, focusing on design-aware planning, workflow structuring, and the relationship between digital models, time, and construction logic.

In parallel, I develop architectural learning solutions that integrate AI as an exploratory and pedagogical layer. This includes structured GPT-based learning flows, controlled experimentation with lightweight AI pipelines such as nano banana, and the use of generative tools like Midjourney to support conceptual inquiry, visual reasoning, and iterative design thinking. My interest is not in replacing architectural judgment, but in augmenting it through systems that encourage curiosity, rigor, and reflective practice.

Across education, training, and consulting, my work seeks to connect analytical structure with architectural meaning, bridging BIM, computation, and AI within a coherent, research-driven approach to contemporary architectural practice.

Arabic (Native), English (Upper Advanced)