Syllabus
Credits: Latent Studio, student: Alberto Carro Novo, advisor: Oana Taut
Intro Description & Structure
The Algorithmic Design I Thesis Cluster is an advanced course that delves into the innovative convergence of artificial intelligence, computational design, and architecture. The cluster aims to revolutionise architectural design by harnessing cutting-edge technologies to create adaptive, resilient, and efficient workflows within the Architecture, Engineering, and Construction (AEC) industry.
Key Research Areas
- Generative Design and AI-Assisted Creativity
- Explore how AI tools can push the boundaries of architectural imagination.
- Investigate methodologies for integrating AI into the creative workflow.
- Intelligent Spatial Analysis and Optimization
- Study computational techniques to enhance building performance.
- Optimize architectural layouts using AI-driven solutions.
- Data-Driven Architecture and Digital Integration
- Research methods to extract and utilize architectural data effectively.
- Integrate AI-generated designs with modern digital practices.
- Next-Generation Architectural Workflows
- Focus on the incorporation of LLMs into architectural processes.
- Enhance professional practice through AI-enabled efficiency and collaboration.
Course Objectives
- Empower Creative Exploration of advanced computation technology and AI
- Conceptualize Building Performance workflows
- Integrate Data-Driven Approaches
- Innovate Architectural Workflows
This cluster aims to push the boundaries of what’s possible in architecture, blending cutting-edge technology with design innovation to shape the adaptive and inspiring spaces of tomorrow.
Faculty
Faculty Assistants
Projects from this course
DESIGN FLEX- PHASE- II
Abstract Parametric design tools like Grasshopper empower architects to create adaptive and efficient spatial layouts, but their complexity presents a barrier for non-experts. This research proposes a community-driven design tool that leverages Graph Neural Networks (GNNs) and Large Language Models (LLMs) to learn from expert-authored Grasshopper scripts, enabling prompt-based parametric layout design. By encoding design … Read more
DECODING URBAN MOBILITY
ABSTRACT; Decoding Urban Mobility: This project evaluates the impact of AI-driven traffic management versus conventional fixed-timing methods on urban congestion. It analyzes real-time and historical data—including traffic patterns, weather, demographics, and incident reports—from cities like London, Barcelona, and Los Angeles and compares machine learning models (e.g., LSTM, GRU, XGBoost) with traditional techniques. The study identifies … Read more
GENERATIVE AI – TIMBER PHYGITAL
This thesis explores the use of generative AI to transform 2D image prompts into fabricatable 3D pavilion designs using timber sheet-based CNC milling. By developing a workflow from AI-driven image generation to mesh segmentation and fabrication detailing, the research aims to bridge the gap between conceptual design and physical realization. The outcome is a phygital … Read more
DESIGN FLEX
Learning from Yesterday, Live for Today, Hope for future, The important thing is not to stop questioning. Albert Einstein
Fire Sense
Automated Fire compliance assessment tool Fire safety in buildings isn’t just about alarms and sprinklers—it’s about designing spaces that prevent tragedies before they happen. Imagine if architects could assess the fire safety of their designs with just a click, ensuring compliance with global standards during the early stages of construction. Sounds futuristic? Not anymore. In … Read more
EcoNodes
Introduction: Transforming Urban Junctions for a Sustainable Future Urbanization has drastically increased impervious surfaces in cities, leading to environmental challenges such as urban heat islands, stormwater runoff, and reduced access to green spaces. Junctions and intersections, often overlooked, are some of the most impervious and environmentally stressed areas in urban landscapes. This project aims to … Read more
GENERATIVE A.I. PHY-GITAL 3D
The research envisions to develop work on the existing artificial intelligence models inclined for development of images through prompts and related tools to generate images which can be further leveraged into 3D translation of geometry to offer an aid for designers and creatives to develop their concept
