The Bachelor of Architecture program prepares future architects by fostering creativity, critical thinking, and design excellence. Through an interdisciplinary curriculum, students are equipped to address global challenges with a focus on sustainability, innovation, digital technologies, and cultural awareness.
Study Plan
Tracks
Track 1: AI in Architecture Track (AIA)
This track focuses on integrating artificial intelligence into the architectural design process, empowering students
to leverage machine learning and AI tools for creating intelligent, data driven designs. Students will delve into
generative design algorithms, AI-powered simulations, and performance analysis to develop innovative solutions.
Includes topics such as: AI-Driven, Design Tools, Generative Design and Optimization, Performance-Based
Design Analytics, Autonomous Building Systems AI for Urban and Environmental Analysis.
Students in the AI in Architecture Track will:
• Understand the fundamentals of AI and ML in the context of architecture and the built environment.
• Develop proficiency in computational design tools, such as Grasshopper, Rhino, MidJourney, Stable
Diffusion, and AI-assisted generative design software.
• Explore AI-driven building performance analysis, including energy modeling, daylight optimization, and
environmental simulations.
• Leverage AI for urban and smart city planning, analyzing big data, mobility patterns, and sustainability
metrics.
• Use AI in architectural visualization, employing tools for automated rendering, image generation, and
augmented reality presentations.
• Investigate ethical considerations and biases in AI-generated designs, ensuring responsible and human-
centered AI integration in architecture.
• Develop innovative AI-driven workflows to automate design iterations, optimize material usage, and
enhance sustainability.
Track Plan
Track 2: Digital and Parametric Architecture (DPA)
This track combines advanced digital tools and parametric methodologies to enable students to create
innovative and performance-driven architectural designs. The curriculum integrates computational design,
parametric modeling, and digital fabrication techniques, focusing on both conceptual exploration and practical
applications. Topics include Parametric Design Fundamentals, Advanced Grasshopper and Computational
Workflows, Generative Algorithms for Architecture, Digital Fabrication Techniques (3D Printing and CNC),
and Performance-Driven Design Strategies.
Students in the Digital and Parametric Architecture Track will:
• Master computational design principles, including rule-based generative design and algorithmic
modeling.
• Develop proficiency in parametric modeling software, such as Rhino + Grasshopper, Dynamo, and
Houdini, to create responsive and performance-driven designs.
• Understand digital fabrication techniques, including 3D printing, CNC milling, and robotic
fabrication, and their application in architectural design.
• Explore form-finding strategies through parametric workflows, using mathematical and data-driven
approaches to optimize structural and environmental performance.
• Investigate material innovations in digital architecture, applying computational simulations to assess
material behavior and sustainability.
• Develop advanced scripting and automation skills using Python and C# in Grasshopper, enabling
customization of design workflows.
• Engage in real-world applications of parametric architecture, working on digital fabrication projects
and interactive installations.
Track Plan
Track 3: Computational Landscape Design (CLD)
This track emphasizes the integration of computational tools and methods in landscape design to create
sustainable and innovative outdoor spaces. Students will explore the use of parametric modeling, simulation
tools, and geographic information systems (GIS) to design ecologically sensitive landscapes that respond to
environmental challenges. Key topics include Parametric Landscape Modeling and Visualization, GIS and
Environmental Analysis for Landscape Design, Computational Ecology and Planting Strategies, Sustainable
Landscape Systems Optimization, and Digital Fabrication for Landscape Features.
Students in the Computational Landscape Design Track will:
• Develop proficiency in parametric modeling and generative design tools (Rhino + Grasshopper,
ArcGIS, Houdini) to create adaptive landscape solutions.
• Integrate Geographic Information Systems (GIS) and data-driven analysis into site planning and
environmental design.
• Apply environmental simulations to optimize stormwater management, energy efficiency, and
microclimate regulation in landscape architecture.
• Explore robotic and digital fabrication methods for landscape prototyping and ecological restoration
strategies.
• Analyze case studies of computationally driven landscape projects to understand the application of
advanced design methodologies.
• Develop workflows for parametric planting design, evaluating species distribution, soil conditions,
and water management.
• Leverage digital twin technology for real-time monitoring and optimization of landscape performance
Track Plan
Track 4: Computational Interior Design (CID)
This track integrates advanced computational tools and methods into the interior design process, empowering
students to create innovative, functional, and performance-driven interior spaces. The curriculum emphasizes
parametric design, material optimization, and data driven strategies to enhance user experience and spatial
efficiency. Students will explore cutting-edge technologies and workflows to address contemporary
challenges in interior design. Key topics include Parametric Design for Interior Spaces, Material and Furniture
Optimization, Lighting and Environmental Simulations, Digital Fabrication for Interior Design.
Students in the Computational Interior Design Track will:
• Develop expertise in parametric and generative interior design, using tools such as Rhino + Grasshopper,
Dynamo, and AI-driven design platforms.
• Apply digital fabrication techniques to produce customized interior elements, furniture, and modular
design components.
• Optimize material use and energy performance through computational simulations and smart building
technologies.
• Integrate immersive technologies such as VR/AR to visualize and test interactive interior spaces.
• Explore digital twin technology for real-time monitoring and responsive interior systems.
• Investigate AI-driven interior design trends that enhance personalized user experiences and adaptability.
• Master project management and digital workflows for large-scale commercial, residential, and hospitality
interiors.