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CoursesArchitectural DesignOptimizing Design Decisions With Machine Learning
Full Access Workshop May 25 & 26, 2024 8 Hours
Add to favorites (11)

Optimizing Design Decisions With Machine Learning

This workshop focuses on using machine learning to make design decisions. It covers theory and practical applications in various areas, such as facade and urban.

Zvonko Vugreshek
Verified Account

3 courses·5.0

Grasshopper 3D
Rhinoceros 3D
LunchBox
Owl
Octopus
Grasshopper 3D
Rhinoceros 3D
LunchBox
Owl
Octopus

About Optimizing Design Decisions With Machine Learning

Nowadays, computers are often the ones calling the shots, and this trend is everywhere. From creative/aesthetic decisions to preparing blueprints, you’re always trying to make the best choice based on a few key details. But making the right call quickly isn’t easy because there’s much to consider. That’s where machine learning and artificial intelligence come in—tools that help us make smarter choices and reduce potential errors. Now, they are accessible more than ever, especially for designers, engineers, and planners.

 

Nowadays, computers are often the ones calling the shots, and this trend is everywhere. From creative/aesthetic decisions to preparing blueprints, you’re always trying to make the best choice based on a few key details. But making the right call quickly isn’t easy because there’s much to consider. That’s where machine learning and artificial intelligence come in—tools that help us make smarter choices and reduce potential errors. Now, they are accessible more than ever, especially for...
What you will learn
  • 01

    How to recognize optimizable problems in your workflow or tasks and automate them.

  • 02

    First steps into data science and machine learning

  • 03

    Analyze existing morphologies/structures and optimize them according to specific criteria.

  • 04

    Make design decisions based on computed recommendations.

Methodology
  • The workshop will adopt a hands-on approach, combining lectures and practical exercises. Students will work individually on design projects that optimize various design parameters using machine learning and AI methods.

The workshop will cover the following workflows:

  • (Design) problem identification and formulation
  • Data collection and analysis
  • Model selection and utilization.
  • Optimization and evaluation
  • Design decision-making based on computed recommendations.

The course will primarily focus on the technical aspects of using machine learning for design decision-making. During the course, we will cover both the theory and practical applications of machine learning to optimize parameters in different design scenarios, such as facades, roof structuring, and urban design.

We will explore a range of methods and models, including single-objective optimization and neural network classifiers, to demonstrate how machine learning can be used. While the primary focus will not always be on the aesthetic outcome, we will work on optimizing the most valuable parameters required for the current example.
The workshop will adopt a hands-on approach, combining lectures and practical exercises. Students will work individually on design projects that optimize various design parameters using machine learning and AI methods. The workshop will cover the following workflows: (Design) problem identification and formulation Data collection and analysis Model selection and utilization. Optimization and evaluation Design decision-making based on computed recommendations. The course will primarily focus on...
Course Content
6 Lessons
Important Notes
  • 01
    Total sessions: 2 Sessions
  • 02
    PAACADEMY will provide a certificate of attendance.
Software & tools
Grasshopper 3DRhinoceros 3DLunchBoxOwlOctopus
Instructors
Zvonko Vugreshek
Zvonko Vugreshek
3 Courses5.0

Zvonko is an architect turned engineer and digital fabricator. He is currently addressing the challenge of integrating data science and machine learning into design and fabrication processes. He is working on his company, Pixolid UG, which operates in these fields, in Berlin. Zvonko has also been active in academia, working as a researcher and lecturer at various universities in Berlin and the surrounding area, including TU Berlin, BTU Cottbus, and IU Berlin, in the fields of digital fabrication, robotics, and computational/generative design.


His work focuses on bridging the gap between digital models and physical realities by training models to enhance robot-to-robot and human-to-robot collaboration. In this workshop, he will share his experience of translating real-world objects from photographs and demonstrate how computer vision and adaptive toolpaths can transform fabrication and design workflows.

Optimizing Design Decisions With Machine Learning FAQ

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Add to favorites (11)
Reviews
Purchase or enroll in this course to leave a review.
4.0avg·2 Reviews
2 Comments
Ignas
Ignas

Thank you

Dec 25, 2025
Pedro Soza
Pedro Soza

Very nice workshop!

Oct 15, 2024