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CoursesArchitectural DesignOptimizing Design Decisions With Machine Learning
May 25-26, 20246 lessonsAdvanced
Architectural DesignFREE with Full AccessWorkshopMay 25-26, 2024Advanced6 lessons7h 46mGenerative DesignDesign Automation

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.

Learn from Zvonko Vugreshek
FREE with Full Access

Instructor

Zvonko Vugreshek3 courses

  • May 25-26, 202416:00 - 20:00 (GMT)
  • 7 Hours 46 MinTotal duration
  • Lifetime accessRewatch anytime
  • AdvancedLevel
  • 50 seatsClass size
  • EnglishLanguage
  • EnglishSubtitles
  • 6 LessonsLessons
  • CertificateIncluded
  • Course filesDownloadable

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.

 

  • 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.

Grasshopper 3DRhinoceros 3DLunchBoxOwlOctopus

How the 2 days are spent, session by session.

Day 1 Program

Saturday · May 25, 2024

Day 1:

 

  • Lecture about ML/Optimization/Data Science for design decision making.
  • Hands-on design of a structure to optimize.
  • Project assignments.
  • Q&A

Day 2 Program

Sunday · May 26, 2024

Day 2:

 

  • More advanced concepts and building up on the projects/topics from the previous day.
  • Project development and reviews.
  • Q&A

  • 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.

6 Lessons7h 46m

  • 01
    Total sessions: 2 Sessions
  • 02
    PAACADEMY will provide a certificate of attendance.

Instructor

Zvonko Vugreshek

View profile
5.0instructor rating3courses

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.

4.3·32
4.3avg·3 Ratings
2 Reviews
IgnasDec 25, 20255.0out of 5

Thank you

Pedro SozaOct 15, 20245.0out of 5

Very nice workshop!

Emre Onural4.0out of 5
Ignas
Ignas
Dec 25, 2025

Thank you

Pedro Soza
Pedro Soza
Oct 15, 2024

Very nice workshop!

Emre Onural
Emre Onural

  • 01AI-Driven Design PracticeCas Esbach€35.00
  • 02Parametric IntelligenceTim Fu€300.00
  • 03Integr8.AEC: Facades - Algorithmic Data ManagementStefano Rossi€35.00
  • 04Data Structure(D) Design 2.0Federico Borello€90.00
  • 05Taking Control 4.0: ControlNet x ComfyUI in ArchitectureCarlos Bañón€175.00
  • 06Taking Control 3.0: Stable Diffusion XL x ControlNetCarlos Bañón€145.00
  • AI-Driven Design PracticeCas EsbachIntermediate3 lessons1 Session (5 Hours)€35.00€50.00
  • Parametric IntelligenceTim FuIntermediate14 lessons4 Sessions (16 Hours)€300.00€400.00
  • Integr8.AEC: Facades - Algorithmic Data ManagementStefano RossiBeginner3 lessons4€35.00€50.00
  • Data Structure(D) Design 2.0Federico BorelloAdvanced10 lessons2 Sessions (8 Hours)€90.00€125.00
  • Taking Control 4.0: ControlNet x ComfyUI in ArchitectureCarlos BañónAdvanced8 lessons2 Sessions (10 Hours)€175.00€250.00
  • Taking Control 3.0: Stable Diffusion XL x ControlNetCarlos BañónIntermediate8 lessons8 Hours€145.00€175.00
Save €20.00

One-time payment

€105.00€125.00

Pay less with membership

Pro Membership€89.25Save €15.75 on this courseFull Access€0.00Plus every other course
InstructorZvonko Vugreshek
Regular Price
Save €20.00
€105.00€125.00
Pay less with membership
Pro Membership€89.25Save €15.75 on this courseFull Access€0.00Plus every other course