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The Meat of AI: Architecture & Dataset Creation
Artificial Intelligence | Online Workshop | English | North-South Americas
Description:
Key Words: Artificial Intelligence,Neural Networks,Dataset Generation,Machine Learning
Required Skills: N/A
Required Software: N/A
Required Hardware: PC
Maximum number of participating students: unlimited
AR2IL / SPAN Artificial Intelligence Workshop
Deep Neural Networks are incredibly data hungry; the high performance of these algorithms is heavily dependent upon the availability of giant training datasets. In the growing field of Deep Design and Architecture, there is a huge need for the collection/creation of comprehensive labeled datasets (in both the 2D image/plan realm as well as for 3D models).
While this workshop will be a crash course instruction in Dataset Generation, including data creation and labeling methodology and tools, we will instruct students on how to create and end-to-end machine learning pipelines. Specifically, how to formulate a desired task into a problem that is solvable with machine vision tools, how to design and generate a dataset that defines the world space for this task/problem space, and finally how one can train and evaluate and algorithm on their dataset.
With these tools, the students of this workshop will be able to participate in a very unique opportunity: they will be able to contribute as both annotators and creators to AR2IL's effort to generate a novel Floor plan dataset, called Common House. The students will be credited as contributors to the dataset, and have opportunities to continue as annotators on the dataset in the months after the workshop.
Schedule:
Jun 26 - Jun 30
  • Day 1 / Jun 26

    9:00 - 17:00 (GMT-4:00) Eastern Time (US and Canada)

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    09:00 - 17:00 (EST)

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    15:00 - 23:00 (CET)

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    21:00 - 05:00 (China)

    Morning: Introduction to Deep Neural Networks and why we need huge datasets / Afternoon: Hands-On/Tutorial: Introduction to Floor Plan Annotation
  • Day 2 / Jun 27

    9:00 - 17:00 (GMT-4:00) Eastern Time (US and Canada)

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    09:00 - 17:00 (EST)

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    15:00 - 23:00 (CET)

    |

    21:00 - 05:00 (China)

    Morning: In Depth Introduction to Labeling Noise/Annotator Bias (what problems can arise in dataset taxonomy, labeling, data collection) / Afternoon: Hands-On/Tutorial: Continuing Floor Plan Annotation
  • Day 3 / Jun 28

    9:00 - 17:00 (GMT-4:00) Eastern Time (US and Canada)

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    09:00 - 17:00 (EST)

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    15:00 - 23:00 (CET)

    |

    21:00 - 05:00 (China)

    Morning: Q and A with workshop leaders / Afternoon: Hands-On/Tutorial: Continuing Floor Plan Annotation
  • Day 4 / Jun 29

    9:00 - 17:00 (GMT-4:00) Eastern Time (US and Canada)

    |

    09:00 - 17:00 (EST)

    |

    15:00 - 23:00 (CET)

    |

    21:00 - 05:00 (China)

    Morning: In depth training and data loader tutorial / Afternoon: Hands-On/Tutorial: Training, then continuing Floor Plan Annotation
  • Day 5 / Jun 30

    9:00 - 17:00 (GMT-4:00) Eastern Time (US and Canada)

    |

    09:00 - 17:00 (EST)

    |

    15:00 - 23:00 (CET)

    |

    21:00 - 05:00 (China)

    Morning: In depth model evaluation tutorial / Afternoon: Hands-On/Tutorial: Evaluating trained models
Instructors:
  • Matias del Campo Taubman College for Architecture and Urban Planning, University of Michigan,Associate Professor
    Dr. Matias del Campo is a registered architect, designer, and educator. He is Associate Professor at Taubman College for Architecture and Urban Planning, University of Michigan, and director of the AR2IL – The Architecture and Artificial Intelligence Laboratory. Here he conducts research on advanced design methods in architecture, primarily through the application of Artificial Intelligence techniques in collaboration with Michigan Robotics and the Computer Science department. Co-founded by Matias del Campo and Sandra Manninger, the architecture practice SPAN is a globally acting practice best known for its application of contemporary technologies in architectural production. Their award-winning architectural designs are informed by advanced geometry, computational methodologies, and philosophical inquiry. SPAN gained wide recognition for its winning competition entry for the Austrian Pavilion at the 2010 Shanghai World Expo, as well as the new Brancusi Museum in Paris. Most recently Matias del Campo was awarded the Accelerate@CERN fellowship, the AIA Studio Prize, and was elected into the boards of directors of ACADIA and IJAC the International Journal of Architectural Computing. SPAN’s work is in the permanent collection of the FRAC, the MAK in Vienna, the Benetton Collection, the Albertina, and several private collections.
  • Alexa Carlson ,
  • Janpreet Singh University of Michigan,Research Assistant
    Currently pursuing Masters in Electrical and computer engineering department at University of Michigan, Ann Arbor. My research interests are in the field of Computer Vision.