Difference between revisions of "DC I/O 2022"
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[[Category:Conferences]] | [[Category:Conferences]] | ||
[[Category:Book]] | [[Category:Book]] | ||
+ | Design Computation Input/Output 2022 Conference (DC I/O 2022). DOI: https://doi.org/10.47330/DCIO.2022.ACSL3567 | ||
+ | [[File:DCIO2022 Poster.png|center|500px]] | ||
− | + | Design Computation Input/Output Conference, or simply DC I/O, was established with the premise that computational design methods should benefit from the scientific method and whenever possible, be cross-referenced in the many design disciplines to evolve and diversify the field. The conference assists in the understanding of the physical and digital relationships of producing design. It focuses on the many channels to capture the data necessary to inform design, the processes – natural and/or digital – of articulating this data input to accomplish design and the outcomes of these processes as artifacts and references of study in the domain of computational design. | |
− | + | =Conference Committee= | |
+ | '''Advisory Board''': Prof. David Kirsh, Prof. Jacqueline Glass, Prof. Jeremy Melvin, Prof. Kate Jeffery, Dr. Patrik Schumacher, and Prof. Robert Aish. | ||
− | + | '''Programme Committee''': Dr. Abel Maciel, Prof. Sean Hanna, Dr. Theodore Spyropoulos. | |
− | + | '''Design Theory Committee''': Dr. Anastasia Globa, Ava Fatah Gen. Schieck, Dustin White, Prof. Marjan Colletti, Prof. Peter Russell. | |
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− | + | '''Scientific Committee''': Alvaro Lopez, Dr. Bailin Deng, Dr Carlos Galera-Zarco, Dr. Christopher Leung, Dr. David Swapp, Dr. Eleni Papadonikolaki, Dr. Iro Armeni, Prof. James Tompkin, Dr. Kimon Krenz, Shneel Malik, Dr. Stephen Law, Prof. Tamir El-Khouly | |
− | Dr. | ||
− | + | '''Industry Committee''': Eduardo Lazzarotto, Greg Demchak, Kean Walmsley, Luis Fraguada, Shajay Bhooshan. | |
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− | + | '''Peer-Reviewers''': Alvaro Lopez, Ava Fatah Gen. Schieck, Bailin Deng, Clara Jaschke, Carlos Galera-Zarco, David Swapp, Eleni Papadonikolaki, Jacqueline Glass, James Tompkin, Kate Jeffery, Kean Walmsley, Kimon Krenz, Luis Fraguada, Maj Plemenitas, Richard Beckett, Robert Aish, Stephen Gage, Tyson Hosmer, Wiktor Kidziak, Stephen Law. | |
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− | Alvaro Lopez, Ava Fatah Gen. Schieck, | ||
=Proceedings= | =Proceedings= | ||
− | |||
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− | |||
==Session 1: Algorithms== | ==Session 1: Algorithms== | ||
===Keynote=== | ===Keynote=== | ||
− | * [[ | + | * [[Neural Fields for Scalable Scene Reconstruction]] |
===Proceedings=== | ===Proceedings=== | ||
− | * [[ | + | * [[A machine learning assisted preliminary design methodology for repetitive design features in complex structures]] |
− | * [[ | + | * [[Environmental-driven Massing Based on Machine learning]] |
− | * [[ | + | * [[Simulation and Fabrication of Elastic Deployable Stripe Structures]] |
+ | *[[View-Based Luminance Mapping in Open Workplace]] | ||
===Discussion=== | ===Discussion=== | ||
− | * [[Session 1 (Algorithms) Discussion]] | + | * [[DC I/O 2022 Session 1 (Algorithms) Discussion]] |
==Session 2: Cognitions== | ==Session 2: Cognitions== | ||
===Keynote=== | ===Keynote=== | ||
− | * [[The | + | * [[The Internet of Doors - topologies and doorframe computing]] |
− | |||
===Proceedings=== | ===Proceedings=== | ||
− | * [[ | + | * [[Aesthetic Measure of Architectural Photography utilizing Computer Vision: Parts-from-Wholes]] |
− | * [[ | + | * [[Eye on HMI - Assessment of Human-Machine Interface with wearable eye-tracking glasses]] |
− | * [[ | + | * [[Interconnectivity of Deep Learning Models in AI-Driven Design Systems]] |
− | * [[ | + | * [[Understanding the Relationship between Eye Position and Body Movement during Navigation with Unusual Visual Perception]] |
===Discussion=== | ===Discussion=== | ||
− | * [[Session 2 (Cognitions) Discussion]] | + | * [[DC I/O 2022 Session 2 (Cognitions) Discussion]] |
==Session 3: Cultures== | ==Session 3: Cultures== | ||
===Keynotes=== | ===Keynotes=== | ||
− | * [[ | + | * [[Postdigital Architecture. What Now?!]] |
− | |||
===Proceedings=== | ===Proceedings=== | ||
− | * [[ | + | * [[Fragmented Layers of Design Thinking: Limitations and Opportunities of Neural Language Model-assisted processes for Design Creativity]] |
− | + | * [[Virtually Physical Immaterial]] | |
− | * [[ | + | * [[Approach to Digital Twins of Woody Vegetation (Trees and Shrubs)]] |
− | * [[ | ||
===Discussion=== | ===Discussion=== | ||
− | * [[Session 3 (Cultures) Discussion]] | + | * [[DC I/O 2022 Session 3 (Cultures) Discussion]] |
==Session 4: Applications== | ==Session 4: Applications== | ||
===Keynotes=== | ===Keynotes=== | ||
− | * [[ | + | * [[Material Based Computational Design Strategies]] |
===Proceedings=== | ===Proceedings=== | ||
− | * [[ | + | *[[Prototyping the Organic: AI in design work-flows for complex forms inspired by nature]] |
− | * [[ | + | *[[KPF Karst Mountains Inspired Facades Optimisation]] |
− | * [[ | + | *[[Research into Digital Twins for AEC]] |
+ | *[[Allplan PythonPart in Practice]] | ||
+ | *[[Bacton Digital Beach Twin: a Digital Twin for natural assets]] | ||
===Discussion=== | ===Discussion=== | ||
− | + | * [[DC I/O 2022 Session 4 (Applications) Discussion]] | |
− | * [[ | ||
− | |||
=Closing Keynote= | =Closing Keynote= | ||
− | *[[ | + | *[[A synthesis of Algorithms, cognitions, Cultures and Applications of Design Computation]] |
=Workshop Sessions= | =Workshop Sessions= | ||
− | * [[ | + | * [[Computational Design in Railway Simulations: Challenges and Hope in Timetable Engineering]] |
− | * [[ | + | * [[Components Fusion in Modo Foundry]] |
+ | * [[Mix Reality, Data and Experiences]] | ||
=Reference= | =Reference= | ||
− | Conference DOI: https://doi.org/10.47330/DCIO. | + | Conference DOI: https://doi.org/10.47330/DCIO.2022.ACSL3567 |
− | Full text in: [https://www.designcomputation.org/dcio2021 Maciel, A. (Ed.), | + | Full text in: [https://www.designcomputation.org/dcio2021 Maciel, A. (Ed.), 2022. Design Computation Input/Output 2022, 1st ed. Design Computation, London, UK. ISBN: 978-1-8381294-2-2] |
Latest revision as of 23:47, 10 December 2023
Design Computation Input/Output 2022 Conference (DC I/O 2022). DOI: https://doi.org/10.47330/DCIO.2022.ACSL3567
Design Computation Input/Output Conference, or simply DC I/O, was established with the premise that computational design methods should benefit from the scientific method and whenever possible, be cross-referenced in the many design disciplines to evolve and diversify the field. The conference assists in the understanding of the physical and digital relationships of producing design. It focuses on the many channels to capture the data necessary to inform design, the processes – natural and/or digital – of articulating this data input to accomplish design and the outcomes of these processes as artifacts and references of study in the domain of computational design.
Contents
Conference Committee
Advisory Board: Prof. David Kirsh, Prof. Jacqueline Glass, Prof. Jeremy Melvin, Prof. Kate Jeffery, Dr. Patrik Schumacher, and Prof. Robert Aish.
Programme Committee: Dr. Abel Maciel, Prof. Sean Hanna, Dr. Theodore Spyropoulos.
Design Theory Committee: Dr. Anastasia Globa, Ava Fatah Gen. Schieck, Dustin White, Prof. Marjan Colletti, Prof. Peter Russell.
Scientific Committee: Alvaro Lopez, Dr. Bailin Deng, Dr Carlos Galera-Zarco, Dr. Christopher Leung, Dr. David Swapp, Dr. Eleni Papadonikolaki, Dr. Iro Armeni, Prof. James Tompkin, Dr. Kimon Krenz, Shneel Malik, Dr. Stephen Law, Prof. Tamir El-Khouly
Industry Committee: Eduardo Lazzarotto, Greg Demchak, Kean Walmsley, Luis Fraguada, Shajay Bhooshan.
Peer-Reviewers: Alvaro Lopez, Ava Fatah Gen. Schieck, Bailin Deng, Clara Jaschke, Carlos Galera-Zarco, David Swapp, Eleni Papadonikolaki, Jacqueline Glass, James Tompkin, Kate Jeffery, Kean Walmsley, Kimon Krenz, Luis Fraguada, Maj Plemenitas, Richard Beckett, Robert Aish, Stephen Gage, Tyson Hosmer, Wiktor Kidziak, Stephen Law.
Proceedings
Session 1: Algorithms
Keynote
Proceedings
- A machine learning assisted preliminary design methodology for repetitive design features in complex structures
- Environmental-driven Massing Based on Machine learning
- Simulation and Fabrication of Elastic Deployable Stripe Structures
- View-Based Luminance Mapping in Open Workplace
Discussion
Session 2: Cognitions
Keynote
Proceedings
- Aesthetic Measure of Architectural Photography utilizing Computer Vision: Parts-from-Wholes
- Eye on HMI - Assessment of Human-Machine Interface with wearable eye-tracking glasses
- Interconnectivity of Deep Learning Models in AI-Driven Design Systems
- Understanding the Relationship between Eye Position and Body Movement during Navigation with Unusual Visual Perception
Discussion
Session 3: Cultures
Keynotes
Proceedings
- Fragmented Layers of Design Thinking: Limitations and Opportunities of Neural Language Model-assisted processes for Design Creativity
- Virtually Physical Immaterial
- Approach to Digital Twins of Woody Vegetation (Trees and Shrubs)
Discussion
Session 4: Applications
Keynotes
Proceedings
- Prototyping the Organic: AI in design work-flows for complex forms inspired by nature
- KPF Karst Mountains Inspired Facades Optimisation
- Research into Digital Twins for AEC
- Allplan PythonPart in Practice
- Bacton Digital Beach Twin: a Digital Twin for natural assets
Discussion
Closing Keynote
Workshop Sessions
- Computational Design in Railway Simulations: Challenges and Hope in Timetable Engineering
- Components Fusion in Modo Foundry
- Mix Reality, Data and Experiences
Reference
Conference DOI: https://doi.org/10.47330/DCIO.2022.ACSL3567 Full text in: Maciel, A. (Ed.), 2022. Design Computation Input/Output 2022, 1st ed. Design Computation, London, UK. ISBN: 978-1-8381294-2-2