AMLD Workshop Generative AI for Forward and Inverse Design in Architecture and Engineering
Presentation
Traditionally, architectural and engineering design involves combining and optimizing many criteria and constraints. For performance-driven design, architects and engineers create parametric design models to generate, simulate, and evaluate many design instances, to gather performance feedback on design alterations. However, this is typically a challenging process, especially in the case of large design problems, limiting the designers to only investigate a narrow spectrum of possible solutions.
At the SDSC, in collaboration with Gramazio Kohler and the group on Concrete Structures and Bridge Design at ETH Zürich, we have developed the tool "AI-eXtended Design" for generative design for parametric modeling. During this workshop, you will be able to explore its possibilities and understand how to harness it to enhance your design workflows using machine learning.
Prerequisites
- Attendees should bring their laptop, and preferably pre-install the AIXD tools and Python environments required.
- The workshop is best suited for practitioners and scientists with at least intermediate experience in Python. It is aimed at architects and engineers with basic coding skills who want to leverage machine learning in their work, as well as computer/data scientists interested in applying their skills in the architecture or engineering domain.
* Recommended: basic understanding of machine learning, generative AI, experience with Python, Jupyter notebook, Pandas.
Details
Co-organised with
📅 Date: Sunday, 24 March
🕒 Time: 14:00 - 17:30
🎫 Get tickets here: https://go.epfl.ch/AMLD
Programme
Presenters
- Aleksandra Anna Apolinarska, Gramazio Kohler, ETHZ, Switzerland
- Michael Kraus, Concrete Structures and Bridge Design, ETHZ, Switzerland
- Luis Salamanca, SDSC, ETHZ and EPFL, Switzerland
14:00 - 15:30 Presentation: Introduction to generative AI for forward and inverse Design
15:30 - 16:00 Coffee break
16:00 - 17:30 Workshop: Applications and hands-on coding with AIXD toolbox
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Silvia holds an MSc in Computer Science from EPFL and a PhD in Computer Science from the University of York, UK. She has been a senior research fellow at the University of Trento and later at Politecnico di Milano, Italy. Here, she had the chance to work on Marie Curie and ERC projects relating to natural language processing. From 2012 to 2019, she was a Senior Manager and NLP expert at ELCA Informatique Switzerland, whose AI department she helped create and expand. Silvia joined the Swiss Data Science Center in 2019 and is currently its Chief Transformation Officer, in charge of the team leading organizations to digital transformation.
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Valerio started his career working for 7 years as a particle-physics researcher at CERN. There, he used state-of-the-art techniques to extract information from data, especially to search for traces of dark matter in particle collisions. Since 2016, he has worked in consulting, applying data science in several industries. First, he joined the Quant team of Ernst & Young in Geneva. Later, he created his own company, SamurAI sàrl, providing consulting services for his clients. He also has a passion for teaching very complex subjects in simple terms. That is why he particularly enjoys offering training programs to private companies and universities. Valerio joined the SDSC in Mai 2022 as a Principal Data Scientist with the mission of accompanying industrial partners and other institutions through their data science journey.
Sean obtained his PhD in Telecommunications Engineering from Dublin City University in 2001. Since then he has worked in large industry and startup contexts but has spent most of his time working in academic research labs with a strong applied focus spanning both Ireland and Switzerland. Sean has experience with all aspects of the research project lifecycle, ranging from project inception to proposal stage to project execution and reporting. Having a keen interest in technology trends and evolution, he strives to maintain a hands on approach with practical experience with key technologies in the rapidly changing cloud and analytics technology landscape. Sean works on the Renku Infrastrucuture team, leveraging his experience with modern cloud technologies, helping to make Renku easy to deploy and manage.
Luis is originally from Spain, where he completed his bachelor's studies in Electrical engineering, and the Ms.C. on signal theory and communications, both at the University of Seville. During his Ph.D. he started focusing on machine learning methods, more specifically message passing techniques for channel coding, and Bayesian methods for channel equalization. He carried it out between the University of Seville and the University Carlos III in Madrid, also spending some time at the EPFL, Switzerland, and Bell Labs, USA, where he worked on advanced techniques for optical channel coding. When he completed his Ph.D. in 2013, he moved to the Luxembourg Center on Systems Biomedicine, where he switched his interest to neuroscience, neuroimaging, life sciences, etc., and the application of machine learning techniques to these fields. During his 4 and a half years there as a Postdoc, he worked on many different problems as a data scientist, encompassing topics such as microscopy image analysis, neuroimaging, single-cell gene expression analysis, etc. He joined the SDSC in April 2018. As Lead Data Scientist, Luis coordinates projects in various domains. Several projects focus on the application of natural language processing and knowledge graphs to the study of different phenomena in social and political sciences. In the domains of architecture and engineering, Luis is responsible for projects centered on the application of novel generative methods to parametric modeling. Finally, Luis also coordinates different projects in robotics, ranging from collaborative robotic construction to deformable object manipulation.
Carlos Vivar Ríos joined the SDSC in 2023, where he is part of the Open Research Data and Engagement Unit (ORDES). As a multidisciplinary data engineer, he brings a diverse background in biology, cognitive sciences, and bioinformatics from the University of Malaga. His multifaceted professional career spans several disciplines, including genomics at RIKEN in Yokohama, multidimensional image analysis in microscopy at the University of Lausanne (UNIL), and cellular biology modeling at INRIA in Lyon. Carlos has been involved in a variety of projects, such as analyzing astrocyte calcium dynamics, de novo sequencing Solea senegalensis, drug repurposing for Alzheimer's based on GWAS studies, conducting geospatial analysis for linguistic corpora, and assessing drought through remote sensing. He is dedicated to advancing reproducible research methods and actively supports the open science movement.
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