Generative AI for Design
May 2, 2025
To be held at MIT (Cambridge, MA)
The Gen AI for Design Workshop brings together researchers in Design, Architecture, Computer Science, Mechanical Engineering, Music, and other related fields to shape future research in generative AI, focusing on performance-based design—an approach that prioritizes achieving specific measurable outcomes in areas like structural integrity, energy efficiency, acoustic performance, material optimization, airflow dynamics, lighting quality, and real-time responsiveness in interactive systems. The topics can include AI-driven optimization in design processes, generative methods for sustainable architecture, acoustics, lighting, immersive environments for gaming, AI-assisted creativity in music and sound design, multi-disciplinary applications of machine learning in design, human-AI collaboration in creative fields, AI-driven code generation for complex system designs, AI-enhanced user interface and user experience (UI/UX) design, algorithmic generation of virtual and augmented reality environments, and any other topic related to performance-based design. Both in-progress projects and published research are allowed.
Call for Submissions
All submissions are handled via OpenReview. The LaTeX template is made available on Overleaf.
Abstracts:
Please submit an abstract (150–300 words) by Jan 20th (deadline extended) to be considered for a presentation or poster. Abstracts should highlight their connection to performance-based Generative AI.
Submitting the abstract before the deadline is mandatory to be considered for participating in the workshop.
Extended abstracts:
Extended abstracts are due by Feb 10th to secure a spot. Submissions should be a maximum of 3 pages in length, excluding references, figures, and tables, with 3–5 figures and tables. Appendices are not permitted. As there will be no published proceedings, presenting at this workshop will not interfere with future publications.
Submissions should include the motivation to the work, clearly state the contributions in the context of the current literature, describe the methodology and show preliminary results and their potential impact. Submissions will be evaluated based on novelty, clarity, technical innovation and potential impact. Decisions on selected abstracts will be sent by Feb 28, 2025.
Presentations and Posters
Submitted abstracts will be considered for both oral presentations and poster sessions. A selection of abstracts will be chosen for oral presentations, while others will be featured in the poster session. The review process will be double-blind and authors will be notified of their presentation format upon acceptance. Each presentation is allocated an 8-minute slot, with an additional 2 minutes dedicated to questions and the change of speaker.
Best Presentation Award
The Best Presentation Award will be announced at the end of the event. Presentations will be evaluated based on scientific merit and innovation, clarity and organization, engagement with the audience, visual and technical quality, contribution and impact.
Registration
Participation is free, but spots are limited and registration before March 28, 2025 is required to guarantee a spot. Lunch will be provided for the presenters.
Important Dates and Deadlines
Abstract submission: Jan 20, 2025
Extended abstract submission: Feb 10, 2025
Author notification: March 7, 2025
Registration: March 28, 2025
Workshop program announced: April 18, 2025
Presentation submission: April 25, 2025
Workshop: May 2, 2025
Keynote Speaker
Dr. Mark Fuge is a Full Professor and Chair of Artificial Intelligence in Engineering Design within the Department of Mechanical and Process Engineering at ETH Zurich. He studies fundamental scientific and mathematical questions behind how humans and computers can work together to design better complex engineered systems, from the molecular scale all the way to systems as large as aircraft and ships using tools from Computer Science (such as machine learning, artificial intelligence, and submodular optimization) and Applied Mathematics (such as graph theory, category theory, and statistics). He received his Ph.D. from UC Berkeley and has received an NSF CAREER Award, a DARPA Young Faculty Award, and a National Defense Science and Engineering Graduate (NDSEG) Fellowship.
Panelists
Anna Huang is an Assistant Professor at MIT, with a shared position between Electrical Engineering and Computer Science (EECS) and Music and Theater Arts (MTA). For the past 8 years, she has been a researcher at Magenta in Google Brain and then Google DeepMind, working on generative models and interfaces to support human-AI partnerships in music making. Anna was a Canada CIFAR AI Chair at Mila, and continues to hold an adjunct professorship at University of Montreal. She was a judge then organizer for AI Song Contest 2020-22. She did her PhD at Harvard University, master’s at the MIT Media Lab, and a dual bachelor’s at University of Southern California in music composition and CS.
Caitlin Mueller is an Associate Professor at MIT’s Department of Architecture and Civil and Environmental Engineering, directing the Building Technology Program and the Digital Structures research group, and Associate Director of the MIT Climate and Sustainability Consortium. She works at the intersection of architecture, structural engineering, and computation to develop new computational design and digital fabrication methods for sustainable, high-performance buildings. Her current projects focus on multi-physics design, optimization, and fabrication of low-cost, low-carbon structures in reinforced concrete and timber. She also develops methods that leverage machine learning and computational geometry for human-centric design processes.
Karl D.D. Willis is a Senior Research Manager at Autodesk Research focused on data-driven design software for manufacturing. He holds a Ph.D. in Computational Design from Carnegie Mellon University and has presented his research internationally at conferences such as ICML, CVPR, ACM SIGGRAPH, ACM UIST, and ACM CHI. His work at Autodesk has won numerous awards including Fast Company Innovation By Design Honoree and Core77 Design Awards Research and Strategy Honoree.
Mina Konakovic Lukovic is an Assistant Professor at MIT, Department of Electrical Engineering and Computer Science. Her research focuses on computer graphics, computational fabrication, 3D geometry processing and machine learning, including architectural geometry and design of smart materials. She was a Schmidt Science Postdoctoral Fellow at MIT CSAIL working in the Computational Fabrication Group mentored by Prof. Dr. Wojciech Matusik. She completed her PhD in Computer Science at the Swiss Federal Institute of Technology Lausanne (EPFL), advised by Prof. Dr. Mark Pauly. She received her MS and BS both from the University of Belgrade, Faculty of Mathematics.
Shrikant Savant is the Director of Data Analysis and Science at Dassault Systèmes SolidWorks Corporation. He holds a Ph.D. from the Massachusetts Institute of Technology (MIT), specializing in Dynamics and Controls, and minored in Business Management at the Sloan School of Management. He also earned an M.S. from the University of California, Santa Barbara, and a B.Tech. from the Indian Institute of Technology. In his role at SolidWorks, Savant focuses on integrating artificial intelligence (AI) and machine learning (ML) into computer-aided design (CAD) processes. He emphasizes capturing and utilizing collective human knowledge to automate workflows and enhance the design process.
Wojciech Matusik is a Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory at MIT, where he leads the Computational Design and Fabrication Group and is a member of the Computer Graphics Group. Before coming to MIT, he worked at Mitsubishi Electric Research Laboratories, Adobe Systems, and Disney Research Zurich. He studied computer graphics at MIT and received his PhD in 2003. He also received a BS in EECS from the University of California at Berkeley in 1997 and MS in EECS from MIT in 2001. His research interests are in computer graphics, computational design and fabrication, computer vision, robotics, and HCI.
Schedule
Sessions will be announced after selecting the abstracts. The workshop schedule will be announced later; please note that lunch will be provided.
Venue
The workshop will take place at the MIT Media Lab (Building E14) located at 75 Amherst St, Cambridge MA 02139, USA
Sponsorship
This workshop is supported by the MIT IBK Program and the Morningside Academy for Design.
Organizing Committee
Alaa Algargoosh (Chair), Assistant Professor in Architecture at Virginia Tech and a Research Affiliate at MIT Media Lab.
Nikhil Singh, Assistant Professor in Computer Science at Dartmouth College.
Sarah Mokhtar, PhD Candidate in Architecture at MIT.
Mohammad Mohammadi Amiri, Assistant Professor in Computer Science at RPI.
Faez Ahmed, Assistant Professor in Mechanical Engineering at MIT.
Questions
If you have any questions, are interested in reviewing, or wish to contact the organizers, please reach out to genaifordesign@gmail.com.