DeCoDE Lab is based in the Mechanical Engineering department at MIT. Our vision is to create a world where humans and AI design together to solve our biggest challenges. We study machine learning and optimization methods to better design complex mechanical systems and assist teams of human designers in creating better products.
Our work lies at the intersections of Mechanical Engineering, Artificial Intelligence, and Human-Computer Interaction. A few questions we are interested in: How can algorithms synthesize high-performing designs that meet real-world requirements? How can algorithms help discover or create creative designs that have never been seen before? How can we enable distributed teams of people to create better products? How can we design, develop, and deploy advanced engineering material systems for complex non-linear inverse problems? How can we quickly and reliably evaluate thousands of ideas to accelerate innovation? While these questions address different areas, our underlying approach is to mathematically characterize these questions as generalizable machine learning and optimization problems, make testable predictions for new problems, and tie together or understand individual empirical results that researchers have generated.
Our techniques apply to a wide range of problems in Engineering. We aim to transform the way humans design products and measure our success by the impact of our work on society. We believe in reproducible and open-source science and do our part by making most of our research code and papers available online.
We have an available PostDoc position in deep generative models and geometric deep learning. Apply here.
If you are interested in joining the DeCoDE lab, drop me an email with the following text in your subject line "Join DeCoDE:" followed by the position you are interested in (for example, a postdoc, intern, visiting student, etc.).
LINKS dataset - A dataset of 100 million planar linkage mechanisms and 1.1 billion coupler curves obtained from kinematic simulations. The dataset contains curated curves, another 100 million negative samples, and publicly available simulation software.
BIKED dataset - A dataset of 4500 community-designed bicycles in tabular and image format, along with images corresponding to different bike parts for each bicycle.
FRAMED dataset - A dataset of 4500 bicycle frames and ten performance metrics obtained from physical simulations.
Aircraft dataset - A dataset of 4045 3D aircraft models from Shapenet and their lift/drag performance values.
Airfoil dataset - A synthetic dataset of 48,503 airfoils and their aerodynamic performance computed using OpenFOAM.
Faez Ahmedd'Arbeloff Career Development Assistant Professor Department of Mechanical Engineering Massachusetts Institute of Technology Email: faez at mit dot edu Faez Ahmed is the d'Arbeloff career development assistant professor in the Department of Mechanical Engineering at MIT, where he leads the Design Computation and Digital Engineering (DeCoDE) lab. His research focuses on developing new machine learning and optimization methods to study complex engineering design problems. Before joining MIT, Ahmed was a postdoctoral fellow at Northwestern University and completed his Ph.D. in mechanical engineering at the University of Maryland. He also worked in the railway and mining industry in Australia, where he pioneered data-driven predictive maintenance and renewal planning efforts.
Congratulations Amin for recieving the 2022 Mathworks Fellowship at MIT.
Congratulations Noah and Lyle for winning the third prize at two ASME IDETC Hackathons.
Dr. Ahmed won the Honorable Mention award in the JMD editors’ choice award for their PaDGAN paper.
Congratulations Kristen for completing her master's degree in MechE.
Dr. Ahmed received the 3M non-tenured faculty award.
Congratulations Noah for winning the ASME student poster travel award.
Congratulations Lyle for passing MechE qualifying exams and becoming DeCoDE lab's first Ph.D. candidate.
Congratulations Lyle and Amin for completing their master's degree in MechE.
Congratulations Lyle for honorable mention in the NSF GRFP award.
Congratulations Kristen for recieving the NSF GRFP award.
Congratulations Amin for recieving the 2021 Mathworks Fellowship at MIT.
Dr. Ahmed recieved the 2022 Alumni Excellence Research Award from the UMD Alumni Association.