Carnegie Mellon University · Mechanical Engineering
Artificial intelligence for engineering design and discovery.
At the Visual Design and Engineering Laboratory, we develop computational methods for understanding, designing, and improving engineered systems. Our work brings together artificial intelligence, geometric modeling, simulation, optimization, and manufacturing.
Featured Research
Selected recent papers
Predicting where peptides bind to proteins
A geometry-aware foundation model identifies peptide binding sites from molecular sequences.
Scaling AI models to million-point simulations
Low-rank attention enables learning from large-scale engineering meshes.
Designing parts around manufacturing resources
A framework jointly considers engineering requirements, costs, lead times, and supplier capabilities when generating parts.
Optimizing parts for efficient milling
Neural implicit fields produce structurally efficient parts with surfaces better suited to subtractive machining.
Designing connected microstructures with neural networks
A continuous neural representation optimizes spatially varying microstructures while maintaining connections between neighboring cells.
Predicting manufacturability with limited training data
Self-supervised learning from CAD geometry improves estimates of machining time, printing time, stress, and build risks.
News
Updates from the lab