Lyle Regenwetter — accepted AI-conference papers

2025

BikeBench: A Bicycle Design Benchmark for Generative Models with Objectives and Constraints

Lyle Regenwetter, Yazan Abu Obaideh, Fabien M. C. Chiotti, Ioanna Lykourentzou, Faez Ahmed

NeurIPS 2025poster

We introduce BikeBench, an engineering design benchmark for evaluating generative models on problems with multiple real-world objectives and constraints. As generative AI's reach continues to grow, evaluating its capability to understand physical laws, human guidelines, and hard constraints grows in…

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2025

Optimize Any Topology: A Foundation Model for Shape- and Resolution-Free Structural Topology Optimization

Amin Heyrani Nobari, Lyle Regenwetter, Cyril Picard, Ligong Han, Faez Ahmed

NeurIPS 2025poster

Structural topology optimization (TO) is central to engineering design but remains computationally intensive due to complex physics and hard constraints. Existing deep-learning methods are limited to fixed square grids, a few hand-coded boundary conditions, and post-hoc optimization, preventing gene…

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