205 citations · 429 across the 4 of their papers we have counts for
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Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformers
Li Zheng, Siddhant Kumar, Dennis M. Kochmann
Generative machine learning models have revolutionized material discovery by capturing complex structure-property relationships, yet extending these approaches to the inverse desig…
HyperCAN: Hypernetwork-Driven Deep Parameterized Constitutive Models for Metamaterials
Li Zheng, Dennis M. Kochmann, Siddhant Kumar
We introduce HyperCAN, a machine learning framework that utilizes hypernetworks to construct adaptable constitutive artificial neural networks for a wide range of beam-based metama…
Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling
Li Zheng, Konstantinos Karapiperis, Siddhant Kumar +1
The rise of machine learning has fueled the discovery of new materials and, especially, metamaterials--truss lattices being their most prominent class. While their tailorable prope…
Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy
Li Zheng, Siddhant Kumar, Dennis M. Kochmann
We present a two-scale topology optimization framework for the design of macroscopic bodies with an optimized elastic response, which is achieved by means of a spatially-variant ce…