activity
20202026
most citedDeep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems

367 citations · 857 across the 15 of their papers we have counts for

collaborators

15 papers

cs.CE2026

One-Shot Generative Design for Disordered Metamaterials via Self-Organizing Neural Cellular Automata

Yujie Xiang, Liwei Wang

Disordered metamaterials feature microstructures with inherent randomness and irregularity, enabling them to achieve broader property coverage and superior performance unavailable…

cs.CE2025★ 1 cited

Data-Driven Topology Optimization for Multiscale Biomimetic Spinodal Design

Shiguang Deng, Doksoo Lee, Aaditya Chandrasekhar +4

Spinodoid architected materials have drawn significant attention due to their unique nature in stochasticity, aperiodicity, and bi-continuity. Compared to classic periodic truss-,…

stat.ML2023★ 4 cited

Mixed-Variable Global Sensitivity Analysis For Knowledge Discovery And Efficient Combinatorial Materials Design

Yigitcan Comlek, Liwei Wang, Wei Chen

Global Sensitivity Analysis (GSA) is the study of the influence of any given inputs on the outputs of a model. In the context of engineering design, GSA has been widely used to und…

stat.ML2023★ 26 cited

A Latent Variable Approach for Non-Hierarchical Multi-Fidelity Adaptive Sampling

Yi-Ping Chen, Liwei Wang, Yigitcan Comlek +1

Multi-fidelity (MF) methods are gaining popularity for enhancing surrogate modeling and design optimization by incorporating data from various low-fidelity (LF) models. While most…

physics.app-ph2023

Physics-aware differentiable design of magnetically actuated kirigami for shape morphing

Liwei Wang, Yilong Chang, Shuai Wu +2

Shape morphing that transforms morphologies in response to stimuli is crucial for future multifunctional systems. While kirigami holds great promise in enhancing shape-morphing, ex…

cs.CE2023★ 229 cited

Data-Driven Design for Metamaterials and Multiscale Systems: A Review

Doksoo Lee, Wei Wayne Chen, Liwei Wang +2

Metamaterials are artificial materials designed to exhibit effective material parameters that go beyond those found in nature. Composed of unit cells with rich designability that a…

cs.CE2022★ 35 cited

t-METASET: Tailoring Property Bias of Large-Scale Metamaterial Datasets through Active Learning

Doksoo Lee, Yu-Chin Chan, Wei Wayne Chen +3

Inspired by the recent achievements of machine learning in diverse domains, data-driven metamaterials design has emerged as a compelling paradigm that can unlock the potential of m…

cs.CE2021

Enhancing Data-driven Multiscale Topology Optimization with Generalized De-homogenization

Liwei Wang, Zhao Liu, Daicong Da +3

De-homogenization is becoming an effective method to significantly expedite the design of high-resolution multiscale structures, but existing methods have thus far been confined to…

cs.CE2021★ 30 cited

Remixing Functionally Graded Structures: Data-Driven Topology Optimization with Multiclass Shape Blending

Yu-Chin Chan, Daicong Da, Liwei Wang +1

To create heterogeneous, multiscale structures with unprecedented functionalities, recent topology optimization approaches design either fully aperiodic systems or functionally gra…

physics.app-ph2021★ 107 cited

Mechanical Cloak via Data-Driven Aperiodic Metamaterial Design

Liwei Wang, Jagannadh Boddapati, Ke Liu +3

Mechanical cloaks are materials engineered to manipulate the elastic response around objects to make them indistinguishable from their homogeneous surroundings. Typically, methods…

cs.LG2021★ 2 cited

Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors

Liwei Wang, Suraj Yerramilli, Akshay Iyer +3

Scientific and engineering problems often require the use of artificial intelligence to aid understanding and the search for promising designs. While Gaussian processes (GP) stand…

cs.CE2021★ 4 cited

Data-Driven Multiscale Design of Cellular Composites with Multiclass Microstructures for Natural Frequency Maximization

Liwei Wang, Anton van Beek, Daicong Da +3

For natural frequency optimization of engineering structures, cellular composites have been shown to possess an edge over solid. However, existing multiscale design methods for cel…

cs.CE2020★ 367 cited

Deep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems

Liwei Wang, Yu-Chin Chan, Faez Ahmed +3

Metamaterials are emerging as a new paradigmatic material system to render unprecedented and tailorable properties for a wide variety of engineering applications. However, the inve…

cs.CE2020★ 5 cited

Data-Driven Topology Optimization with Multiclass Microstructures using Latent Variable Gaussian Process

Liwei Wang, Siyu Tao, Ping Zhu +1

The data-driven approach is emerging as a promising method for the topological design of multiscale structures with greater efficiency. However, existing data-driven methods mostly…

cs.CE2020★ 47 cited

METASET: Exploring Shape and Property Spaces for Data-Driven Metamaterials Design

Yu-Chin Chan, Faez Ahmed, Liwei Wang +1

Data-driven design of mechanical metamaterials is an increasingly popular method to combat costly physical simulations and immense, often intractable, geometrical design spaces. Us…