145 citations · 339 across the 28 of their papers we have counts for
31 papers
Ortho2CAD: 3D CAD generation from orthographic drawings using vision language models
Aditya Joglekar, Amit Regmi, Kenji Shimada +1
Engineering design intent is often communicated through rasterized orthographic drawings. However, downstream workflows require editable and parametrically defined 3D computer-aide…
Natural-Language to SysMLv2 Translation via Conformance-Driven Iterative Refinement
Chance LaVoie, Eladio Andujar Lugo, Taylan G. Topcu +1
Model-Based Systems Engineering (MBSE) relies on formal system models as primary technical artifacts for representing requirements, structure, and behavior across the system lifecy…
MDDM: A Molecular Dynamics Diffusion Model to Predict Particle Self-Assembly
Kevin Ferguson, Yu-hsuan Chen, Levent Burak Kara
The discovery and study of new material systems rely on molecular simulations that often come with significant computational expense. We propose MDDM, a Molecular Dynamics Diffusio…
Topology-Agnostic Graph U-Nets for Scalar Field Prediction on Unstructured Meshes
Kevin Ferguson, Yu-hsuan Chen, Yiming Chen +3
Machine-learned surrogate models to accelerate lengthy computer simulations are becoming increasingly important as engineers look to streamline the product design cycle. In many ca…
Scalar Field Prediction on Meshes Using Interpolated Multi-Resolution Convolutional Neural Networks
Kevin Ferguson, Andrew Gillman, James Hardin +1
Scalar fields, such as stress or temperature fields, are often calculated in shape optimization and design problems in engineering. For complex problems where shapes have varying t…
Generative Manufacturing: A requirements and resource-driven approach to part making
Hongrui Chen, Aditya Joglekar, Zack Rubinstein +6
Advances in CAD and CAM have enabled engineers and design teams to digitally design parts with unprecedented ease. Software solutions now come with a range of modules for optimizin…
VIRL: Volume-Informed Representation Learning towards Few-shot Manufacturability Estimation
Yu-hsuan Chen, Jonathan Cagan, Levent Burak kara
Designing for manufacturing poses significant challenges in part due to the computation bottleneck of Computer-Aided Manufacturing (CAM) simulations. Although deep learning as an a…
SNF-ROM: Projection-based nonlinear reduced order modeling with smooth neural fields
Vedant Puri, Aviral Prakash, Levent Burak Kara +1
Reduced order modeling lowers the computational cost of solving PDEs by learning a low-order spatial representation from data and dynamically evolving these representations using m…
Multi-scale Topology Optimization using Neural Networks
Hongrui Chen, Xingchen Liu, Levent Burak Kara
A long-standing challenge is designing multi-scale structures with good connectivity between cells while optimizing each cell to reach close to the theoretical performance limit. W…
Curve-based Neural Style Transfer
Yu-hsuan Chen, Levent Burak Kara, Jonathan Cagan
This research presents a new parametric style transfer framework specifically designed for curve-based design sketches. In this research, traditional challenges faced by neural sty…
Inference of highly time-resolved melt pool visual characteristics and spatially-dependent lack-of-fusion defects in laser powder bed fusion using acoustic and thermal emission data
Haolin Liu, Christian Gobert, Kevin Ferguson +5
With a growing demand for high-quality fabrication, the interest in real-time process and defect monitoring of laser powder bed fusion (LPBF) has increased, leading manufacturers t…
Automating Style Analysis and Visualization With Explainable AI -- Case Studies on Brand Recognition
Yu-hsuan Chen, Levent Burak Kara, Jonathan Cagan
Incorporating style-related objectives into shape design has been centrally important to maximize product appeal. However, stylistic features such as aesthetics and semantic attrib…
Topology Optimization using Neural Networks with Conditioning Field Initialization for Improved Efficiency
Hongrui Chen, Aditya Joglekar, Levent Burak Kara
We propose conditioning field initialization for neural network based topology optimization. In this work, we focus on (1) improving upon existing neural network based topology opt…
DMF-TONN: Direct Mesh-free Topology Optimization using Neural Networks
Aditya Joglekar, Hongrui Chen, Levent Burak Kara
We propose a direct mesh-free method for performing topology optimization by integrating a density field approximation neural network with a displacement field approximation neural…
Target specific peptide design using latent space approximate trajectory collector
Tong Lin, Sijie Chen, Ruchira Basu +3
Despite the prevalence and many successes of deep learning applications in de novo molecular design, the problem of peptide generation targeting specific proteins remains unsolved.…
Component Segmentation of Engineering Drawings Using Graph Convolutional Networks
Wentai Zhang, Joe Joseph, Yue Yin +5
We present a data-driven framework to automate the vectorization and machine interpretation of 2D engineering part drawings. In industrial settings, most manufacturing engineers st…
Hierarchical Automatic Power Plane Generation with Genetic Optimization and Multilayer Perceptron
Haiguang Liao, Vinay Patil, Xuliang Dong +5
We present an automatic multilayer power plane generation method to accelerate the design of printed circuit boards (PCB). In PCB design, while automatic solvers have been develope…
Concurrent build direction, part segmentation, and topology optimization for additive manufacturing using neural networks
Hongrui Chen, Aditya Joglekar, Kate S. Whitefoot +1
We propose a neural network-based approach to topology optimization that aims to reduce the use of support structures in additive manufacturing. Our approach uses a network archite…
Placement in Integrated Circuits using Cyclic Reinforcement Learning and Simulated Annealing
Dhruv Vashisht, Harshit Rampal, Haiguang Liao +4
Physical design and production of Integrated Circuits (IC) is becoming increasingly more challenging as the sophistication in IC technology is steadily increasing. Placement has be…
Track-Assignment Detailed Routing Using Attention-based Policy Model With Supervision
Haiguang Liao, Qingyi Dong, Weiyi Qi +2
Detailed routing is one of the most critical steps in analog circuit design. Complete routing has become increasingly more challenging in advanced node analog circuits, making adva…
StressGAN: A Generative Deep Learning Model for 2D Stress Distribution Prediction
Haoliang Jiang, Zhenguo Nie, Roselyn Yeo +2
Using deep learning to analyze mechanical stress distributions has been gaining interest with the demand for fast stress analysis methods. Deep learning approaches have achieved ex…
Attention Routing: track-assignment detailed routing using attention-based reinforcement learning
Haiguang Liao, Qingyi Dong, Xuliang Dong +5
In the physical design of integrated circuits, global and detailed routing are critical stages involving the determination of the interconnected paths of each net on a circuit whil…
TopologyGAN: Topology Optimization Using Generative Adversarial Networks Based on Physical Fields Over the Initial Domain
Zhenguo Nie, Tong Lin, Haoliang Jiang +1
In topology optimization using deep learning, load and boundary conditions represented as vectors or sparse matrices often miss the opportunity to encode a rich view of the design…
Structural Design Using Laplacian Shells
Erva Ulu, James McCann, Levent Burak Kara
We introduce a method to design lightweight shell objects that are structurally robust under the external forces they may experience during use. Given an input 3D model and a gener…