12 citations · 24 across the 42 of their papers we have counts for
15 papers · 1 filter
KEO: Knowledge Extraction on OMIn via Knowledge Graphs and RAG for Safety-Critical Aviation Maintenance
Kuangshi Ai, Jonathan A. Karr, Meng Jiang +2
We present Knowledge Extraction on OMIn (KEO), a domain-specific knowledge extraction and reasoning framework with large language models (LLMs) in safety-critical contexts. Using t…
An Evaluation-Centric Paradigm for Scientific Visualization Agents
Kuangshi Ai, Haichao Miao, Zhimin Li +2
Recent advances in multi-modal large language models (MLLMs) have enabled increasingly sophisticated autonomous visualization agents capable of translating user intentions into dat…
TopoImages: Incorporating Local Topology Encoding into Deep Learning Models for Medical Image Classification
Pengfei Gu, Hongxiao Wang, Yejia Zhang +3
Topological structures in image data, such as connected components and loops, play a crucial role in understanding image content (e.g., biomedical objects). % Despite remarkable su…
TexGS-VolVis: Expressive Scene Editing for Volume Visualization via Textured Gaussian Splatting
Kaiyuan Tang, Kuangshi Ai, Jun Han +1
Advancements in volume visualization (VolVis) focus on extracting insights from 3D volumetric data by generating visually compelling renderings that reveal complex internal structu…
AortaDiff: Volume-Guided Conditional Diffusion Models for Multi-Branch Aortic Surface Generation
Delin An, Pan Du, Jian-Xun Wang +1
Accurate 3D aortic construction is crucial for clinical diagnosis, preoperative planning, and computational fluid dynamics (CFD) simulations, as it enables the estimation of critic…
VolSegGS: Segmentation and Tracking in Dynamic Volumetric Scenes via Deformable 3D Gaussians
Siyuan Yao, Chaoli Wang
Visualization of large-scale time-dependent simulation data is crucial for domain scientists to analyze complex phenomena, but it demands significant I/O bandwidth, storage, and co…
NLI4VolVis: Natural Language Interaction for Volume Visualization via LLM Multi-Agents and Editable 3D Gaussian Splatting
Kuangshi Ai, Kaiyuan Tang, Chaoli Wang
Traditional volume visualization (VolVis) methods, like direct volume rendering, suffer from rigid transfer function designs and high computational costs. Although novel view synth…
MC-INR: Efficient Encoding of Multivariate Scientific Simulation Data using Meta-Learning and Clustered Implicit Neural Representations
Hyunsoo Son, Jeonghyun Noh, Suemin Jeon +2
Implicit Neural Representations (INRs) are widely used to encode data as continuous functions, enabling the visualization of large-scale multivariate scientific simulation data wit…
EcoSphere: A Decision-Support Tool for Automated Carbon Emission and Cost Optimization in Sustainable Urban Development
Siavash Ghorbany, Ming Hu, Siyuan Yao +2
The construction industry is a major contributor to global greenhouse gas emissions, with embodied carbon being a key component. This study develops EcoSphere, an innovative softwa…
iVR-GS: Inverse Volume Rendering for Explorable Visualization via Editable 3D Gaussian Splatting
Kaiyuan Tang, Siyuan Yao, Chaoli Wang
In volume visualization, users can interactively explore the three-dimensional data by specifying color and opacity mappings in the transfer function (TF) or adjusting lighting par…
AI-Powered Automated Model Construction for Patient-Specific CFD Simulations of Aortic Flows
Pan Du, Delin An, Chaoli Wang +1
Image-based modeling is essential for understanding cardiovascular hemodynamics and advancing the diagnosis and treatment of cardiovascular diseases. Constructing patient-specific…
ViSNeRF: Efficient Multidimensional Neural Radiance Field Representation for Visualization Synthesis of Dynamic Volumetric Scenes
Siyuan Yao, Yunfei Lu, Chaoli Wang
Domain scientists often face I/O and storage challenges when keeping raw data from large-scale simulations. Saving visualization images, albeit practical, is limited to preselected…
Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation
Maizhe Yang, Kaiyuan Tang, Chaoli Wang
Implicit neural representation (INR) has emerged as a promising solution for encoding volumetric data, offering continuous representations and seamless compatibility with the volum…
Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation
Delin An, Pan Du, Pengfei Gu +2
Accurate segmentation of the aorta and its associated arch branches is crucial for diagnosing aortic diseases. While deep learning techniques have significantly improved aorta segm…
SurfPatch: Enabling Patch Matching for Exploratory Stream Surface Visualization
Delin An, Chaoli Wang
Unlike their line-based counterparts, surface-based techniques have yet to be thoroughly investigated in flow visualization due to their significant placement, speed, perception, a…