Skylar W. Wurster
Computer Science · The Ohio State University
Publications
19
Citations
117
Est. group size
~4
Recurring co-author estimate
Active years
9
Publishing since 2018
Skylar W. Wurster works on scientific visualization and machine learning methods for representing and exploring large, complex datasets, such as those from ocean simulations. A major focus is on neural implicit representations (compact neural network models that encode data like 3D scenes or images) and techniques to make them faster, more accurate, and scalable for scientific visualization tasks.
Publication output has been relatively steady with modest fluctuations over the last decade, averaging about 2-3 papers per year in the most recent five years without a clear long-term increase or decline.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Refine Now, Query Fast: A Decoupled Refinement Paradigm for Implicit Neural Fields
Open MIND · 2026
- Refine Now, Query Fast: A Decoupled Refinement Paradigm for Implicit Neural Fields
arXiv (Cornell University) · 2026
- AMGSRN++: Improved Adaptive SRN for Scientific Visualization
2025
- Regularized Multi-Decoder Ensemble for an Error-Aware Scene Representation Network
IEEE Transactions on Visualization and Computer Graphics · 2024
- Gabor Splatting for High-Quality Gigapixel Image Representations
2024
- Regularized Multi-Decoder Ensemble for an Error-Aware Scene Representation Network
arXiv (Cornell University) · 2024
- Adaptively Placed Multi-Grid Scene Representation Networks for Large-Scale Data Visualization
IEEE Transactions on Visualization and Computer Graphics · 2023
- Neural Stream Functions
2023
- Adaptively Placed Multi-Grid Scene Representation Networks for Large-Scale Data Visualization
arXiv (Cornell University) · 2023
- GNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations
IEEE Transactions on Visualization and Computer Graphics · 2022
- Deep Hierarchical Super Resolution for Scientific Data
IEEE Transactions on Visualization and Computer Graphics · 2022
- Reinforcement Learning for Load-Balanced Parallel Particle Tracing
IEEE Transactions on Visualization and Computer Graphics · 2022
- Deep Hierarchical Super-Resolution for Scientific Data Reduction and Visualization
arXiv (Cornell University) · 2021
- Human Gist Processing Augments Deep Learning Breast Cancer Risk Assessment
arXiv (Cornell University) · 2019
- Human Gist Processing Augments Deep Learning Breast Cancer Risk\n Assessment
arXiv (Cornell University) · 2019
- arXiv (Cornell University)×8
- IEEE Transactions on Visualization and Computer Graphics×5
- Open MIND×1
- Jia‐Bin Huang
Computer Science · Purdue University West Lafayette
- Voicu Popescu
Computer Science · Purdue University West Lafayette
- Andrew Jones
Computer Science · Indiana University
- James Davis
Computer Science · Purdue University West Lafayette
- Jinsu Yoo
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile