Tom Peterka
Computer Science · The Ohio State University
Publications
84
Citations
1,764
Est. group size
~3
Recurring co-author estimate
Active years
20
Publishing since 2006
Tom Peterka works on managing and visualizing extremely large scientific datasets produced by high-performance computing (supercomputer) simulations. His work covers 'in situ' data processing (analyzing data as it's generated, without saving it all to disk first), scalable volume visualization (rendering 3D data for scientific images), and compact mathematical representations of data for faster storage and rendering. Prospective students would likely engage with software systems and algorithms for parallel and distributed computing applied to scientific data.
Publication output has declined from a peak of 8 papers/year in 2017-2018 to a lower, fluctuating rate of 2-6 papers/year in recent years, averaging 2.8 per year over the last five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Make the Fastest Faster: Importance Mask Synthesis for Interactive Volume Visualization using Reconstruction Neural Networks
arXiv (Cornell University) · 2025
- F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding
arXiv (Cornell University) · 2025
- Wilkins: HPC in situ workflows made easy
Frontiers in High Performance Computing · 2024
- Wilkins: HPC In Situ Workflows Made Easy
arXiv (Cornell University) · 2024
- Adaptive Multi-Resolution Encoding for Interactive Large-Scale Volume Visualization through Functional Approximation
arXiv (Cornell University) · 2024
- LowFive: In Situ Data Transport for High-Performance Workflows
2023
- Scalable Volume Visualization for Big Scientific Data Modeled by Functional Approximation
2023
- MFA-DVR: Direct Volume Rendering of MFA Models
arXiv (Cornell University) · 2022
- ASCR Workshop on In Situ Data Management: Enabling Scientific Discovery from Diverse Data Sources
2019
- The challenges of elastic in situ analysis and visualization
2019
- Spark-DIY: A Framework for Interoperable Spark Operations with High Performance Block-Based Data Models
2018
- Decaf: Decoupled Dataflows for In Situ High-Performance Workflows
2017
- Detection of Silent Data Corruption in Adaptive Numerical Integration Solvers
2017
- Manala: A Flexible Flow Control Library for Asynchronous Task Communication
2017
- CoSS
2017
- IEEE Transactions on Visualization and Computer Graphics×9
- arXiv (Cornell University)×9
- Lecture notes in computer science×4
- HAL (Le Centre pour la Communication Scientifique Directe)×2
- Communications of the ACM×1
- Suren Byna
Computer Science · The Ohio State University
- Pouya Kousha
Computer Science · The Ohio State University
- Dingwen Tao
Computer Science · Indiana University
- Jiannan Tian
Computer Science · Indiana University
- Sian Jin
Computer Science · Indiana 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.
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