LabCompass

Matthew T. Pratola

Computer Science · The Ohio State University

OpenAlex ORCID
Mid career · publishing since 2003
Gaussian Processes and Bayesian InferenceAdvanced Multi-Objective Optimization AlgorithmsStatistical Methods and InferenceProbabilistic and Robust Engineering DesignOptimal Experimental Design Methods

Publications

61

Citations

662

Est. group size

~1

Recurring co-author estimate

Active years

23

Publishing since 2003

Research summary
AI-generated

Matthew T. Pratola works on statistical and computational methods for uncertainty quantification, focusing on Bayesian tree-based models (such as Bayesian Additive Regression Trees) and Gaussian process methods for emulating complex computer simulations. His work is applied to problems in engineering design, climate modeling, and nuclear physics, where combining and calibrating computational models with data under uncertainty is important. This research blends statistics, machine learning, and computational methods with applications in the physical sciences.

Bayesian statistics and regression treesGaussian process emulation and modelingUncertainty quantification in computer simulationsModel mixing and calibration for scientific applicationsScalable Bayesian computation methods

Publication output has fluctuated over the last decade with peaks around 2019, 2021, and 2023, but has remained relatively steady overall without a clear long-term increase or decline.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 3.8/year recently
2017: 2 publications172018: 3 publications182019: 8 publications8192020: 2 publications202021: 8 publications8212022: 4 publications222023: 7 publications232024: 3 publications242025: 5 publications2526
Recent publications
Publishes in
  • arXiv (Cornell University)×16
  • Figshare×6
  • Technometrics×4
  • Physical Review C×2
  • Bayesian Analysis×2
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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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