Philip J. Smith
Engineering · The Ohio State University
Publications
482
Citations
12,299
Est. group size
—
Recurring co-author estimate
Active years
56
Publishing since 1971
This researcher's work spans combustion and energy systems engineering (such as coal and biomass power plants), Bayesian statistical methods for quantifying uncertainty in physical models, and human factors topics like air traffic management, human-automation interaction, and the effects of AI assistance on skill learning. A recurring focus is combining physics-based models with statistical (Bayesian) techniques to build 'digital twins' of industrial energy systems, alongside separate work on how humans interact with automated and AI-based tools in aviation and other applied settings.
Publication output has declined over the past decade, dropping from around 10-15 papers per year in 2017-2019 to an average of about 4-5 per year in the most recent five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Bridging the gap: Expert perspectives on the integration of urban and advanced air mobility
Journal of Air Transport Management · 2026
- Using Bayesian analysis to quantify and reduce uncertainty in experimental measurements — A narrow-angle radiometer case study
Measurement Energy · 2025
- Validation and Uncertainty Quantification of a digital model for an oxy-coal combustion power unit using Bayesian-based analysis
Energy · 2025
- The Effects of Artificial Intelligence Assistants on the Acquisition of Laparoscopic Surgical Spatial Navigation Skills
2025
- Does using artificial intelligence assistance accelerate skill decay and hinder skill development without performers’ awareness?
Cognitive Research Principles and Implications · 2024
- Cognitive Systems Engineering Issues in the Design of Machine Learning Systems
Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2024
- Improved spatial understanding of induced seismicity hazard from the discretization of a curved fault surface
Computational Geosciences · 2024
- Climate change—so what should we do about it?
Frontline Gastroenterology · 2024
- An approachable problem for the Bayesian analysis of a variety of uncertainties in hierarchical physical models
2024
- Validation and Uncertainty Analysis of a Digital Model for an Oxy-Fuel Power Unit Using Bayesian Methods
SSRN Electronic Journal · 2024
- Atikokan Digital Twin, Part B: Bayesian decision theory for process optimization in a biomass energy system
Applied Energy · 2023
- On the Path to Least Principal Stress Prediction: Quantifying the Impact of Borehole Logs on the Prediction Model
2023
- Strengthening the US Department of Energy’s Recruitment Pipeline: The DOE/NNSA Predictive Science Academic Alliance Program (PSAAP) Experience
Practice and Experience in Advanced Research Computing · 2023
- Use of Trajectory Option Sets to Support Collaborative Constraint Propagation
Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2023
- Are you not moved? Incorporating Sensorimotor Knowledge to Improve Metaphor Detection
2023
- The Cambridge Structural Database×9
- NASA Technical Reports Server (NASA)×7
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting×6
- Fuel×3
- Journal of Cognitive Engineering and Decision Making×3
- Carson D. Slabaugh
Engineering · Purdue University West Lafayette
- Ariff Magdoom Mahuthannan
Engineering · The Ohio State University
- Alexander J. Hodge
Engineering · Purdue University West Lafayette
- Aman Satija
Engineering · Purdue University West Lafayette
- Erik L. Braun
Engineering · Purdue University West Lafayette
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