Ilias Bilionis
Computer Science · Purdue University West Lafayette
Publications
205
Citations
3,240
Est. group size
~25
Recurring co-author estimate
Active years
17
Publishing since 2010
Ilias Bilionis works on combining statistics and machine learning with physics-based models to handle uncertainty in engineering systems. His work includes Bayesian methods for calibrating and estimating parameters in physical models, physics-informed neural networks, and applications such as heat transfer in manufacturing, engine emissions modeling, and material property prediction. Prospective students would likely engage with topics at the intersection of probabilistic modeling, scientific computing, and engineering design.
Publication output has fluctuated over the past decade, peaking around 2019 and again in 2025, with a relatively steady average of about 16 publications per year over the last five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- An Interpretation of the Brownian Bridge as a Physics-Informed Prior for the Poisson Equation
SIAM/ASA Journal on Uncertainty Quantification · 2026
- Bayesian neural networks with interpretable priors from Mercer kernels
Computer Methods in Applied Mechanics and Engineering · 2026
- Bayesian calibration of engine-out NOx models for engine-to-engine transferability
International Journal of Engine Research · 2026
- Coding-agents can replicate scientific machine learning papers
arXiv (Cornell University) · 2026
- Coding-agents can replicate scientific machine learning papers
arXiv (Cornell University) · 2026
- Causality enforcing parametric heat transfer solvers for evolving geometries in advanced manufacturing
Computer Methods in Applied Mechanics and Engineering · 2025
- Neural information field filter
Mechanical Systems and Signal Processing · 2025
- Control-Oriented Dynamic Computational Modeling
SSRN Electronic Journal · 2025
- Physics-informed neural networks to accelerate heat transfer predictions in additive manufacturing
2025
- Introduction to Data Science for Engineering Students
WORLD SCIENTIFIC eBooks · 2025
- An information field theory approach to Bayesian state and parameter estimation in dynamical systems
Journal of Computational Physics · 2024
- Learning to solve Bayesian inverse problems: An amortized variational inference approach using Gaussian and Flow guides
Journal of Computational Physics · 2024
- Uniqueness of MAP estimates for inverse problems under information field theory
arXiv (Cornell University) · 2024
- Neural information field filter
arXiv (Cornell University) · 2024
- Physics-Informed Information Field Theory Approach to Dynamical System Parameter and State Estimation in Path Space
Conference proceedings of the Society for Experimental Mechanics · 2024
- arXiv (Cornell University)×34
- SSRN Electronic Journal×9
- Building and Environment×7
- Journal of Computational Physics×6
- Energy and Buildings×6
- Matthew T. Pratola
Computer Science · The Ohio State University
- Kairui Hao
Computer Science · Purdue University West Lafayette
- Sharmila Karumuri
Decision Sciences · Purdue University West Lafayette
- Guang Lin
Physics and Astronomy · Purdue University West Lafayette
- Dongbin Xiu
Decision Sciences · 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 20, 2026.
Claim or correct this profile