activity
20242026
collaborators

5 papers

stat.CO2026

Subtrace-Conditional Validation of Simulation Models and Digital Twins

Mohammadmahdi Ghasemloo, David J. Eckman, Yaxian Li

Validating simulation models against historical output data is essential for their successful deployment in digital-twin environments. We propose a statistical validation framework…

stat.ML2026

Accelerating Reinforcement Learning Training Using Simulation Surrogate Models

Mohammadmahdi Ghasemloo, David J. Eckman, Yaxian Li

High-fidelity simulation models are widely used to analyze complex stochastic systems, but their high computational cost motivates the development of cheaper surrogate models that…

stat.CO2026

Quantifying and Attributing Submodel Uncertainty in Stochastic Simulation Models and Digital Twins

Mohammadmahdi Ghasemloo, David J. Eckman, Yaxian Li

Stochastic simulation is widely used to study complex systems composed of various interconnected subprocesses, such as input processes, routing and control logic, optimization rout…

cs.LG2025

Informed Forecasting: Leveraging Auxiliary Knowledge to Boost LLM Performance on Time Series Forecasting

Mohammadmahdi Ghasemloo, Alireza Moradi

With the widespread adoption of Large Language Models (LLMs), there is a growing need to establish best practices for leveraging their capabilities beyond traditional natural langu…

stat.ME2024

An Agglomerative Clustering of Simulation Output Distributions Using Regularized Wasserstein Distance

Mohammadmahdi Ghasemloo, David J. Eckman

Using statistical learning methods to analyze stochastic simulation outputs can significantly enhance decision-making by uncovering relationships between different simulated system…