Amir Barati Farimani

New methods improve adsorption energy prediction for catalysts using machine learning.

GradNav helps scientists study molecular behavior more efficiently.

This research focuses on detecting porosity in additive manufacturing with thermal images and AI.

This article discusses the role of machine learning in improving additive manufacturing processes.

Combining Large Language Models with data to discover scientific equations effectively.

CaFA brings efficiency and accuracy to global weather predictions with machine learning.

Research explores spatter behavior to improve additive manufacturing quality.

AMGPT provides precise support for researchers in metal additive manufacturing.

Multi-Peptide combines data models to enhance peptide behavior predictions.

Researchers improve neural PDE models using pretrained lower-dimensional equations for better performance.

New framework uses AI to enhance error detection in 3D printing.

Study reveals improved accuracy in predictions using ensemble methods with diffusion models.

A new approach enhances airfoil designs through machine learning and data-driven methods.

AbGPT aids in creating effective antibody sequences using advanced machine learning techniques.

PLATO enables robots to understand natural language for better task execution.

A new method enhances metal part monitoring during LPBF using deep learning for image improvement.

BAPULM simplifies drug interaction predictions, speeding up medicine development.

Neural surrogates enhance simulation accuracy by predicting changes over time.