Erin Santini-Bell

Professor

University of New Hampshire

United States

Research Interests

Explore related searches

Professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Dr. Erin Santini-Bell is a Professor at the University of New Hampshire, USA. Her research focuses on structural engineering and asset management, particularly in the context of bridge systems and artificial intelligence applications. Recent publications include topics on neural networks for structural analysis, deep reinforcement learning for maintenance strategies, and methodologies for optimizing transportation assets.

Articles (10)

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2020

Year:

2020

Collaborators (2)

Saeed Eftekhar Azam

Assistant Professor

University of New Hampshire

UNITED STATES

View details

Fei Han

Assistant Professor

University of New Hampshire

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Erin Santini-Bell

Research Interests

Explore related searches

Contact this professor

About

Articles (10)

Automated structural parameter estimation of semi-rigid complex joints in a benchmark laboratory steel grid by experimental modal analysis

Robustness analysis of multi-layer feedforward artificial neural networks for finite element model updating

Towards equitable infrastructure asset management: Scour maintenance strategy for aging bridge systems in flood-prone zones using deep reinforcement learning

Modal–based uncertainty quantification for deterministically estimated structural parameters in low-fidelity model updating of complex connections

Bridge-Level Optimization Module for Planning and Programming

Element-Based Multi-Objective Optimization Methodology Supporting a Transportation Asset Management Framework for Bridge Planning and Programming

Element-Level Optimization Module for Bridge Planning and Programming

Fatigue crack detection in welded structural components of steel bridges using artificial neural network

Views of the Highway: Infrastructure Reality, Perceptions, and Politics

Comparison between a Linear Regression and an Artificial Neural Network Model to Detect and Localize Damage in the Powder Mill Bridge

Collaborators (2)

Saeed Eftekhar Azam

Fei Han

Make your next move.