N Attoh-Okine

N Attoh-Okine

University of Delaware

H-index: 33

North America-United States

About N Attoh-Okine

N Attoh-Okine, With an exceptional h-index of 33 and a recent h-index of 21 (since 2020), a distinguished researcher at University of Delaware, specializes in the field of Hilbert Huang Transform, Graphical Models, Big Data, Pavement Engineering, Resilience Engineering.

His recent articles reflect a diverse array of research interests and contributions to the field:

Special Section on Digital Twins: A New Frontier in Critical Infrastructure Protection and Resilience

Optimal Transport Theory for Railway Track Safety Applications

Covariate-shift generative adversarial network and railway track image analysis

Hilbert-Huang transformation (HHT) based texture profile analysis for continuous friction characterisation of pavements

Hybrid Reduction Techniques With Covariate Shift Optimization in High-Dimensional Track Geometry

Estimating peak floor acceleration using artificial neural networks

Hybrid rail track quality analysis using nonlinear dimension reduction technique with machine learning

Deep learning approach towards squat isolation in a multi-embedded track geometry defects

N Attoh-Okine Information

University

Position

Professor Civil and Environmental Eng. Newark DE

Citations(all)

4667

Citations(since 2020)

1903

Cited By

4290

hIndex(all)

33

hIndex(since 2020)

21

i10Index(all)

77

i10Index(since 2020)

46

Email

University Profile Page

University of Delaware

Google Scholar

View Google Scholar Profile

N Attoh-Okine Skills & Research Interests

Hilbert Huang Transform

Graphical Models

Big Data

Pavement Engineering

Resilience Engineering

Top articles of N Attoh-Okine

Title

Journal

Author(s)

Publication Date

Special Section on Digital Twins: A New Frontier in Critical Infrastructure Protection and Resilience

ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg

Nii Attoh-Okine

2024/3/1

Optimal Transport Theory for Railway Track Safety Applications

ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg

Nii O Attoh-Okine

2024/9/1

Covariate-shift generative adversarial network and railway track image analysis

Journal of Transportation Engineering, Part A: Systems

Ibrahim Balogun

Nii Attoh-Okine

2023/3/1

Hilbert-Huang transformation (HHT) based texture profile analysis for continuous friction characterisation of pavements

International Journal of Pavement Engineering

Wenying Yu

Joshua Qiang Li

Guangwei Yang

Kelvin CP Wang

Nii Attoh-Okine

2022/5/12

Hybrid Reduction Techniques With Covariate Shift Optimization in High-Dimensional Track Geometry

Journal of Computing and Information Science in Engineering

Ibrahim Balogun

Nii Attoh-Okine

2022/2/1

Estimating peak floor acceleration using artificial neural networks

Wael Aloqaily

Monique Head

Nii Attoh-Okine

2022

Hybrid rail track quality analysis using nonlinear dimension reduction technique with machine learning

Canadian Journal of Civil Engineering

Ahmed Lasisi

Nii Attoh-Okine

2021

Deep learning approach towards squat isolation in a multi-embedded track geometry defects

Ibrahim Balogun

Mark Leadingham

Dominique Gulliot

Nii Attoh-Okine

2021/12/15

Random Forest–Based Covariate Shift in Addressing Nonstationarity of Railway Track Data

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

Ibrahim Balogun

Nii Attoh-Okine

2021/9/1

Approximate Bayesian computation for railway track geometry parameter estimation

Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit

Grace Ashley

Nii Attoh-Okine

2021/9

Bayesian nonparametric approach to average annual daily traffic estimation for bridges

Transportation research record

Grace Ashley

Nii Attoh-Okine

2021/7

A Bayesian Nonparametric Approach to AADT Estimation for Bridges

Grace Ashley

Nii Attoh-Okine

2021

Relationship Between Track Geometry Defects and Measured Track Subsurface Condition

Allan M Zarembski

Dennis Yurlov

Joseph Palese

Nii Attoh-Okine

2020/2/1

Predicting Track Geometry Defect Probability Based on Tie Condition Using Pattern Recognition Technique

Ali Alsahli

Allan M Zarembski

Nii Attoh-Okine

2020/11/16

Risk and advantages of federated learning for health care data collaboration

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

Anna Bogdanova

Nii Attoh-Okine

Tetsuya Sakurai

2020/9/1

Special Collection on Resilience Quantification and Modeling for Decision Making

Gian Paolo Cimellaro

Nii O Attoh-Okine

2020/9/1

Methods for aligning near-continuous railway track inspection data

Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit

Joseph W Palese

Allan M Zarembski

Nii O Attoh-Okine

2020/8

An unsupervised learning framework for track quality index and safety

Transportation Infrastructure Geotechnology

Ahmed Lasisi

Nii Attoh-Okine

2020/3

See List of Professors in N Attoh-Okine University(University of Delaware)