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2025

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Rising Stars

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5018
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Engineering and Technology

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38
Citations
7062
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  • 2025 - Research.com Rising Stars Award

Overview

Sujith Mangalathu is affiliated with the Georgia Institute of Technology in the United States. Their research primarily focuses on engineering, with a specialization in civil and structural engineering. Their scholarly output covers a range of topics related to structural health monitoring, seismic performance, infrastructure maintenance, and the structural behavior of reinforced concrete.

The scientist has contributed significantly to the understanding of structural health monitoring techniques and seismic performance and analysis. Their research interests extend into infrastructure maintenance and monitoring, concrete corrosion and durability, as well as responses of structures to dynamic loads and dam engineering and safety.

Frequent co-authors in their collaborative work include:

  • Jong-Su Jeon
  • Muhamed Safeer Pandikkadavath
  • Robin Davis
  • A. Anisha
  • S. Somala

They have published extensively in several academic journals, with notable recurring publication venues including:

  • Engineering Structures
  • Structures
  • Earthquake Engineering & Structural Dynamics
  • Journal of Building Engineering
  • Journal of Structural Engineering

The following recent papers exemplify their research contributions:

  • Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach, 2020, Engineering Structures
  • Data-driven machine-learning-based seismic failure mode identification of reinforced concrete shear walls, 2020, Engineering Structures

Other notable papers relevant to their research domain, including coauthor works, are:

  • Interpretable XGBoost-SHAP Machine-Learning Model for Shear Strength Prediction of Squat RC Walls, 2021, Journal of Structural Engineering
  • Data-driven shear strength prediction of steel fiber reinforced concrete beams using machine learning approach, 2021, Engineering Structures
  • Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements, 2021, Engineering Structures

Best Publications

  • Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach

    Sujith Mangalathu;Seong Hoon Hwang;Jong Su Jeon

  • Interpretable XGBoost-SHAP Machine-Learning Model for Shear Strength Prediction of Squat RC Walls

    De-Cheng Feng;Wen-Jie Wang;Sujith Mangalathu;Ertugrul Taciroglu

  • Classification of failure mode and prediction of shear strength for reinforced concrete beam-column joints using machine learning techniques

    Sujith Mangalathu;Jong-Su Jeon

  • Data-driven shear strength prediction of steel fiber reinforced concrete beams using machine learning approach

    Jesika Rahman;Jesika Rahman;Khondaker Sakil Ahmed;Nafiz Imtiaz Khan;Kamrul Islam;Kamrul Islam

  • Data-driven machine-learning-based seismic failure mode identification of reinforced concrete shear walls

    Sujith Mangalathu;Hansol Jang;Seong Hoon Hwang;Jong Su Jeon

  • Artificial neural network based multi-dimensional fragility development of skewed concrete bridge classes

    Sujith Mangalathu;Gwanghee Heo;Jong Su Jeon

  • Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements

    De-Cheng Feng;Wen-Jie Wang;Sujith Mangalathu;Gang Hu

  • Classifying Earthquake Damage to Buildings Using Machine Learning

    Sujith Mangalathu;Han Sun;Chukwuebuka C. Nweke;Zhengxiang Yi

  • Machine Learning–Based Failure Mode Recognition of Circular Reinforced Concrete Bridge Columns: Comparative Study

    Sujith Mangalathu;Jong-Su Jeon

  • Rapid seismic damage evaluation of bridge portfolios using machine learning techniques

    Sujith Mangalathu;Seong-Hoon Hwang;Eunsoo Choi;Jong-Su Jeon

  • Critical uncertainty parameters influencing seismic performance of bridges using Lasso regression

    Sujith Mangalathu;Jong Su Jeon;Reginald DesRoches

  • Machine learning-based approaches for seismic demand and collapse of ductile reinforced concrete building frames

    Seong Hoon Hwang;Sujith Mangalathu;Jiuk Shin;Jong Su Jeon

  • Data‐driven rapid damage evaluation for life‐cycle seismic assessment of regional reinforced concrete bridges

    Unknown

  • Explainable machine learning models for punching shear strength estimation of flat slabs without transverse reinforcement

    Sujith Mangalathu;Hanbyeol Shin;Eunsoo Choi;Jong Su Jeon

  • Machine-learning interpretability techniques for seismic performance assessment of infrastructure systems

    Sujith Mangalathu;Karthika Karthikeyan;De-Cheng Feng;Jong-Su Jeon

  • Stripe-based fragility analysis of multispan concrete bridge classes using machine learning techniques

    Sujith Mangalathu;Jong Su Jeon

  • Predicting the dissolution kinetics of silicate glasses using machine learning

    N. M. Anoop Krishnan;Sujith Mangalathu;Morten Mattrup Smedskjær;Adama Tandia

  • Deep learning-based classification of earthquake-impacted buildings using textual damage descriptions

    Sujith Mangalathu;Henry V. Burton

  • Parameterized Seismic Fragility Curves for Curved Multi-frame Concrete Box-Girder Bridges Using Bayesian Parameter Estimation

    Jong-Su Jeon;Sujith Mangalathu;Junho Song;Reginald Desroches

  • Explainable machine learning models for predicting the axial compression capacity of concrete filled steel tubular columns

    Unknown

  • Review of strength models for masonry spandrels

    Katrin Beyer;Sujith Mangalathu

  • Fragility analysis of gray iron pipelines subjected to tunneling induced ground settlement

    Pengpeng Ni;Pengpeng Ni;Sujith Mangalathu

  • ANCOVA-based grouping of bridge classes for seismic fragility assessment

    Sujith Mangalathu;Jong-Su Jeon;Jamie E. Padgett;Reginald DesRoches

  • Bridge classes for regional seismic risk assessment: Improving HAZUS models

    Sujith Mangalathu;Farahnaz Soleimani;Jong-Su Jeon

Frequent Co-Authors

Jong-Su Jeon
Jong-Su Jeon Hanyang University
Pengpeng Ni
Pengpeng Ni Sun Yat-sen University
Reginald DesRoches
Reginald DesRoches Rice University
Jamie E. Padgett
Jamie E. Padgett Rice University
De-Cheng Feng
De-Cheng Feng Southeast University
Mathieu Bauchy
Mathieu Bauchy University of California, Los Angeles
Morten Mattrup Smedskjær
Morten Mattrup Smedskjær Aalborg University
Yaolin Yi
Yaolin Yi Nanyang Technological University
Junho Song
Junho Song Seoul National University
Ertugrul Taciroglu
Ertugrul Taciroglu University of California, Los Angeles

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