Sujith Mangalathu

7.1k citations

106 papers · 5.6k indexed · 7 hit papers · h-index 35

Civil and Structural Engineering top 0.1%
- Seismic Performance and Analysis 53
- Structural Health Monitoring Techniques 48
- Infrastructure Maintenance and Monitoring 25
- Concrete Corrosion and Durability 22
- Geotechnical Engineering and Underground Structures 12
- Structural Response to Dynamic Loads 12
- Structural Engineering and Vibration Analysis 7
Building and Construction top 0.2%
- Structural Behavior of Reinforced Concrete 21
Safety, Risk, Reliability and Quality top 1%
Statistics, Probability and Uncertainty top 1%
Environmental Engineering top 5%

Co-authors: Jong‐Su Jeon Seong‐Hoon Hwang De‐Cheng Feng Pengpeng Ni Reginald DesRoches Henry V. Burton Eunsoo Choi Wenjie Wang
Cited by: Civil and Structural Engineering Building and Construction Safety, Risk, Reliability and Quality
Partner nations: India South Korea United States

In The Last Decade

Sujith Mangalathu

104 papers receiving 5.4k citations

Hit Papers

7 papers align trajectories log scale

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

2021 Data-driven shear strength prediction of steel fiber reinforced concrete beams using machine learning approach
2021 Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements
2021 Interpretable XGBoost-SHAP Machine-Learning Model for Shear Strength Prediction of Squat RC Walls
2020 Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach
2020 Data-driven machine-learning-based seismic failure mode identification of reinforced concrete shear walls
2018 Classification of failure mode and prediction of shear strength for reinforced concrete beam-column joints using machine learning techniques
2018 Artificial neural network based multi-dimensional fragility development of skewed concrete bridge classes

Peers

Countries citing papers authored by Sujith Mangalathu

Since Specialization

Citations

This map shows the geographic impact of Sujith Mangalathu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sujith Mangalathu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sujith Mangalathu more than expected).

Fields of papers citing papers by Sujith Mangalathu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sujith Mangalathu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sujith Mangalathu. The network helps show where Sujith Mangalathu may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Sujith Mangalathu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sujith Mangalathu Line = papers co-authored together Sujith Mangalathu links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Predicting shear strength of hollow pretensioned spun precast concrete pile using machine learning models Tanvir Hassan Tusher,Abdullah Al Moneim,Khondaker Sakil Ahmed,A. H. M. Muntasir Billah,Sujith Mangalathu	2025	1
2	Machine learning-based full-life-cycle seismic response assessment for in-service bridge piers: Comprehensive analysis of interpretability and seismic fragility Yalin Li,Zhen Sun,Sujith Mangalathu,Yaqi Li,Weidong He,Xu Xue	2025	7
3	Interpretable machine learning based tsunami bridge fragility assessment V.M. Sreedevi,A. Anisha,C.K. Jithin,S. Jyothika,T Shilpa,Sujith Mangalathu,Prateek Negi,Robin Davis	2025	0
4	A robust force-finding framework for tensegrity structures using gradient-boosting decision trees and Latin hypercube sampling Yutao He,Jiamin Guo,Huan Ping,Mingliang Zhu,Sujith Mangalathu	2025	1
5	Seismic response evaluation of RC bridge considering maximum and residual column curvature ductility Edavalath Nadeem,Karuparambath Muhammed Navvar,Muhamed Safeer Pandikkadavath,Sujith Mangalathu	2025	1
6	Near-field seismic response assessment of buckling-restrained braced frames for different engineering demand parameters T.P. Anand,Muhamed Safeer Pandikkadavath,Sujith Mangalathu	2024	5
7	Data driven models for capacity prediction of CFS lipped channel flexural members V.M. Sreedevi,V.E. Parvathi,K. Rajneesh,S. Aswin,V. Aswin,A. Anisha,P.J. Usman Arshad,Sujith Mangalathu,Robin Davis	2024	4
8	Effect of data drift on the performance of machine‐learning models: Seismic damage prediction for aging bridges Mengdie Chen,Yewon Park,Sujith Mangalathu,Jong‐Su Jeon	2024	10
9	Rapid damage state identification of structures using generalized zero‐shot learning method Mengdie Chen,Sujith Mangalathu,Jong‐Su Jeon	2024	4
10	Machine learning models for seismic analysis of buckling-restrained braced frames T.P. Anand,Muhamed Safeer Pandikkadavath,Sujith Mangalathu,Dipti Ranjan Sahoo	2024	5
11	Machine learning-based framework for predicting the fire-induced spalling in concrete tunnel linings Gaveen Sirisena,Thushara Jayasinghe,Tharaka Gunawardena,Lihai Zhang,Priyan Mendis,Sujith Mangalathu	2024	12
12	Smart bridge bearing monitoring: Predicting seismic responses with a multi‐head attention‐based CNN‐LSTM network Omid Yazdanpanah,Minwoo Chang,M. K. Park,Sujith Mangalathu	2024	6
13	Evaluation and analysis of liquefaction potential of gravelly soils using explainable probabilistic machine learning model Kaushik Jas,Sujith Mangalathu,G. R. Dodagoudar	2024	30
14	Betweenness Centrality-Based seismic risk management for bridge transportation networks Mengdie Chen,Sujith Mangalathu,Jong‐Su Jeon	2023	16
15	Condition Assessment of Highway Bridges Using Textual Data and Natural Language Processing- (NLP-) Based Machine Learning Models De‐Cheng Feng,Wenjie Wang,Sujith Mangalathu,Zhen Sun	2023	11
16	Probabilistic curvature-and-drift limit states predictive models of high-strength bridge columns Jian Zhong,Yanyan Zhu,Sujith Mangalathu,Kang Gao	2023	18
17	2018 Kerala Flood Damage: Survey, Identification, and Damage Prediction Models Using Machine Learning A. Anisha,K. Malavika,K. Erfana,K. Dheeraj,Abdul Subahan,Anmay Raj,Sujith Mangalathu,Robin Davis	2023	2
18	Classifying earthquake damage to buildings using machine learning Sujith Mangalathu,Han Sun,Chukwuebuka C. Nweke,Zhengxiang Yi,Henry V. Burton	2019	196
19	Adjustment Factors to Account for the Effect of Bridge Deck Horizontal Curvature on the Seismic Response of Concrete Box‐Girder Bridges in California Sujith Mangalathu,Jong‐Su Jeon	2018	8
20	Development of a bridge-specific fragility methodology to improve the seismic resilience of bridges Jazalyn Dukes,Sujith Mangalathu,Jamie E. Padgett,Reginald DesRoches	2018	22

About Sujith Mangalathu

Sujith Mangalathu is a scholar working on Civil and Structural Engineering, Building and Construction and Statistics, Probability and Uncertainty, having authored 106 papers that have together received 5.6k indexed citations. Recurring topics across this work include Seismic Performance and Analysis (53 papers), Structural Health Monitoring Techniques (48 papers), Infrastructure Maintenance and Monitoring (25 papers), Concrete Corrosion and Durability (22 papers), Structural Behavior of Reinforced Concrete (21 papers), Geotechnical Engineering and Underground Structures (12 papers), Structural Response to Dynamic Loads (12 papers) and Structural Engineering and Vibration Analysis (7 papers). The work is most often cited by research in Civil and Structural Engineering (4.5k citations), Building and Construction (1.3k citations) and Safety, Risk, Reliability and Quality (320 citations). Sujith Mangalathu has collaborated with scholars based in India, South Korea and United States. Frequent co-authors include Jong‐Su Jeon, Seong‐Hoon Hwang, De‐Cheng Feng, Pengpeng Ni, Reginald DesRoches, Henry V. Burton, Eunsoo Choi, Wenjie Wang, Gwanghee Heo and Ertuǧrul Taciroğlu.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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