Sujith Mangalathu, Ph.D

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9 articoli

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Jong-Su JeonAssociate Professor of Civil and Environmental Engineering, Hanyang UniversityEmail verificata su hanyang.ac.kr
Reginald DesRochesDean of Engineering, Rice UniversityEmail verificata su rice.edu
Seong-Hoon HwangAssistant Professor, Kumoh National Institute of TechnologyEmail verificata su kumoh.ac.kr
De-Cheng FengProfessor, School of Civil Engineering, Southeast University, ChinaEmail verificata su seu.edu.cn
Pengpeng NiProfessor of Geotechnical Engineering, Sun Yat-sen UniversityEmail verificata su mail.sysu.edu.cn
Henry V Burton Ph.D., S.E.Associate Professor, University of California, Los AngelesEmail verificata su seas.ucla.edu
Robin Davis P.Assistant Professor of Civil Engineering National Institute of Technology CalicutEmail verificata su nitc.ac.in
Muhamed Safeer Pandikkadavath, PhDNational Institute of Technology CalicutEmail verificata su nitc.ac.in
Farahnaz SoleimaniAssistant Professor, Oregon State UniversityEmail verificata su gatech.edu
Surendra Nadh SomalaAssociate Professor, Indian Institute of Technology HyderabadEmail verificata su iith.ac.in
Mengdie ChenHanyang UniversityEmail verificata su hanyang.ac.kr
Kamrul IslamPolytechnique MontrealEmail verificata su polymtl.ca
Anisha AGovernment Engineering College, PalakkadEmail verificata su gecskp.ac.in
Khondaker Sakil Ahmed, PhD, PEng,...Professor (Assoc), Department of Civil Eng, MIST, BSc (BUET), PhD (National University of Singapore)Email verificata su ce.mist.ac.bd
Bilal AhmedPh.D. Applied Mechanics and MaterialsEmail verificata su nyu.edu
Nafiz Imtiaz KhanPhD Student, UC DavisEmail verificata su ucdavis.edu
Jesika RahmanPhD Student, Department of Civil Engineering, University of Calgary, AB, CanadaEmail verificata su ucalgary.ca
Zhengxiang YiApplied Scientist, AmazonEmail verificata su g.ucla.edu
Gang HUHarbin Institute of Technology (Shenzhen)Email verificata su hit.edu.cn
Jiuk Shin, PhD, Associate ProfessorGyeongsang National UniversityEmail verificata su gnu.ac.kr

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Sujith Mangalathu, Ph.D

Mangalathu, Mylamkulam

Email verificata su gatech.edu - Home page

Machine Learning Statistical Modeling Risk Assessment Probabilistic Methods


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach S Mangalathu, SH Hwang, JS Jeon Engineering Structures 219, 110927, 2020	673	2020
Classification of failure mode and prediction of shear strength for reinforced concrete beam-column joints using machine learning techniques S Mangalathu, JS Jeon Engineering Structures 160, 85-94, 2018	337	2018
Interpretable XGBoost-SHAP machine-learning model for shear strength prediction of squat RC walls DC Feng, WJ Wang, S Mangalathu, E Taciroglu Journal of Structural Engineering 147 (11), 04021173, 2021	294	2021
Data-driven machine-learning-based seismic failure mode identification of reinforced concrete shear walls S Mangalathu, H Jang, SH Hwang, JS Jeon Engineering Structures 208, 110331, 2020	279	2020
Data-driven shear strength prediction of steel fiber reinforced concrete beams using machine learning approach J Rahman, KS Ahmed, NI Khan, K Islam, S Mangalathu Engineering Structures 233, 111743, 2021	258	2021
Artificial neural network based multi-dimensional fragility development of skewed concrete bridge classes S Mangalathu, G Heo, JS Jeon Engineering Structures 162, 166-176, 2018	255	2018
Classifying earthquake damage to buildings using machine learning S Mangalathu, H Sun, CC Nweke, Z Yi, HV Burton Earthquake Spectra 36 (1), 183-208, 2020	252	2020
Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements DC Feng, WJ Wang, S Mangalathu, G Hu, T Wu Engineering Structures 235, 111979, 2021	247	2021
Machine learning–based failure mode recognition of circular reinforced concrete bridge columns: Comparative study S Mangalathu, JS Jeon Journal of Structural Engineering 145 (10), 04019104, 2019	239	2019
Rapid seismic damage evaluation of bridge portfolios using machine learning techniques S Mangalathu, SH Hwang, E Choi, JS Jeon Engineering Structures 201, 109785, 2019	178	2019
Machine learning-based approaches for seismic demand and collapse of ductile reinforced concrete building frames SH Hwang, S Mangalathu, J Shin, JS Jeon Journal of Building Engineering 34, 101905, 2021	166	2021
Critical uncertainty parameters influencing seismic performance of bridges using Lasso regression S Mangalathu, JS Jeon, R DesRoches Earthquake Engineering and Structural Dynamics 47 (3), 784-801, 2018	161	2018
Explainable machine learning models for punching shear strength estimation of flat slabs without transverse reinforcement S Mangalathu, H Shin, E Choi, JS Jeon Journal of Building Engineering 39, 102300, 2021	135	2021
Stripe‐based fragility analysis of multispan concrete bridge classes using machine learning techniques S Mangalathu, JS Jeon Earthquake Engineering & Structural Dynamics 48 (11), 1238-1255, 2019	132	2019
Predicting the dissolution kinetics of silicate glasses using machine learning NM Krishnan, S Mangalathu, MM Smedskjaer, A Tandia, H Burton, ... Journal of Non-Crystalline Solids 487, 37-45, 2018	130	2018
PERFORMANCE BASED GROUPING AND FRAGILITY ANALYSIS OF BOX-GIRDER BRIDGES IN CALIFORNIA S Mangalathu Georgia Institute of Technology, 2017	117	2017
Deep learning-based classification of earthquake-impacted buildings using textual damage descriptions S Mangalathu, HV Burton International Journal of Disaster Risk Reduction 36, 101111, 2019	112	2019
Machine-learning interpretability techniques for seismic performance assessment of infrastructure systems S Mangalathu, K Karthikeyan, DC Feng, JS Jeon Engineering Structures 250, 112883, 2022	99	2022
Parameterized seismic fragility curves for curved multi-frame concrete box-girder bridges using Bayesian parameter estimation JS Jeon, S Mangalathu, J Song, R Desroches Journal of Earthquake Engineering 23 (6), 954-979, 2019	96	2019
ANCOVA-based grouping of bridge classes for seismic fragility assessment S Mangalathu, JS Jeon, JE Padgett, R DesRoches Engineering Structures 123, 379-394, 2016	93	2016

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