Divesh Ranjan Kumar

@tu.ac.th

Postdoctoral researcher, Department of Civil Engineering, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani, Thailand.
Thammasat university

Divesh Ranjan Kumar


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https://researchid.co/ranjandivesh453

EDUCATION

PhD in Civil Engineering (Geotechnical Engineering), National Institute of Technology Patna, 2020 to 2023

MTech in Civil Engineering (Geotechnical Engineering), National Institute of Technology Patna, 2018 to 2020

B.Tech in Civil Engineering, Nalanda College of Engineering Chandi nalanda (Honors with highest GPA), 2013 to 2017

RESEARCH, TEACHING, or OTHER INTERESTS

Civil and Structural Engineering, Safety, Risk, Reliability and Quality, Engineering, Artificial Intelligence
78

Scopus Publications

1439

Scholar Citations

26

Scholar h-index

41

Scholar i10-index

Scopus Publications

RECENT SCHOLAR PUBLICATIONS

  • Thermal performance evaluation of geothermal energy pile using deep learning-based approaches–A comparative study
    A Kumar, R Bag, BP Nayak, DR Kumar
    Geothermics 140, 103709 , 2026
    2026
  • Experimental evaluation-based machine learning approach to estimate the volumetric heat capacity of bentonite-based soil mixtures
    PK Sah, DR Kumar, SS Kumar, M Devarangadi, W Wipulanusat
    International Communications in Heat and Mass Transfer 176, 111314 , 2026
    2026
  • Performance Analysis of Lime-Treated Geogrid-Reinforced Silty Sand for Rectangular Footings Using Experimental and Computational Approaches
    SM Yousuf, F Ahmad, SM Gulzar, DR Kumar, W Wipulanusat
    Transportation Infrastructure Geotechnology 13 (5), 140 , 2026
    2026
  • 3D reliability assessment of railway embankment under pore-water pressure and seismic loading using supervised machine learning models
    B Rao, DR Kumar, S Kumar, W Wipulanusat, A Burman, LB Roy
    Modeling Earth Systems and Environment 12 (3), 178 , 2026
    2026
  • Compressive strength prediction of metakaolin mortar using CATBoost enhanced with genetic algorithm and particle swarm optimization
    P Thamsatitdej, DR Kumar, W Wipulanusat
    Asian Journal of Civil Engineering, 1-22 , 2026
    2026
    Citations: 1
  • Predicting vertical vibrations of circular foundation on transversely isotropic saturated soils using machine learning models
    B Phulsawat, T Senjuntichai, A Senjuntichai, DR Kumar, ...
    Innovative Infrastructure Solutions 11 (5), 252 , 2026
    2026
  • Hybrid Least Square Support Vector Machine Model for Predicting Flexural Performance of Heavyweight Concrete made with Metakaolin and Granite Industry Waste
    O Saensuk, DR Kumar, C Suksiripattanapong, P Nuaklong
    Engineered Science , 2026
    2026
  • Effect of nano silica dosage on the performance and durability of high-performance concrete using experimental and AI-based modeling approaches
    A Bharat, R Kumar, DR Kumar, W Wipulanusat, S Kumar
    Journal of Structural Integrity and Maintenance 11 (2), 2624145 , 2026
    2026
  • Optimization of the compost C/N ratio in garden waste in-vessel composting using a machine learning
    D Sharma, H Shivam, S Kumar, DR Kumar, W Wipulanusat
    Chemical Papers 80 (4), 4213-4229 , 2026
    2026
  • Integrating machine learning for efficient and safe tunnel design: an analysis of stability load coefficients in circular tunnels
    DR Kumar, W Wipulanusat, P Thangavel, C Boonyong
    Modeling Earth Systems and Environment 12 (2), 82 , 2026
    2026
    Citations: 1
  • Application of Random Forest and Optimization Techniques in Forecasting the Axial Load Capacity of Lipped Channel Cold-Formed Steel Sections
    DR Kumar, P Thangavel, W Wipulanusat, J Sunkpho
    Journal of Soft Computing in Civil Engineering 10 (2), e1950 , 2026
    2026
    Citations: 2
  • Mechanical properties of heavyweight concrete made from metakaolin and granite industry waste using ANN-based model
    O Saensuk, DR Kumar, P Nuaklong, P Jongvivatsakul, S Tangaramvong, ...
    Results in Engineering, 110057 , 2026
    2026
  • Enhancing Slope Stability Assessment Under Seismic Conditions: A Comparative Analysis of Monte Carlo Simulation, Subset Simulation, and a Second-order Reliability Method for …
    F Ahmad, DR Kumar, W Wipulanusat, P Samui, SS Mishra
    Transportation Infrastructure Geotechnology 13 (3), 47 , 2026
    2026
  • Optimizing COD removal using machine learning in a UASB-Clariflocculator wastewater treatment system
    S Kumar, DR Kumar, AR Quaff, W Wipulanusat
    Environment, Development and Sustainability, 1-31 , 2026
    2026
  • Development of an affordable and eco-friendly composite liner for municipal solid waste landfills using locally available materials and industrial waste: A hybrid experimental …
    R Kumar, DR Kumar, S Kumari, W Wipulanusat
    ENGINEERING Structure and Civil Engineering, 1-27 , 2026
    2026
  • Hybrid explainable machine learning models for predicting rapid chloride penetration test and sorptivity of self-compacting concrete with fly ash and silica fume under thermal …
    DR Kumar, S Kumar, T Senjuntichai, S Kaewunruen
    ENGINEERING Structure and Civil Engineering, 1-31 , 2026
    2026
    Citations: 2
  • Enhancing the Reliability-Based Design of Pile Foundations Using the Genetic Algorithm-Based XGBoost and ANFIS Approaches
    DR Kumar, M Kumar, A Kumar, N Kumar, W Wipulanusat, ...
    Journal of Soft Computing in Civil Engineering 10 (1), e1943 , 2026
    2026
    Citations: 4
  • Experimental and machine learning-based estimation of the thermal diffusivity of high-plastic soil
    PK Sah, DR Kumar, SS Kumar, W Wipulanusat
    Geothermics 134, 103489 , 2026
    2026
    Citations: 3
  • Optimization of pond-ash-based controlled low-strength materials with lime and superplasticizer via experiments and supervised machine learning
    DR Kumar, LD Kannari, T Senjuntichai, S Kaewunruen
    Results in Engineering, 108476 , 2025
    2025
    Citations: 3
  • Predicting the UCS of Industrial Byproduct-Based CLSM Using Machine Learning and Experiments
    CK Singh, DR Kumar, KL Dev, W Wipulanusat
    Civil Engineering Journal 11 (11) , 2025
    2025
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • Prediction of probability of liquefaction using soft computing techniques
    DR Kumar, P Samui, A Burman
    Journal of The Institution of Engineers (India): Series A 103 (4), 1195-1208 , 2022
    2022
    Citations: 81
  • Prediction of bearing capacity of pile foundation using deep learning approaches
    M Kumar, DR Kumar, J Khatti, P Samui, KS Grover
    Frontiers of Structural and Civil Engineering 18 (6), 870-886 , 2024
    2024
    Citations: 65
  • Machine learning approaches for stability prediction of rectangular tunnels in natural clays based on MLP and RBF neural networks
    W Jitchaijaroen, S Keawsawasvong, W Wipulanusat, DR Kumar, ...
    Intelligent Systems with Applications 21, 200329 , 2024
    2024
    Citations: 57
  • Development of ANN-based metaheuristic models for the study of the durability characteristics of high-volume fly ash self-compacting concrete with silica fume
    S Kumar, DR Kumar, W Wipulanusat, S Keawsawasvong
    Journal of Building Engineering 94, 109844 , 2024
    2024
    Citations: 56
  • Buckling response of CNT based hybrid FG plates using finite element method and machine learning method
    R Kumar, A Kumar, DR Kumar
    Composite Structures 319, 117204 , 2023
    2023
    Citations: 56
  • Soft computing-based prediction models for compressive strength of concrete
    M Kumar, R Biswas, DR Kumar, P Samui, MR Kaloop, M Eldessouki
    Case Studies in Construction Materials 19, e02321 , 2023
    2023
    Citations: 53
  • State-of-the-art XGBoost, RF and DNN based soft-computing models for PGPN piles
    M Kumar, P Samui, DR Kumar, PG Asteris
    Geomechanics and Geoengineering 19 (6), 975-990 , 2024
    2024
    Citations: 51
  • Prediction of probability of liquefaction using hybrid ANN with optimization techniques
    DR Kumar, P Samui, A Burman
    Arabian Journal of Geosciences 15 (20), 1587 , 2022
    2022
    Citations: 51
  • Optimized neural network-based state-of-the-art soft computing models for the bearing capacity of strip footings subjected to inclined loading
    DR Kumar, W Wipulanusat, M Kumar, S Keawsawasvong, P Samui
    Intelligent Systems with Applications 21, 200314 , 2024
    2024
    Citations: 45
  • Liquefaction susceptibility using machine learning based on SPT data
    DR Kumar, P Samui, A Burman, W Wipulanusat, S Keawsawasvong
    Intelligent Systems with Applications 20, 200281 , 2023
    2023
    Citations: 44
  • Soft computing techniques for predicting penetration and uplift resistances of dual pipelines in cohesive soils
    DR Kumar, P Samui, W Wipulanusat, S Keawsawasvong, K Sangjinda, ...
    Engineered Science 24 (7), 897 , 2023
    2023
    Citations: 41
  • Metaheuristic models for the prediction of bearing capacity of pile foundation
    M Kumar, R Biswas, DR Kumar, T Pradeep, P Samui
    Geomechanics and Engineering 31 (2), 129-147 , 2022
    2022
    Citations: 39
  • Soft-computing techniques for predicting seismic bearing capacity of strip footings in slopes
    DR Kumar, P Samui, W Wipulanusat, S Keawsawasvong, K Sangjinda, ...
    Buildings 13 (6), 1371 , 2023
    2023
    Citations: 38
  • Bearing capacity of eccentrically loaded footings on rock masses using soft computing techniques
    DR Kumar, P Samui, W Wipulanusat, S Keawsawasvong, K Sangjinda, ...
    Engineered Science 24 (929), 929 , 2023
    2023
    Citations: 38
  • Estimation of the compressive strength of ultrahigh performance concrete using machine learning models
    R Kumar, DR Kumar, W Wipulanusat, C Thongchom, P Samui, B Rai
    Intelligent Systems with Applications 25, 200471 , 2025
    2025
    Citations: 36
  • Hybrid artificial neural network models for bearing capacity evaluation of a strip footing on sand based on Bolton failure criterion
    W Jitchaijaroen, DR Kumar, S Keawsawasvong, W Wipulanusat, ...
    Transportation Geotechnics 48, 101347 , 2024
    2024
    Citations: 36
  • An eXtreme Gradient Boosting prediction of uplift capacity factors for 3D rectangular anchors in natural clays
    DT Tran, T Onjaipurn, DR Kumar, W Chim-Oye, S Keawsawasvong, ...
    Earth Science Informatics 17 (3), 2027-2041 , 2024
    2024
    Citations: 36
  • Application of novel deep neural network on prediction of compressive strength of fly ash based concrete
    R Biswas, M Kumar, DR Kumar, P Samui, P T, MK Rajak, DJ Armaghani, ...
    Nondestructive Testing and Evaluation 40 (10), 4638-4668 , 2025
    2025
    Citations: 35
  • Machine learning approaches for prediction of the bearing capacity of ring foundations on rock masses
    DR Kumar, P Samui, W Wipulanusat, S Keawsawasvong, K Sangjinda, ...
    Earth Science Informatics 16 (4), 4153-4168 , 2023
    2023
    Citations: 29
  • Reliability-based design for strip-footing subjected to inclined loading using hybrid LSSVM ML models
    M Kumar, DR Kumar, W Wipulanusat
    Geotechnical and Geological Engineering 42 (8), 7677-7697 , 2024
    2024
    Citations: 28