Education and Academic Background

• 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

Professional Experience 

• 1 June 2025 to Present --- Postdoc Research Scholar, Chulalongkorn University, Phayathai Road, Pathumwan, Bangkok 10330 Thailand

• 1 April 2024 to 31 March 2024  --- Postdoc Research Scholar, Research Unit in Data Science and Digital Transformation, Department of Civil Engineering, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathum Thani, Thailand 

• December 2023 to March 2024 --- Visiting Research Student, Department of Civil Engineering, Thammasat School of Engineering, Thammasat University

Research

• Geotechnical Stability Analysis

• Earthquake engineering

• Soil liquefaction

• Slope stability

• Reliability analysis

• Probabilistic analysis

• Soft Computing in Civil Engineering

• Machine learning and optimization algorithm

• Finite Element Limit Analysis

• Optimization in Civil Engineering

Publications

International Journal 

1. Thangavel, P., Palanisamy, M., Kumar, D. R., Wipulanusat, W., Sunkpho, J., & Roy, K. (2025). Investigation of cold formed steel angle compression through high throughput design FEA and machine learning. Scientific Reports, 15(1), 1-28.

2. Dev, K., Kumar, D. R., & Wipulanusat, W. (2025). Performance Evaluation of Pond Ash-Enhanced Flowable Fill for Plastic Concrete Cutoff Walls in Earthen Dams Using Advanced Machine Learning Models. Arabian Journal for Science and Engineering, 1-25.

3. Kumar, S., Weesakul, U., Kumar, D. R., Thangavel, P., Wipulanusat, W., & Sunkpho, J. (2025). A machine learning approach for corrosion rate modeling in Patna water distribution network of Bihar. Scientific Reports, 15(1), 11678.

4. Kumar, D. R., Kumar, P., Wipulanusat, W., Tran, D. T., & Keawsawasvong, S. (2025). Seismic stability of unsupported rectangular excavations in cohesive-frictional soils: FELA simulations and comparative analysis using MARS, GP, and GMDH models. Geotechnical and Geological Engineering, 43(3), 136.

5. Kumar, D. R., Kaorapapong, S., Wipulanusat, W., & Keawsawasvong, S. (2025). Mean Limiting Pressure Factors Determination in Contiguous Pile Walls using RAFELA and Nonlinear Regression Models in Spatially Random Soil. Results in Engineering, 104436.

6. Kumar, S., Kumar, D. R., Kumar, M., Wipulanusat, W., & Kaewmoracharoen, M. (2025). A novel approach to analyzing the 3D slope of Mount St. Helens via soft computing techniques. Earth Science Informatics, 18(2), 1-24.

7. Kumar, R., Kumar, D. R., Kumari, S., & Wipulanusat, W. (2025).  Assessing the significance of the particle size of Ganga sand Sone sand and bentonite mixtures for hydraulic containment liners integrated with machine learning-based UCS predictions. Constr Build Mater 465:140236. https://doi.org/10.1016/j.conbuildmat.2025.140236

8. Kumar, M., Kumar, D.R., Wipulanusat, W. et al. Deep Learning and Genetic Programming-Based Soft-Computing Prediction Models for Metakaolin Mortar. Transp. Infrastruct. Geotech. 12, 75 (2025). https://doi.org/10.1007/s40515-025-00532-9 

9. Tran, D. T., Shiau, J., Kumar, D. R., & Keawsawasvong, S. (2025). Optimization of ANN using metaheuristic algorithms for predicting failure envelope of ring foundations on anisotropic clay. Applied Ocean Research, 154, 104375. 

10. Kumar, R., Kumar, D. R., Wipulanusat, W., Thongchom, C., Samui, P., & Rai, B. (2024). Estimation of the Compressive Strength of Ultrahigh Performance Concrete using Machine Learning Models. Intelligent Systems with Applications, 200471. 

11. Chansavang, B., Kounlavong, K., Kumar, D. R., Nguyen, T. S., Wipulanusat, W., Keawsawasvong, S., & Jamsawang, P. (2024). Regression Machine Learning Models for Probabilistic Stability Assessment of Buried Pipelines in Spatially Random Clays. Arabian Journal for Science and Engineering, 1-28. 

12. Biswas, R., Kumar, M., Kumar, D. R., Samui, P., Rajak, M. K., Armaghani, D. J., & Singh, S. (2024). Application of novel deep neural network on prediction of compressive strength of fly ash based concrete. Nondestructive Testing and Evaluation, 1-31. 

13. Dev, K. L., Kumar, D. R., & Wipulanusat, W. (2024). Machine learning prediction of the unconfined compressive strength of controlled low strength material using fly ash and pond ash. Scientific Reports, 14(1), 27540. 

14. Kumar, M., Kumar, D. R., & Wipulanusat, W. (2024). Reliability-Based Design for Strip-Footing Subjected to Inclined Loading Using Hybrid LSSVM ML Models. Geotechnical and Geological Engineering, 1-21. 

15. Jitchaijaroen, W., Kumar, D. R., Keawsawasvong, S., Wipulanusat, W., & Jamsawang, P. (2024). Hybrid artificial neural network models for bearing capacity evaluation of a strip footing on sand based on Bolton failure criterion. Transportation Geotechnics, 48, 101347. 

16. Kumar, D. R., Wipulanusat, W., & Keawsawasvong, S. (2024). Application of Advanced Machine Learning Models for Uplift and Penetration Resistance in Clay-Embedded Dual Interfering Pipelines. Modeling Earth Systems and Environment, 1-25. 

17. Tran, D. T., Kumar, D. R., Keawsawasvong, S., Wipulanusat, W., & Jamsawang, P. (2024). Innovative approaches for predicting seismic stability of circular and rectangular tunnels in cohesive-frictional soils using machine learning and finite element limit analysis. Modeling Earth Systems and Environment, 10(4), 5831-5849. 

18. Kumar, D. R., Samui, P., Burman, A., Biswas, R., & Vanapalli, S. (2024). A novel approach for assessment of seismic induced liquefaction susceptibility of soil. Journal of Earth System Science, 133(3), 128. 

19. T. P., kumar, D. R., Kumar, M., Samui, P., & Armaghani, D. J. (2024). A novel approach to estimate rock deformation under uniaxial compression using a machine learning technique. Bulletin of Engineering Geology and the Environment, 83(7), 278. 

20. Sangjinda, K., Kumar, D. R., Keawsawasvong, S., Wipulanusat, W., & Jamsawang, P. (2024). Novel neural network-based metaheuristic models for the stability prediction of rectangular trapdoors in anisotropic and non-homogeneous clay. Advances in Engineering Software, 193, 103668. 

21. Kumar, M., Kumar, D. R., Khatti, J., Samui, P., & Grover, K. S. (2024). Prediction of bearing capacity of pile foundation using deep learning approaches. Frontiers of Structural and Civil Engineering, 1-17. 

22. Rabbani, A., Kumar, D. R., Fissha, Y., Bhavani, N. P., Ahirwar, S. K., Sharma, S., ... & Adachi, T. (2024). Optimization of an Artificial Neural Network Using Four Novel Metaheuristic Algorithms for the Prediction of Rock Fragmentation in Mine Blasting. Journal of The Institution of Engineers (India): Series D, 1-20. 

23. Kumar, S., Kumar, D. R., Wipulanusat, W., & Keawsawasvong, S. (2024). Development of ANN-Based Metaheuristic Models for the Study of the Durability Characteristics of High-Volume Fly Ash Self-Compacting Concrete with Silica Fume. Journal of Building Engineering, 109844. 

24. Pradeep, T., Kumar, D. R., Kumar, N., Wipulanusat, W., Keawsawasvong, S., & Sunkpho, J. (2024). Performance Evaluation and Triangle Diagram of Deep Learning Models for Embedment Depth Prediction in Cantilever Sheet Piles. Eng. Sci, 28(1082), 1082. 

25. Kumar, D. R., Wipulanusat, W., Sunkpho, J., Keawsawasvong, S., Jitchaijaroen, W., & Samui, P. (2024). Machine learning approaches for the prediction of the seismic stability of unsupported rectangular excavation. Engineered Science, 28, 1083. 

26. Tran, D. T., Onjaipurn, T., Kumar, D. R., Chim-Oye, W., Keawsawasvong, S., & Jamsawang, P. (2024). An eXtreme Gradient Boosting prediction of uplift capacity factors for 3D rectangular anchors in natural clays. Earth Science Informatics, 1-15. 

27. Kumar, M., Samui, P., Kumar, D. R., & Asteris, P. G. (2024). State-of-the-art XGBoost, RF and DNN based soft-computing models for PGPN piles. Geomechanics and Geoengineering, 1-16. 

28. Kumar, D. R., Wipulanusat, W., Kumar, M., Keawsawasvong, S., & Samui, P. (2024). Optimized neural network-based state-of-the-art soft computing models for the bearing capacity of strip footings subjected to inclined loading. Intelligent Systems with Applications, 21, 200314. 

29. Jitchaijaroen, W., Keawsawasvong, S., Wipulanusat, W., Kumar, D. R., Jamsawang, P., & Sunkpho, J. (2024). Machine learning approaches for stability prediction of rectangular tunnels in natural clays based on MLP and RBF neural networks. Intelligent Systems with Applications, 200329. 

30. Kumar, D. R., Bharti, A., Samui, P., Kurup, P., & Kumar, S. (2024). Development of fragility curve for railway embankment. International Journal of Mining and Geo-Engineering. 

31. Kumar, D. R., Samui, P., Wipulanusat, W., Keawsawasvong, S., Sangjinda, K., & Jitchaijaroen, W. (2023). Machine learning approaches for prediction of the bearing capacity of ring foundations on rock masses. Earth Science Informatics, 16(4), 4153-4168. 

32. Kumar, M., Biswas, R., Kumar, D. R., Samui, P., Kaloop, M. R., & Eldessouki, M. (2023). Soft computing-based prediction models for compressive strength of concrete. Case Studies in Construction Materials, 19, e02321. 

33. Kumar, D. R., Samui, P., Burman, A., Wipulanusat, W., & Keawsawasvong, S. (2023). Liquefaction susceptibility using machine learning based on SPT data. Intelligent Systems with Applications, 20, 200281. 

34. Kumar, D. R., Samui, P., Burman, A., & Kumar, S. (2023). Seismically induced liquefaction potential assessment by different artificial intelligence procedures. Transportation Infrastructure Geotechnology, 1-22. 

35. Kumar, R., Kumar, A., & Kumar, D. R. (2023). Buckling response of CNT based hybrid FG plates using finite element method and machine learning method. Composite Structures, 117204.

36. Kumar, D. R., Samui, P., & Burman, A. (2023). Suitability assessment of the best liquefaction analysis procedure based on SPT data. Multiscale and Multidisciplinary Modeling, Experiments and Design, 6(2), 319-329.

37. Kumar, D. R., Samui, P., Wipulanusat, W., Keawsawasvong, S., Sangjinda, K., & Jitchaijaroen, W. (2023). Soft-Computing Techniques for Predicting Seismic Bearing Capacity of Strip Footings in Slopes. Buildings, 13(6), 1371. 

38. Kumar, D. R., Samui, P., Wipulanusat, W., Keawsawasvong, S., Sangjinda, K., & Jitchaijaroen, W. (2023). Soft computing techniques for predicting penetration and uplift resistances of dual pipelines in cohesive soils. Engineered Science, 24, 897.

39. Kumar, M., Fathima, N. Z., & Kumar, D. R. (2023, March). A novel XGBoost and RF-based metaheuristic models for concrete compression strength. In International Conference on Civil Engineering Innovative Development in Engineering Advances (pp. 495-503). Singapore: Springer Nature Singapore. 

40. Kumar, D. R., Samui, P., Wipulanusat, W., Keawsawasvong, S., Sangjinda, K., & Jitchaijaroen, W. (2023). Bearing capacity of eccentrically loaded footings on rock masses using soft computing techniques. Eng Sci, 24(929), 929. 

41. Kumar, D. R., Samui, P., & Burman, A. (2022). Determination of best criteria for evaluation of liquefaction potential of soil. Transportation Infrastructure Geotechnology, 1-20. 

42. Kumar, D. R., Samui, P., & Burman, A. (2022). Prediction of probability of liquefaction using soft computing techniques. Journal of The Institution of Engineers (India): Series A, 103(4), 1195-1208. 

43. Kumar, M., Biswas, R., Kumar, D. R., Pradeep, T., & Samui, P. (2022). Metaheuristic models for the prediction of bearing capacity of pile foundation. Geomechanics and Engineering, 31(2), 129.

44. Kumar, D. R., Samui, P., & Burman, A. (2022). Prediction of probability of liquefaction using hybrid ANN with optimization techniques. Arabian Journal of Geosciences, 15(20), 1587.