Dr. Barada Prasad Sethy

Employment

• NIST University Teaching and Research
  2019 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (13)

• Balancing accuracy and interpretability: AI-driven predictive modeling of construction schedule performance in India
  Asian Journal of Civil Engineering 2025 DOI: 10.1007/s42107-025-01363-2
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• Artificial intelligence models for predicting unconfined compressive strength of mixed soil types: focusing on clay and sand
  Asian Journal of Civil Engineering 2025 DOI: 10.1007/s42107-025-01285-z
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• Optimizing construction time, cost, and quality: a hybrid AHP-NSGA-III model for enhanced multi-objective decision making
  Asian Journal of Civil Engineering 2024 DOI: 10.1007/s42107-024-01232-4
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• Prediction of swelling pressure of expansive soil using machine learning methods
  Asian Journal of Civil Engineering 2024 DOI: 10.1007/s42107-024-01205-7
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• Bearing Capacity of Circular Foundation on a Sand Layer of Limited Thickness Under Eccentrically Inclined Loading
  Soil Mechanics and Foundation Engineering 2021 DOI: 10.1007/s11204-021-09692-5
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• Bearing Capacity of Circular Foundation on Sand of Limited Thickness under Inclined Loading
  Geotechnical Special Publication 2020 DOI: 10.1061/9780784482780.029
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• Behavior of circular foundation on sand layer of limited thickness subjected to eccentrically inclined load
  Soils and Foundations 2020 DOI: 10.1016/j.sandf.2019.12.005
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• Bearing Capacity of Circular Foundation on Sand Layer of Limited Thickness Underlain by Rigid Rough Base Subjected to Eccentrically Inclined Load
  Geotechnical Testing Journal 2019 DOI: 10.1520/GTJ20170420
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• Prediction of ultimate bearing capacity of circular foundation on sand layer of limited thickness using artificial neural network
  International Journal of Geotechnical Engineering 2019 DOI: 10.1080/19386362.2019.1645437
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• Ultimate Bearing Capacity of Eccentrically Inclined Loaded Circular Foundation on Sand Layer of Limited Thickness Using ANN
  Advanced Research on Shallow Foundations 2019 DOI: 10.1007/978-3-030-01923-5_4
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