Dr. KAUSHIK JAS

About

Dr. Kaushik Jas is currently working as a Postdoctoral Research Associate in the School of Civil Engineering. He completed his MS and PhD degrees in Civil Engineering at the Indian Institute of Technology Madras (IITM), Chennai, India, in 2025. He was a recipient of the prestigious Prime Minister’s Research Fellowship (PMRF) during his PhD. At IITM, he worked under the supervision of Prof. G. R. Dodagoudar on the topic “Assessment of Liquefaction Potential of Saturated Cohesionless Soils Using Machine Learning Techniques.” He earned his Bachelor of Engineering (B.E.) degree in Civil Engineering from Jadavpur University, Kolkata, West Bengal, India, in 2018. His research interests lie in the field of geotechnical earthquake engineering and the application of soft computing techniques in this domain. Dr. Jas received the Institute Research Award (2024) from IITM in recognition of his research progress and contributions. He was also awarded the International Immersion Experience (IIE) Award 2024 and the One Program for Global Goals (OGGs)–JASSO Fellowship to pursue a visiting doctoral study at Hokkaido University, Japan. He is a student member of the Indian Geotechnical Society (IGS), Chennai Chapter, the Earthquake Engineering Research Institute (M.EERI), and an affiliate member of the American Society of Civil Engineers (Aff.M.ASCE).

Employment

• Indian Institute of Technology Madras PhD Research Scholar
  2021 - 2025

Education

• Indian Institute of Technology Madras MS and PhD
  2019 - 2025
• Jadavpur University BE
  2014 - 2018

Projects & Funding

Projects & funding information is unavailable.

Publications (6)

• Evaluation and Future Prospects of Data‐Driven Intelligence‐Based Framework for Predicting Cyclic Behavior of Reconstituted Sand
  International Journal for Numerical and Analytical Methods in Geomechanics 2025 DOI: 10.1002/nag.3939
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• SPT- and VS-based probabilistic evaluation of soil liquefaction potential using explainable boosting machine
  18th World Conference on Earthquake Engineering 2024
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• Evaluation and analysis of liquefaction potential of gravelly soils using explainable probabilistic machine learning model
  Computers and Geotechnics 2024 DOI: 10.1016/j.compgeo.2023.106051
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• Prediction of shear strain and excess pore water pressure response in liquefiable sands under cyclic loading using deep learning model
  Japanese Geotechnical Society Special Publication 2024 DOI: 10.3208/jgssp.v10.os-35-05
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• Liquefaction Potential Assessment of Soils Using Machine Learning Techniques: A State-of-the-Art Review from 1994–2021
  International Journal of Geomechanics 2023 DOI: 10.1061/IJGNAI.GMENG-7788
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• Explainable machine learning model for liquefaction potential assessment of soils using XGBoost-SHAP
  Soil Dynamics and Earthquake Engineering 2023 DOI: 10.1016/j.soildyn.2022.107662
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