Research Intern, NIT Kurukshetra (AI/ML modeling and evaluation)
Other
Conducted AI/ML model development and evaluation for cavitation index prediction using multiple algorithms. Interpreted model behavior and feature importance using sensitivity analysis and explainability methods. Validated model performance against experimental data to confirm predictive alignment with physical principles. • Built and benchmarked 7 machine learning models (linear regression to Gradient Boosting). • Performed Sobol and Morris sensitivity analyses to rank critical predictors (Froude Number). • Applied SHAP analysis to interpret GBM feature contributions. • Achieved near-perfect validation accuracy (CC > 0.999) against experimental results.
2025 - 2025