MUMBAI, India, March 13 -- Intellectual Property India has published a patent application (202621010555 A) filed by Symbiosis International, Pune, Maharashtra, on Jan. 31, for 'machine learning based automated system and method for predicting scholarship eligibility of students.'
Inventor(s) include Rohit Pawar; Ayushi Ray; Shruti Bawankar; and Sanvi Wadhankar.
The application for the patent was published on March 13, under issue no. 11/2026.
According to the abstract released by the Intellectual Property India: "The present invention discloses a machine learning based system (100) and method for predicting scholarship eligibility of students. The system comprises a data input module (110) receiving student data including CGPA, parental income, and demographic attributes, a data preprocessing module (120) performing cleaning, normalization, and categorical encoding, a feature engineering module (130) generating derived features including category-based scoring metrics, a machine learning classification module (140) implementing XGBoost gradient boosting algorithm, a threshold optimization module (150) determining optimized classification thresholds through precision-recall analysis, and a prediction output module (160) generating binary eligibility predictions with confidence metrics. The system achieves accuracy of 99.87 percent, precision of 0.99, and recall of 1.0 on test data, significantly outperforming conventional classification approaches. The invention addresses limitations of manual scholarship evaluation including time-intensive processing, human bias, and scalability challenges, providing educational institutions with an automated, objective, and efficient tool for distributing financial aid to deserving students."
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