Aastha Mehra

Solved a healthcare classification problem by cleaning and structuring 1,000+ ECG records, extracting signal features, and removing noise to prepare ML-ready data.

• Built and evaluated SVM and Decision Tree classifiers in Scikit-learn, achieving ~94% classification accuracy and validating results with precision, recall, and F1-score.
• Published findings in a Scopus-indexed peer-reviewed journal (2024), demonstrating research rigor and technical writing ability.

Investigated antimicrobial efficacy of ZnO nanoparticles by organizing multi-variable experimental data across batch cycles into a structured Excel dataset.

• Built Excel dashboards with PivotTables and trend charts to analyze antimicrobial outcomes, following a data collection → cleaning → analysis → reporting workflow.
• Communicated results in a published academic research paper (2023), reinforcing end-to-end research and reporting skills.