An interpretable early-warning engine that detects academic instability before grades collapse. Instead of predicting performance, it models pressure accumulation, buffer strength, and transition risk using attendance, engagement, and study load to explain fragility and identify high-leverage interventions.

Springforth University Food Bank: A collaborative initiative with UNESCO to address student food insecurity. Contains code and resources for the web application, data analysis, and insights into the prevalence and impact of food insecurity on academic performance.

Analyzes student behavior patterns to understand their impact on academic performance. Provides clear visual insights and correlations from real data. Supports early prediction and decision-making for improving student outcomes.

EDA of the AMCAT job dataset to uncover trends in salary, academic performance, skills, and job locations using Python and data visualization tools.

Study of US/CA High School Performance and Socioeconomic Factors with SQL and GeoPandas