Seraphine MUKABUGINGO

Conducted quantitative research and backtested alpha-factor prediction algorithms on large financial time-series, completing 4 advanced projects and performing performance attribution and risk analysis.

Led RDHS-based ML research predicting early pregnancy, engineered 50+ features from 15,000+ records, and developed models achieving 85%+ AUC-ROC to inform national health programs.

Selected as a national master trainer for AI and coding education, trained 50+ teachers and conducted workshops for 200+ students while creating training materials and assessment frameworks.

Delivered advanced programming curricula to 150+ students annually, designed project-based data literacy programs, and led STEM mentoring that increased girls pursuing tech careers by 40%.

Built an automated chest X-ray preprocessing pipeline and developed CNN models for TB screening optimized for rural health centers, improving diagnostic speed and early detection.

Grade: Distinction (Grand Distinction 16.00–20.00 scale)

Activities and societies: Thesis supervised by Dr. Nizeyimana Eric; coursework in Advanced Research Methodology, Demographic Health Surveys, Cloud Computing, and Distributed Systems.

Master of Science in Big Data Analytics with thesis on predicting early sexual debut and early pregnancy in Rwanda using machine learning; included advanced coursework in machine learning, biostatistics, epidemiological methods, and big data analytics.

Grade: Honours

Activities and societies: Major coursework in Computer Science and minor in Mathematics.

Bachelor of Education in Computer Science (Honours) with a major in Computer Science and minor in Mathematics; coursework included data structures, algorithms, database systems, and statistics.