samuel mwengi

Led the annotation of over 1,200 complex mathematical expressions for AI training datasets, enhancing model accuracy by 35%. Diagnosed and resolved 98% of logic errors in AI-generated calculus solutions through systematic validation. Collaborated with NLP teams to design concept maps for improved AI reasoning.

Conduct monthly Python and machine learning workshops for over 50 university students, focusing on AI applications in local industries. Co-developed an online course on math foundations for AI developers with over 300 enrollments.

Volunteered to curate and label crisis-response datasets during Kenya's 2021 flood season, improving disaster prediction models. Trained staff on error-checking workflows for geospatial data.

Created over 50 AI-augmented problem sets for Calculus II and Linear Algebra, reducing student errors by 25%. Automated grading workflows for differential equations using Python, significantly cutting grading time while maintaining high accuracy.

Designed gamified math modules for over 200 high school girls, increasing participation in STEM subjects by 35% at partner schools. Focused on engaging young women in mathematics and technology.

Developed a Python tool to validate statistical climate models, which reduced manual verification time by 35%. Contributed to research efforts in data science and statistical modeling.

Grade: 3.8/4.0

Master’s-qualified Mathematics Specialist with expertise in applied calculus, AI data annotation, and mathematical modeling. Completed a thesis on optimizing neural network training through adaptive numerical PDE solvers, demonstrating a 20% reduction in training time for PDE-based AI systems.

Grade: 3.7/4.0

Graduated with a Bachelor of Science in Mathematics, focusing on graph theory and network optimization. Recognized for an outstanding capstone project and completed a minor in Computer Science.