Red Cedar

Developed comprehensive educational technology platform for Michigan State University supporting curriculum development and student success initiatives.

Architected scalable learning analytics system processing data from 50,000+ students. Implemented AI-driven assessment tools and professional development platforms.

The platform provides educators with powerful tools for curriculum design, student assessment, and data-driven decision making.

Advanced analytics enable early intervention strategies and personalized learning experiences for improved educational outcomes.

Served as Design Director leading product, platform, and cross-functional delivery for statewide education and public-sector systems focused on real-time analytics, scientific modeling, and institutional decision-making.

Directed multiple teams across PHP, .NET, data science, QA, sales, and state-level leadership, aligning technical execution with policy, education standards, and operational needs.

Designed and guided platforms that translated complex mathematical and statistical models into usable systems for educators, administrators, and government stakeholders.

Collaborated directly with higher education leaders and state institutions while contributing to early AI-driven systems, including language and writing tools such as ELI, integrating emerging machine learning capabilities into education workflows.

Successfully deployed EdTech platform serving 1.9 million students. Improved student retention by 20% through predictive analytics and early interventions.

Enhanced curriculum effectiveness with data-driven insights leading to 15% improvement in learning outcomes. Reduced assessment time by 60% with automated grading systems.

Platform adopted by multiple universities and school districts nationwide. Generated significant research funding through advanced learning analytics. Established Michigan State as leader in educational technology innovation.

Delivered scalable education platforms that unified data, analytics, and operational workflows across institutions, enabling real-time insight into performance at the student, classroom, and system level.

Improved decision-making by making complex data models accessible and actionable while aligning technical systems with educational and policy objectives.

Successfully led multi-disciplinary teams and state stakeholders to deliver cohesive, production-ready platforms, establishing a foundation for data-driven education systems and early adoption of AI-supported cognitive learning and content generation tools.