Goodnews Oseni

Led AI-integration initiatives to optimize chemical production, improving predictive modeling and increasing system efficiency by 15% while reducing waste by 25%. Built predictive maintenance models to improve uptime by 12% and reduce operational costs by 10%.

Applied machine learning to improve data-driven decision-making, contributing to a 10% reduction in energy consumption in production systems. Designed and deployed NLP models for engineering text analysis and built end-to-end AI models from preprocessing through validation and deployment.

Supported AI research combining chemical engineering and machine learning, contributing to published papers and improved chemical process simulation accuracy by 15%. Developed deep learning models and performed data annotation and feature engineering for training datasets used in industrial AI applications.

Completed an M.S. in Artificial Intelligence, Data Science, and Engineering at the University of Alaska Anchorage.

Completed a B.S. in Chemical Engineering at Washington State University (Voiland School) via the UAF 2+2 program.

Completed a B.S. in Chemistry (Transfer Foundation) at the University of Alaska Fairbanks.