Teaching Assistant for ME 4710 – Foundations in Machine Learning for Engineers at Georgia Institute of Technology (Fall 2025), working with Dr. Jarred Fountain.

Responsibilities

• Designed and developed comprehensive grading rubrics for programming assignments covering data analysis workflows, statistical measures, and machine learning algorithm implementations
• Assessed and graded student assignments weekly, providing detailed technical feedback on Python implementations, experimental design, feature engineering, and model performance evaluation
• Responded to student inquiries via email, clarifying complex concepts in statistical modeling, uncertainty quantification, algorithm selection, and dataset amenability assessment for ML applications
• Collaborated with the instructor to refine assignment specifications and rubric criteria, ensuring alignment with course objectives on evaluating when, why, and how to apply machine learning in engineering problems

Course Information

ME 4710 teaches mechanical engineers foundational data analytics principles to evaluate when, why, and how to use or not use machine learning in engineering problems. Topics include documenting ML workflows, statistical measures, design of experiments, data feature engineering, algorithm selection, and uncertainty quantification for model evaluation.

Instructor

Dr. Jarred Fountain, Georgia Institute of Technology