ME 506 Artificial Intelligence and Machine Learning For Mechanical Engineering

This course introduces the fundamentals of artificial intelligence (AI) and machine learning (ML) and examines their growing role in mechanical engineering. No prior experience with AI or ML is assumed; the course is designed to build both conceptual understanding and practical skills from the ground up. Students will develop a working knowledge of core algorithms, model design, and data-driven workflows, then apply these tools to a wide range of mechanical engineering domains. Application areas cover the instructor's own research as well as the broader interests of the department, including AI-powered sensing and optical measurement, autonomous robot control, fluid mechanics and thermal science, acoustics and vibration, solid mechanics, advanced energy materials (e.g., solid-state batteries), and emerging biomedical topics such as bacterial motion analysis for antibiotic susceptibility testing. Selected topics are drawn from the instructor's research, recent publications in leading journals and conferences, and course materials from peer institutions. Upon successful completion of the course, students will understand and implement fundamental AI and ML concepts, apply them to real mechanical engineering datasets, and communicate results clearly. Special attention is given to model interpretability, uncertainty quantification, and the safety and reliability considerations that are essential in engineering practice.