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Subject offerings of new and developing areas of knowledge in Systems Engineering and Design intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: 1 to 4 undergraduate hours. 1 to 4 graduate hours.

This course explores the development of AI-driven intelligent systems with an emphasis on creating real-world impact on real-world challenges in healthcare, manufacturing, and cyber-physical systems. The main components of this course include lectures and group projects. Students will be guided through a research project cycle, starting with sensing and data collection from diverse sources, such as wearables, images, videos, acoustics, and structural vibrations, to AI and data modeling of the collected data for predictive analysis, anomaly detection, and decision-making. By the end of this course, students will be able to: 1) Understand the basics of sensors, data processing, and AI models. 2) Formulate a research study motivated by real-world problems. 3) Gain hands-on experience in designing a health intelligence system and present the outcomes through scientific writing and presentations. Prior exposure to probability, statistics, and programming (e.g., MATLAB, Python) is needed. It