New Courses in Systems Engineering

Faculty in the Department of Systems Engineering are excited to offer two new courses in applications of systems, starting in Spring semester 2023. Both courses target new and upcoming technologies, and both are taught by faculty from industry partners. Our anticipation is that these courses will become regular offerings within the curriculum. Below are the official catalog descriptions for these two courses.

Multiagent Robotic Systems

This course will comprehensively explore distributed decision architecture in multiagent systems for the cooperative control of multirobot systems. The primary objective is to equip students with the knowledge and skills to design distributed controllers and strategies that leverage local interactions among networked agents (robots) to achieve global objectives. We will delve into the control-theoretic aspects of multirobot systems, focusing on how the underlying network topology influences the dynamic behavior of these interconnected systems. By the end of the course, students will have a clear understanding of various distributed control strategies and their applications in multirobot systems, including formation control, coverage control, connectivity maintenance and topology management, resilient and fault-tolerant control, and self-organization within multirobot systems.

Functional Safety Systems

Exploration of functional safety systems in various industries from a technical and management perspective. Students will perform individual case studies on functional safety best practices in selected industries such as machinery, transportation, medical, process sector, and energy storage. Students will collaborate on cross-functional teams for practical experience conducting weekly activities in Functional Safety Management, Hazard and Risk Assessment, Safety Concepts, Safety Requirements Specifications, Safety Design Documentation, Failure Modes and Effects Analysis, Validation and Verification, Functional Safety Assessment and Certification. Industry partners will guide students throughout the course and participate in final project mock assessment and certification.

Data Science in Digital Health Systems

This project-based course will teach systems analysis and data science techniques using digital health data. The project will: have students collect data on themselves throughout the semester using a provided Ōura Ring wearable device (at no cost to the student); build a secure system to store, access, and analyze the data; and use signal processing and machine learning approaches to identify and analyze trends in collected signals. Lectures will cover a variety of topics, including systems analysis, data science, and digital health. No prior knowledge of biology or human health is required.