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Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

This course explores the digital transformation of agricultural production systems through the integration of automation, AI, sensing, connectivity, and electrification. With rising global challenges related to labor, sustainability, and food security, agriculture is rapidly becoming one of the most complex and impactful domains for cyber-physical systems research and deployment. The course focuses on the engineering foundations of modern farm operations?including field robotics, machine perception, farm management information systems, and digital twins?while emphasizing system integration, safety, and usability in real-world agricultural environments. Students will read and critique state-of-the-art research papers spanning autonomous machinery, edge/cloud computing for farms, computer vision for crops and livestock, and scalable decision support systems. A semester-long team project will allow students to conceptualize, prototype, and present a solution to a real-world digital ag