Faculty in the University of Maryland Institute for Advanced Computer Studies (UMIACS) are involved in four of the 15 new courses announced by the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM) as part of its 2026–27 course development grant program.
The AIM grants, valued at $10,000 each, support courses that address societal challenges in an AI-driven world. The courses will be developed by the end of 2026 and presented at an AI education symposium at UMD in spring 2027.
The four courses involving UMIACS faculty are:
Autonomy/AI Fundamentals for the Development, Test and Evaluation, Verification and Validation Workforce
Associate Professor of computer science Pratap Tokekar, in collaboration with Donald Costello of the Maryland Autonomous Technologies Research Innovation & eXploration (MATRIX) Laboratory and Aerospace Engineering associate professor Mumu Xu, will develop a graduate course focused on evaluating autonomous and AI-enabled aviation systems. The course introduces core concepts, control methods and risk mitigation challenges associated with uncrewed and autonomous transportation. Students will gain hands-on experience in formal methods, reinforcement learning and perception programming, with an emphasis on assessing system safety, performance and reliability. Tokekar has an appointment in UMIACS and is affiliated with the University of Maryland Center for Machine Learning.
Embodied AI Studio: Installation, Performance and Intelligent Media Through Reflective Making
This 400-level course, developed by Assistant Professor of computer science Huaishu Peng and Immersive Media Design (IMD) lecturer Jonathan Martin, brings together students across disciplines to explore how AI can be experienced through physical interaction. Through studio projects and a semester-long capstone, students will create interactive works combining generative AI or computer vision with physical computing, including wearables, installations and simple robotics. The course also examines ethical and social dimensions of embodied AI and culminates in a public-facing project. Peng has an appointment in UMIACS and is active in the IMD program.
Interpretable AI: Bridging Technical and Philosophical Perspectives
Electrical and Computer Engineering assistant professor Sanghamitra Dutta is developing an interdisciplinary undergraduate course on interpretable AI, focusing on making machine learning systems more transparent and trustworthy in areas such as healthcare and finance. Students will study approaches ranging from inherently interpretable models to post hoc techniques and large language model methods, incorporating perspectives from philosophy, cognitive science and human-computer interaction. Dutta has an affiliate appointment in UMIACS and is active in the University of Maryland Center for Machine Learning.
Modern Software Development
Assistant Professor of computer science Leonidas Lampropoulos and computer science senior lecturer Anwar Mamat are developing an undergraduate course on building production-quality software using modern, AI-assisted workflows. Students will work on team-based projects covering version control, testing, architecture, security, user experience and cloud deployment, while also examining the capabilities and limitations of AI tools in software development. Lampropoulos has an appointment in UMIACS and is a core faculty member in the Maryland Cybersecurity Center (MC2).
—Adapted from a story originally published in Maryland Today.