Start with a simple question: What is the best major for a student to become a roboticist? In my role leading the creation of the Robotics Undergraduate Major at Michigan, we tackled this question through the curricular challenge of how to both: 1) educate people to put ideas of the robotics discipline into practice and 2) endow them with the intellectual lens for creating new ideas that extend the frontiers of the robotics discipline -- where mobility and dexterity through humanoid robots are poised to have a transformative impact in our increasingly AI-driven world.

In this talk, I will discuss my work to both advance the state of the art in semantic understanding for robotics and prepare students for possible futures where robotics and AI are abundant and ubiquitous. I will present the design, launch, and innovations for the Michigan Robotics Major for undergraduates, as robotics emerges into its own as a true academic discipline. I will describe highlights from research in semantic 3D perception for mobile manipulation robots (including humanoids) to understand the form and function (or affordances) for a diversity of objects in common environments. I will also share insights from my role as Program Chair of the AAAI-26 Conference (and its roughly 30,000 submissions) and how this role, and my experiences with Amazon AWS Machine Learning University, has reshaped my perspective on AI for teaching at the university level. Finally, I will discuss new efforts in my course this semester to formulate "mutation assessments" that gauge student understanding of agentically coded projects.