eventSeminar
HAI Weekly Seminar with Dorsa Sadigh
Walking the Boundary of Learning and Interaction
AI+Education Summit 2026
ConferenceFeb 11, 20268:00 AM - 5:00 PM
February
11
2026
The AI Inflection Point: What, How, and Why We Learn
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Walking the Boundary of Learning and Interaction
The AI Inflection Point: What, How, and Why We Learn
How did we get to today’s technology which now supports a trillion dollar AI industry? What were the key scientific breakthroughs? What were the surprises and dead-ends along the way...
How did we get to today’s technology which now supports a trillion dollar AI industry? What were the key scientific breakthroughs? What were the surprises and dead-ends along the way...
The African Olympiad Academy is a world-class high school dedicated to training Africa’s most promising students in mathematics, science, and artificial intelligence through olympiad-based pedagogy.
The African Olympiad Academy is a world-class high school dedicated to training Africa’s most promising students in mathematics, science, and artificial intelligence through olympiad-based pedagogy.
There have been significant advances in the field of robot learning in the past decade. However, many challenges still remain when considering how robot learning can advance interactive agents such as robots that collaborate with humans. This includes autonomous vehicles that interact with human-driven vehicles or pedestrians, service robots collaborating with their users at homes over short or long periods of time, or assistive robots helping patients with disabilities. This introduces an opportunity for developing new robot learning algorithms that can help advance interactive autonomy.
In this talk, I will discuss a formalism for human-robot interaction built upon ideas from representation learning. Specifically, I will first discuss the notion of latent strategies — low dimensional representations sufficient for capturing non-stationary interactions. I will then talk about the challenges of learning such representations when interacting with humans, and how we can develop data-efficient techniques that enable actively learning computational models of human behavior from demonstrations, preferences, or physical corrections. Finally, I will introduce an intuitive controlling paradigm that enables seamless collaboration based on learned representations, and further discuss how that can be used for influencing humans.
