Hello ECE Community,

We warmly invite you to attend the next ECE Research Seminar. Light refreshments will be provided, so please RSVP to confirm your attendance. We kindly ask HDR attendees to bring their signed attendance form on the day; this form is also attached to the calendar invite. Please feel free to reach out if you have any questions.

Date and Time: Wednesday 27th May 12:00- 1:00pm Location: :J02, PNR Building, Lecture Theatre 304

Title: Optimizing for the Unknown: Toward Robots That Can Explore Anywhere, Handle Anything, and Learn from Little Abstract: Robots have the potential to become extraordinary tools that extend humanity’s reach, automating tasks that range from exploring the solar system and the deep oceans to manipulating delicate objects in our homes. Across these settings, robots face a common challenge: making good decisions when the world is only partially known, data are scarce, and mistakes are costly. In this talk, I will present recent work from my group on principled numerical optimization methods that enable robots to reason, act, and learn in uncertain and partially observable environments. I will show how these methods support long-horizon ocean exploration by balancing information gathering, safety, and resource constraints; improve precision manipulation by accounting for uncertainty in perception, contact, and dynamics; and accelerate multimodal (visual) policy learning by extracting more capability from limited experience. Across these domains, a central theme emerges optimization provides a powerful framework for building robots that are not merely reactive, but purposeful—capable of planning over long timescales, adapting to changing conditions, and learning efficiently from limited data. Together, these advances point toward a future in which robots can travel farther, handle more diverse tasks, and learn more quickly in the real world—bringing robust autonomy to environments where human presence is limited, uncertainty is unavoidable, and intelligent decision-making is critical. Speaker Bio: [AI, rat whiskers, and robots in the wild: Talking with Ian Abraham | Yale News]

Dr. Ian Abraham’s research sits at the intersection of robotics, optimization, control, machine learning, and artificial intelligence. His work focuses on developing computational methods that enable robotic systems to interact with, explore, and learn in extreme and remote environments. He has received numerous prestigious awards, including an NSF CAREER Award. Prior to joining the University of Sydney, Ian was an Assistant Professor at Yale University, with appointments in the Mechanical Engineering and Computer Science departments. He earned his PhD from Northwestern University and completed a postdoctoral fellowship at the Robotics Institute at Carnegie Mellon University.

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