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Spring 2026 GRASP on Robotics: Roni Sengupta, University of North Carolina at Chapel Hill, “From Pixels to Physics: Understanding and Manipulating Physics from Images”

February 6 @ 10:30 am - 11:45 am

This event will be in-person ONLY in Wu and Chen Auditorium.

ABSTRACT

A hallmark of human vision is the ability to reason about the physics of the world: we can infer the shape of the object, how light reflects off the object, and how the object deforms under force. Yet today’s AI systems still lack this kind of physical intuition. Enabling machines to perceive and manipulate physics would mark a major step toward grounding AI in the real world.

In this talk, I will present my lab’s research at the intersection of computer vision, graphics, and machine learning that takes an inverse graphics perspective: rather than forward-simulating the physics of light, materials, and deformation as in decades of computer graphics, we aim to invert this process to infer and control these properties directly from images. The first part of the talk will focus on explicitly estimating physics, with examples in recovering lighting, reflectance, and object deformation. The second part will show how controlled generative models allow us to manipulate physics, with applications in relighting and simulating facial aging. Together, these efforts highlight a path toward AI systems with a deeper and more actionable understanding of the physical world.

Presenter

Roni Sengupta

Roni Sengupta - Learn More

Roni Sengupta is an Assistant Professor of Computer Science at the University of North Carolina at Chapel Hill. She leads the Spatial & Physical Intelligence (SPIN) Lab, building spatial AI models for the physical world. Her research lies at the intersection of Computer Vision and Computer Graphics, broadly in 3D Computer Vision & Computational Photography, with special focus on solving Inverse Graphics/Physics problems with applications in visual content creation and editing, telepresence, AR/VR, robotic perception, and 3D medical imaging. Previously, she was a Postdoctoral Research Associate at the University of Washington, Seattle (2019–2022), following her PhD from the University of Maryland, College Park. She is a recipient of the New & Early Career Trailblazer Award from the National Institute of Biomedical Imaging and Bioengineering (NIH). Her work on Background Matting received a Best Student Paper Honorable Mention at CVPR 2021 (Top 7 out of 1600 accepted papers) and has been adopted by several companies, including Microsoft, Inter-State Studio, and Lenovo.

Details

Venue

Wu and Chen Auditorium
3330 Walnut Street
Philadelphia, PA 19104
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