VASC Seminar

Abstract: Nano-optical devices provide a new way to control light at the subwavelength scale, enabling optical functionalities beyond conventional optics. By engineering the nanostructures, we can tailor the optical response as a function of space, polarization, wavelength, and angle of incidence -- effectively turning the optical front end into a controllable, programmable physical layer. This [...]

Abstract: I will introduce "generative re-photography" methods that use new generative video models to get more out of your photos—even the blurry ones. First, I will present a method for converting motion-blurred images to video. This method can even predict the "past" and "future" (right before and after the capture) of a motion-blurred image. I will [...]

Abstract:  Gridded pixel and voxel representations form the backbone of visual computing, but they struggle to scale efficiently to large, high-dimensional data, such as volumetric medical scans and complex scientific simulations. Consequently, continuous, nongridded models such as implicit neural representations (INRs) and Gaussian splatting have gained significant research traction over the past five years. However, [...]

Abstract:  Autonomous systems ultimately rely on extracting information from light, yet remain brittle in extreme environments, from nighttime navigation to high-speed robotics. This limitation stems from a classical imaging abstraction: conventional sensors integrate photon flux over fixed exposure windows, imposing trade-offs between sensitivity, dynamic range, and temporal resolution that degrade perception when photons are scarce [...]

Abstract:   Transformers are ubiquitous. They influence nearly every aspect of modern AI. However, the mechanics of their training remain poorly understood. This poses a problem for the field due to the immense amounts of data, computational power, and energy being invested in the training of these networks. I highlight a recent intriguing empirical result from [...]

Abstract:   Light and sound are traditionally treated as distinct physical phenomena, yet their interaction provides a powerful mechanism for manipulating and sensing information across imaging, communication, and measurement. This talk explores computational acousto-optic systems that co-design acoustics, optics, and signal processing to enable programmable control of light and high-speed optical sensing without mechanical motion. [...]

Abstract:  In his essay "The Bitter Lesson," Richard Sutton argued that general methods leveraging computation ultimately outperform hand-crafted ones. In this talk, I share my own version of this lesson, learned the hard way over a decade in computer graphics. Where does the bitter lesson apply to graphics, and where does it not? I argue [...]

Abstract: Robots must often make decisions in scenes containing many objects: they need to identify what is present, understand where objects are, predict how they will interact, and choose actions accordingly. Learning these capabilities directly from pixels is challenging, especially when the number and arrangement of objects can change from one scene to another. In [...]

Abstract:  Most cameras on robots today capture images without considering scene content. In contrast, animal eyes have fast mechanical movements that control how the scene is imaged in detail by the fovea, where visual acuity is highest. The prevalence of active vision during biological imaging, and the wide variety of it, makes it very clear [...]

Abstract:   Equipping AI and robotic systems with the ability to understand human behavior is essential for enabling them to assist people across a wide range of everyday applications. This need is more pressing than ever: the heaviest consumers of such knowledge are no longer perception systems alone, but robot policies that must learn to act in [...]