Seminar
Quanta Perception as Probabilistic Events
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 [...]
Cutting the Skip: Training Residual-Free Transformers
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 [...]
Using Sound to Steer Light and Light to Measure Sound
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. [...]
My Bitter Lesson with Computer Graphics
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 [...]
CANCELED – Trust, Sensing, and Learning for Provable Multi-Robot Performance
Seminar Canceled This seminar has been canceled and may be rescheduled for a future date. Please check back for updates. Abstract: Multi-robot systems are physically embodied networks — they sense, move, and communicate through the physical world. The bar for safe decision-making rises as these systems enter safety-critical, real-world settings where they must perform [...]
Augmenting Bee Colonies with Robotics and AI Technologies for Ecosystem Support
Abstract: Earth’s ecosystems are facing a rapid decline in biodiversity, with honeybees —keystone pollinators critical to ecosystem stability— being among the most affected. The EU-funded RoboRoyale project addresses this crisis by integrating advanced robotics and AI to augment the beehive, enabling observation at unprecedented resolutions and scales. Featured on the cover of Science Robotics and [...]
Decision-Making in a World of Latent Particles
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 [...]
Adaptive Cameras: Bridging Novel Sensors and Robot Perception
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 [...]
