Colloquium Speaker Silvio Savarese, Stanford University Tuesday, December 9, 4:30pm Computer Science 105 Sensing and sensibility We are moving into a world where sensors will be everywhere and will be ubiquitous. In the recent years, we have seen an explosion of new artificial visual sensors that can integrate luminance values with other sensing modalities: infrared, thermal, gravity, depth, to cite a few. Sensing is not the hard problem here, however. Sensibility, or, intelligent understanding of the sensing data is the challenge. When we look at an environment such as a coffee shop, we don't just recognize the objects in isolation, but rather perceive a rich scenery of the 3D space, its objects and all the relations among them. This allows us to effortlessly navigate through the environment, or to interact and manipulate objects in the scene with amazing precision. A major line of work from my group in recent years has been to design visual models that can process different sensing modalities and enable sensibility. I will start by giving an overview of our research for detecting objects and determining their geometric and physical properties such as 3D location, pose or shape from images, videos or RGB-Depth imagery. Then, I will demonstrate that these detection methods play a critical role for modeling the interplay between objects and space which, in turn, enable simultaneous inference of the semantic and spatial properties of a scene. I will conclude this talk by demonstrating that our models for sense and sensibility are potentially transformative in application areas related to autonomous or assisted navigation, smart environments, augmented reality, and large scale information management. Silvio Savarese is an Assistant Professor of Computer Science at Stanford University. He earned his Ph.D. in Electrical Engineering from the California Institute of Technology in 2005 and was a Beckman Institute Fellow at the University of Illinois at Urbana-Champaign from 2005–2008. He joined Stanford in 2013 after being Assistant and then Associate Professor (with tenure) of Electrical and Computer Engineering at the University of Michigan, Ann Arbor, from 2008 to 2013. His research interests include computer vision, object recognition and scene understanding, shape representation and reconstruction, human activity recognition and visual psychophysics. He is recipient of several awards including the James R. Croes Medal in 2013, a TRW Automotive Endowed Research Award in 2012, an NSF Career Award in 2011 and Google Research Award in 2010. In 2002 he was awarded the Walker von Brimer Award for outstanding research initiative.