Seminar
Attention and Activities in First Person Vision
Event Location: Newell Simon Hall 1507Bio: Yin Li is currently a doctoral candidate in the School of Interactive Computing at the Georgia Institute of Technology. His research interests lie at the intersection of computer vision and mobile health. Specifically, he creates methods and systems to automatically analyze first person videos, known as First Person Vision [...]
TBA: Yin Li
Embodied learning for visual recognition
Event Location: Gates 7101Bio: Dinesh Jayaraman is a PhD candidate in Kristen Grauman's group at UT Austin. His research interests are broadly in visual recognition and machine learning. In the last few years, Dinesh has worked on visual learning and active recognition in embodied agents, unsupervised representation learning from unlabeled video, visual attribute prediction, and [...]
From Drones To Robots, The Road To Make Technologies More Accessible
Shuo Yang Director of Intelligent Navigation Technologies, DJI Abstract Over the past decade, DJI has developed several world-leading drone products, turning cutting-edge technologies such as high resolution image transmission, visual odometry, and learning-based object tracking into affordable commercial products. Along with all these technological successes, DJI is exploring innovative ways to make them more accessible. [...]
Assistive technology for wayfinding, information access, and public transit
Event Location: Newell Simon Hall 1507Bio: Roberto Manduchi is a Professor of Computer Engineering at the University of California, Santa Cruz, where he conducts research in the areas of computer vision and sensor processing with applications to assistive technology. Prior to joining UCSC in 2001, he worked at the NASA Jet Propulsion Laboratory and at [...]
Stabilizing the Unstable Brain
Noah Cowan Associate Professor of Mechanical Engineering, Johns Hopkins University Abstract The nervous system is arguably the most sophisticated control system in the known universe, riding at the helm of an equally sophisticated plant. Understanding how the nervous system encodes and processes sensory information, and then computes motor action, therefore, involves understanding a closed loop. [...]
Robot Skill Learning: From the Real World to Simulation and Back
Event Location: NSH 1305Bio: Dr. Peter Stone is the David Bruton, Jr. Centennial Professor and Associate Chair of Computer Science, as well as Chair of the Robotics Portfolio Program, at the University of Texas at Austin. In 2013 he was awarded the University of Texas System Regents' Outstanding Teaching Award and in 2014 he was [...]
Robot Skill Learning: From the Real World to Simulation and Back
Peter Stone David Bruton, Jr. Centennial Professor, The University of Texas at Austin Abstract For autonomous robots to operate in the open, dynamically changing world, they will need to be able to learn a robust set of interacting skills. This talk begins by introducing "Overlapping Layered Learning" as a novel hierarchical machine learning paradigm for [...]