RI Seminar

Katsushi Ikeuchi : e-Intangible Heritage

NSH 1305

Katsushi Ikeuchi Principal Researcher, Microsoft Research Asia Abstract Tangible heritage, such as temples and statues, is disappearing day-by-day due to human and natural disaster. In e-tangible heritage, such as folk dances, local songs, and dialects, has the same story due to lack of inheritors and mixing cultures. We have been developing methods to preserve such [...]

RI Seminar

From Drones To Robots, The Road To Make Technologies More Accessible

NSH 1305

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. [...]

RI Seminar

Stabilizing the Unstable Brain

NSH 1305

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. [...]

RI Seminar
Peter Stone
David Bruton, Jr. Centennial Professor
The University of Texas at Austin

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 [...]

RI Seminar

Robot Skill Learning: From the Real World to Simulation and Back

NSH 1305

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 [...]

RI Seminar

Deep Robotic Learning

NSH 1305

Sergey Levine Assistant Professor, UC Berkeley Abstract Deep learning methods have provided us with remarkably powerful, flexible, and robust solutions in a wide range of passive perception areas: computer vision, speech recognition, and natural language processing. However, active decision making domains such as robotic control present a number of additional challenges, standard supervised learning methods [...]