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Presenter: Shree Nayar (Homepage)
Friday April 3, 2015 from 11:00am to 12:00pm
Computational imaging uses new optics to capture a coded image, and an appropriate algorithm to decode the captured image. This approach of manipulating images before there are recorded and processing recorded images before they are presented has three key benefits. First, it enables us to implement imaging functionalities that would be difficult, if not impossible, to achieve using traditional imaging. Second, it can be used to significantly reduce the hardware complexity of an imaging system.
Shree K. Nayar is the T. C. Chang Professor of Computer Science at
Columbia University. He heads the Columbia Vision Laboratory (CAVE),
which develops advanced computer vision systems. His research is focused
on three areas - the creation of novel cameras that provide new forms
of visual information, the design of physics based models for vision and
graphics, and the development of algorithms for understanding scenes
from images. His work is motivated by applications in the fields of
digital imaging, computer graphics, robotics and human-computer
Nayar received his PhD degree in Electrical and Computer Engineering from the Robotics Institute at Carnegie Mellon University. For his research and teaching he has received several honors including the David Marr Prize (1990 and 1995), the David and Lucile Packard Fellowship (1992), the National Young Investigator Award (1993), the NTT Distinguished Scientific Achievement Award (1994), the Keck Foundation Award for Excellence in Teaching (1995), the Columbia Great Teacher Award (2006), and the Carnegie Mellon Alumni Achievement Award (2009). For his contributions to computer vision and computational imaging, he was elected to the National Academy of Engineering in 2008, the American Academy of Arts and Sciences in 2011, and the National Academy of Inventors in 2014.
Presenter: Katie Byl (Homepage)
Friday March 27, 2015 from 11:00am to 12:00pm
Katie Byl received her B.S., M.S., and Ph.D. degrees in mechanical engineering from MIT. Her research is in dynamic systems and control, with particular interest in modeling and control techniques to deal with the challenges of underactuation, stochasticity, and dimensionality reduction that characterize bio-inspired robot locomotion and manipulation in real-world environments. She is the recipient of an NSF CAREER award (2013), a Hellman Foundation Fellowship (2012), and an Alfred P. Sloan Research Fellowship in Neuroscience (2011). Katie has worked on a wide range of research topics in the control of dynamic systems, including magnetic bearing control, flapping-wing microrobotics, piezoelectic noise cancellation for aircraft, and vibration isolation for gravity wave detection, and she was once a professional gambler on the now-infamous MIT Blackjack Team.
Presenter: Sanja Fidler (Homepage)
Friday March 20, 2015 from 11:00am to 12:00pm
A successful autonomous system needs to not only understand the visual
world but also communicate its understanding with humans. To make this
possible, language can serve as a natural link between high level
semantic concepts and low level visual perception. In this talk, I'll
present our recent work on 3D scene understanding, and show how natural
sentential descriptions can be exploited to improve 3D visual parsing,
and vice-versa, how image information can help resolve ambiguities in
Sanja Fidler is an Assistant Professor at the Department of Computer Science, University of Toronto. Previously she was a Research Assistant Professor at TTI-Chicago, a philanthropically endowed academic institute located in the campus of the University of Chicago. She completed her PhD in computer science at University of Ljubljana in 2010, and was a postdoctoral fellow at University of Toronto during 2011-2012. In 2010 she visited UC Berkeley as a visiting student. She has served in program committees of numerous international conferences, and has received three outstanding reviewer awards (ECCV 2008, CVPR 2012, ECCV 2012). She also served as presentations chair at CVPR 2010, and publication chair of CVPR 2013, 2014 and 2015. Her main research interests are large-scale object detection, 3D scene understanding, and combining language and vision.
Presenter: Noah Cowan (Homepage)
Friday April 17, 2015 from 11:00am to 12:00pm
Control systems engineering commonly relies on the
"separation principle", which allows designers to independently design
state observers and controllers. Biological control systems, however,
routinely violate the requirements for
separability. Indeed, animals often rely on a strategy known as "active
sensing" in which organisms use their own movements to alter
spatiotemporal patterns of sensory information to improve
task-level control performance.
Noah Cowan earned his Ph.D. from the University of Michigan, Ann Arbor, in 2001 in Electrical Engineering. Following his Ph.D., he was a Postdoctoral Fellow in Integrative Biology at the University of California, Berkeley for 2 years. In 2003, he joined Johns Hopkins University, where he is now an associate professor of Mechanical Engineering and directs the LIMBS Laboratory. Noah's research is devoted to understanding navigation and control in machines and animals. This research program has been recognized by a Presidential Early Career Award in Science and Engineering (PECASE) and a James S. McDonnel Complex Systems Scholar award.
Friday February 27, 2015 at 9:00am
GRASP Lab - Industry Day February 27, 2015
Krishna P. Singh Center
3205 Walnut St., Philadelphia, PA
9:00 am – 5:00 pm
09:00 – 10:00 Registration and Continental Breakfast
10:00 – 11:00 Presentations (Glandt Forum, 3rd Floor)
Presenter: Ayanna Howard (Homepage)
Friday February 20, 2015 from 11:00am to 12:00pm
Robots for therapy applications can increase the quality of life for
children who experience disabling circumstances, by, for example,
becoming therapeutic playmates for children with neurological disorders.
There are numerous challenges though that must be addressed -
determining the roles and responsibilities of both clinician, child, and
robot; developing interfaces for clinicians to interact with robots
that does not require extensive training; and developing methods to
allow the robot to learn from their child counterpart.
Ayanna Howard is the Motorola Foundation Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. She received her B.S. in Engineering from Brown University, her M.S.E.E. from the University of Southern California, and her Ph.D. in Electrical Engineering from the University of Southern California in 1999. Her area of research is centered around the concept of humanized intelligence, the process of embedding human cognitive capability into the control path of autonomous systems. This work, which addresses issues of autonomous control as well as aspects of interaction with humans and the surrounding environment, has resulted in over 180 peer-reviewed publications in a number of projects – from scientific rover navigation in glacier environments to assistive robots for the home. To date, her unique accomplishments have been highlighted through a number of awards and articles, including highlights in USA Today, Upscale, and TIME Magazine, as well as being named a MIT Technology Review top young innovator of 2003, recognized as NSBE Educator of the Year in 2009, and receiving the Georgia-Tech Outstanding Interdisciplinary Activities Award in 2013. In 2013, she also founded Zyrobotics, which is currently licensing technology derived from her research lab and has released their first suite of educational technology products. From 1993-2005, Dr. Howard was at NASA's Jet Propulsion Laboratory, California Institute of Technology. Following this, she joined Georgia Tech in July 2005 and founded the Human-Automation Systems Lab. She is currently the Associate Director of Research for the Georgia Tech Institute for Robotics and Intelligent Machines. Prior to that, she served as Chair of the multidisciplinary Robotics Ph.D. program at Georgia Tech for three years from 2010-2013.
Presenter: Soon-Jo Chung (Homepage)
Friday February 13, 2015 from 11:00am to 12:00pm
The rapid and ubiquitous proliferation of reliable rotorcraft platforms
such as quadcopters has resulted in a boom in aerial robotics. However,
rotorcraft have issues of safety, high noise levels, and low efficiency
for forward flight.
Prof. Soon-Jo Chung received the S.M. degree in Aeronautics and Astronautics and the Sc.D. degree in Estimation and Control from MIT in 2002 and 2007, respectively. He received the B.S. degree from KAIST in 2000 (school class rank 1/120). He is currently an Assistant Professor in the Department of Aerospace Engineering and the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. He is also a Beckman Fellow of the U. of Illinois Center for Advanced Study (2014-2015). His research areas include nonlinear control and estimation theory and optimal/robust flight controls with application to aerial robotics, distributed spacecraft systems, and computer vision-based navigation. He is a recipient of the 2014 UIUC Engineering Dean’s Award for Excellence in Research, the AFOSR Young Investigator Award, the NSF CAREER Award, and two best conference paper awards from IEEE and AIAA. He also received multiple teaching recognitions including the UIUC List of Teachers Ranked as Excellent and the instructor/advisor for the 1st place winning team of the AIAA Undergraduate Team Space Design Competition. Prof. Chung has been a Member of the Guidance & Control Analysis Group in the Jet Propulsion Laboratory as a JPL Summer Faculty Fellow/Affiliate working on distributed small satellites during the summers of 2010-2014. http://publish.illinois.edu/aerospacerobotics/
Presenter: Dana Ballard (Homepage)
Friday February 6, 2015 from 11:00am to 12:00pm
The human motor control system is an extraordinarily
complex system that consists of layers of neural control
systems that address different demands of motive behavior. A
primary distinction between these systems can be made on the
basis of time. Systems in the forebrain operate on the order
Dr. Dana Ballard is currently a Professor in Computer Science at the University of Texas at Austin. He received his PhD in 1974 from the University of California, Irvine. Dr. Ballard's main research interest is in computational theories of the brain with emphasis on human vision. In 1985 Chris Brown and Dr. Ballard led a team that designed and built a high speed binocular camera control system capable of simulating human eye movements. The system was mounted on a robotic arm that allowed it to move at one meter per second in a two meter radius workspace. This system has led to an increased understanding of the role of behavior in vision. The theoretical aspects of that system were summarized in a paper ``Animate Vision,'' which received the Best Paper Award at the 1989 International Joint Conference on Artificial Intelligence. Currently, Dr. Ballard is interested in pursuing this research by using model humans in virtual reality environments. In addtion, he is interested in models of the brain that relate to detailed neural codes. A position paper on this work appeared in the Behavioral and Brain Sciences.
Presenter: Hanumant Singh (Homepage)
Friday January 30, 2015 from 11:00am to 12:00pm
The Arctic and Antarctic remain one of least explored parts of the
world's oceans. In this talk we look at efforts over the last decade to explore areas under-ice
which have traditionally been difficult to access. The focus of the talk will be on the robots,
the role of communications over low bandwidth acoustic links, and navigation and mapping
methodologies. This is all within the context of real data collected on several expeditions to the
Arctic and Antarctic.
Hanumant Singh graduated from the MIT WHOI Joint Program in 1995 after which he joined the staff at the Woods Hole Oceanographic Institution. His interests lie at the intersection of imaging and robotics underwater. Over the course of his career he has participated in more than 50 research expeditions all over the world in support of Marine Archaeology, Marine Geology and Geophysics, Marine Chemistry, Coral Reef Ecology, Fisheries and Polar Studies.
Presenter: Subramanian Ramamoorthy (Homepage)
Friday January 23, 2015 from 11:00am to 12:00pm
Autonomous robots that seek to work together with human co-workers must adopt representations that span the hierarchy from the quantitative sensorimotor signals to more qualitative task specifications. Despite significant recent activity around methods for learning hierarchical representations, e.g., in computer vision, the problem of defining and learning action-oriented symbols remains somewhat open.
Dr. Subramanian Ramamoorthy is a Reader (Associate Professor) in the School of Informatics, University of Edinburgh, where he has been since 2007. He is Coordinator of the EPSRC Robotarium Research Facility, and Executive Committee Member for the Centre for Doctoral Training in Robotics and Autonomous Systems. Previously, he received a PhD in Electrical and Computer Engineering from The University of Texas at Austin. He is a Member of the Young Academy of Scotland at the Royal Society of Edinburgh.
His current research is focussed on problems of autonomous learning and decision-making under uncertainty, by long-lived agents and agent teams interacting within dynamic environments. This work is motivated by applications in autonomous robotics, human-robot interaction, intelligent interfaces and other autonomous agents in mixed human-machine environments. These problems are solved using a combination of methods involving layered representations based on geometric/topological abstractions, game theoretic and behavioural models of inter-dependent decision making, and machine learning with emphasis on issues of transfer, online and reinforcement learning.
His work has been recognised by nominations for Best Paper Awards at major international conferences - ICRA 2008, IROS 2010, ICDL 2012 and EACL 2014. He serves in editorial and programme committee roles for conferences and journals in the areas of AI and Robotics. He leads Team Edinferno, the first UK entry in the Standard Platform League at the RoboCup International Competition. This work has received media coverage, including by BBC News and The Telegraph, and has resulted in many public engagement activities, such as at the Royal Society Summer Science Exhibition, Edinburgh International Science festival and Edinburgh Festival Fringe.
Before joining the School of Informatics, he was a Staff Engineer with National Instruments Corp., where he contributed to five products in the areas of motion control, computer vision and dynamic simulation. This work resulted in seven US patents and numerous industry awards for product innovation.