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Humans’ remarkable abilities to perceive, navigate and interact with natural environments dramatically eclipse those of current robotic systems. Research connecting perception and robotics investigates questions such as: How do humans recognize objects in natural scenes? How can we make a robot recognize and pick up objects in a kitchen? How do humans and animals find their way around? How can we build a car that drives itself? Interdisciplinary research will enable new insights into the performance of human and animal perception as well as the design of new algorithms that will enable robots to perceive and act in complex scenes. Graduate traineeships, with support from the National Science Foundation’s Integrative Graduate Education and Research Training (IGERT) program, are available to qualified applicants to cover tuition costs and to provide stipends of up to $30,000 per year for five years of graduate training leading to a Ph.D. in a relevant discipline. IGERT is a National Science Foundation program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the skills needed for the career demands of the future. GRADUATE TRAINEESHIPS IN PERCEPTION & ROBOTICS University of Pennsylvania • PhiladelPhia, Pa FOR MORE INFORMATION VISIT US AT http://igert.perception.upenn.edu FACULTY: GEOFFREY AGUIRRE - Cortical Organization DAVID BRAINARD - Visual Perception - Computational Modeling JOHANNES BURGE - Computational Modeling - Perceptual Systems - Vision KOSTAS DANIILIDIS - Visual Navigation - Recognition RUSSELL EPSTEIN - Cognitive Neuroscience - Scene Perception and Navigation JOSHUA GOLD - Neural Basis of Decision Making MICHAEL KAHANA - Cognitive Neuroscience - Memory KATHERINE KUCHENBECKER - Haptics - Touch Perception - Robotics VIJAY KUMAR - Robotics - Dynamics - Motor control TIMOTHY LUCAS - Brain-Computer Interface JAVIER MEDINA - Neural Basis of Motor Learning NICOLE RUST - Neural Basis of Object Recognition JIANBO SHI - Computer Vision VIJAY BALASUBRAMANIAN - Theoretical and Computational Neuroscience - Sensory Systems YALE COHEN - Neural Basis of Auditory Objects MARIA GEFFEN - Auditory perception - Computational audition DANIEL KODITSCHEK - Robotics - Computational Neuromechanics DANIEL LEE - Machine Learning - Robotics ISABEL MUZZIO - Neural Basis of Declarative Memory - Spatial Navigation ALAN STOCKER - Visual Perception - Computational Vision CAMILLO J. TAYLOR - Computer Vision - Vision Guided Robots

FacULTY: PER - Penn Engineeringigert/images/2014poster.pdf · DAviD BrAinArD - visual Perception ... - computational modeling JohAnnes BurGe - computational modeling - Perceptual

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Humans’ remarkable abilities to perceive, navigate and interact with natural environments dramatically eclipse those of current robotic systems. Research connecting perception and robotics investigates

questions such as: How do humans recognize objects in natural scenes? How can we make a robot

recognize and pick up objects in a kitchen? How do humans and animals find their way around? How can we build a car that drives itself? Interdisciplinary research will enable new insights into the performance

of human and animal perception as well as the design of new algorithms that will enable robots to perceive and act in complex scenes.

Graduate traineeships, with support from the National Science Foundation’s Integrative Graduate Education and Research Training (IGERT) program, are available to qualified applicants to cover tuition

costs and to provide stipends of up to $30,000 per year for five years of graduate training leading to a Ph.D. in a relevant discipline. IGERT is a National Science Foundation program intended to meet

the challenges of educating U.S. Ph.D. scientists and engineers with the skills needed for the career demands of the future.

GRaDUaTE TRaINEESHIPS IN

PERcEPTIoN & RoboTIcS

University of Pennsylvania • PhiladelPhia, Pa

FoR moRE INFoRmaTIoN vISIT US aThttp://igert.perception.upenn.edu

FacULTY:

Geoffrey AGuirre- cortical organization

DAviD BrAinArD- visual Perception- computational modeling

JohAnnes BurGe - computational modeling - Perceptual Systems- vision

KostAs DAniiliDis- visual Navigation- Recognition

russell epstein- cognitive Neuroscience- Scene Perception and Navigation

JoshuA GolD- Neural basis of Decision making

MichAel KAhAnA- cognitive Neuroscience- memory

KAtherine KuchenBecKer- Haptics- Touch Perception- Robotics

viJAy KuMAr- Robotics- Dynamics- motor control

tiMothy lucAs- brain-computer Interface

JAvier MeDinA- Neural basis of motor Learning

nicole rust- Neural basis of object Recognition

JiAnBo shi- computer vision

viJAy BAlAsuBrAMAniAn- Theoretical and computational Neuroscience- Sensory Systems

yAle cohen- Neural basis of auditory objects

MAriA Geffen- auditory perception- computational audition

DAniel KoDitscheK- Robotics- computational Neuromechanics

DAniel lee- machine Learning- Robotics

isABel Muzzio- Neural basis of Declarative memory- Spatial Navigation

AlAn stocKer- visual Perception- computational vision

cAMillo J. tAylor- computer vision- vision Guided Robots