NSF Expeditions, 2008-2012: Difference between revisions
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* Lead PI: Daniela Rus, Massachusetts Institute of Technology (MIT) | * Lead PI: Daniela Rus, Massachusetts Institute of Technology (MIT) | ||
* Collaborators: University of Pennsylvania and Harvard University | * Collaborators: University of Pennsylvania and Harvard University | ||
* This project envisions a future where 3-D robotic systems can be produced and designed using 2-D desktop technology fabrication methods. If this feat is achieved, it would be possible for the average person to design, customize and print a specialized robot in a matter of hours. Currently, it takes years and many resources to produce, program and design a functioning robot. This new project would completely automate the process, from sketches on-demand, anywhere, and with the skill of a team of professional engineers, leading to potential transformations in advanced manufacturing. | |||
This project envisions a future where 3-D robotic systems can be produced and designed using 2-D desktop technology fabrication methods. If this feat is achieved, it would be possible for the average person to design, customize and print a specialized robot in a matter of hours. Currently, it takes years and many resources to produce, program and design a functioning robot. This new project would completely automate the process, from sketches on-demand, anywhere, and with the skill of a team of professional engineers, leading to potential transformations in advanced manufacturing. | |||
'''Making Sense at Scale with Algorithms, Machines and People (AMP)''' | '''Making Sense at Scale with Algorithms, Machines and People (AMP)''' | ||
* Lead PI: Michael Franklin, University of California (UC) Berkeley | * Lead PI: Michael Franklin, University of California (UC) Berkeley | ||
* AMP will tackle the challenge known as the Big Data problem, in which current data analytics fall short in making sense of the volume, diversity and complexity of data being generated by computers, sensors and scientific instruments; media such as images and video; and free-form tweets, text messages, blogs and documents. AMP seeks to turn this knowledge into insight, to uncover the keys to solving huge societal problems, from improving productivity and efficiency and creating new economic opportunities, to unlocking discoveries in medicine, science and the humanities. The team will focus on key societal applications, including: cancer genomics and personalized medicine; large-scale sensing for traffic prediction, environmental monitoring, and urban planning; and network security. | |||
AMP will tackle the challenge known as the Big Data problem, in which current data analytics fall short in making sense of the volume, diversity and complexity of data being generated by computers, sensors and scientific instruments; media such as images and video; and free-form tweets, text messages, blogs and documents. AMP seeks to turn this knowledge into insight, to uncover the keys to solving huge societal problems, from improving productivity and efficiency and creating new economic opportunities, to unlocking discoveries in medicine, science and the humanities. The team will focus on key societal applications, including: cancer genomics and personalized medicine; large-scale sensing for traffic prediction, environmental monitoring, and urban planning; and network security. | |||
'''ExCAPE: Expeditions in Computer Augmented Program Engineering''' | '''ExCAPE: Expeditions in Computer Augmented Program Engineering''' | ||
* Lead PI: Rajeev Alur, University of Pennsylvania | * Lead PI: Rajeev Alur, University of Pennsylvania | ||
* Collaborators: Cornell, MIT, University of California Los Angeles, University of Illinois at Urbana-Champaign, University of Maryland, University of Michigan, UC Berkeley, Rice University | * Collaborators: Cornell, MIT, University of California Los Angeles, University of Illinois at Urbana-Champaign, University of Maryland, University of Michigan, UC Berkeley, Rice University | ||
* ExCAPE aims to change computer programming from the tedious, error-prone, purely manual task it has always been to one in which a programmer and an "automated program synthesis tool" collaborate to generate software that meets its specifications. Computers have revolutionized daily life, and yet the way computers are programmed has changed little in the last several decades. The ExCAPE team brings together expertise in theoretical foundations (computer-aided verification, control theory, program analysis), design methodology (human-computer interaction, model-based design, programming environments), and applications (concurrent programming, network protocols, robotics, system architecture) to pursue research focused on developing new computational engines for transformation and integration of synthesis artifacts, and effective methods for programmer interaction and feedback. | |||
ExCAPE aims to change computer programming from the tedious, error-prone, purely manual task it has always been to one in which a programmer and an "automated program synthesis tool" collaborate to generate software that meets its specifications. Computers have revolutionized daily life, and yet the way computers are programmed has changed little in the last several decades. The ExCAPE team brings together expertise in theoretical foundations (computer-aided verification, control theory, program analysis), design methodology (human-computer interaction, model-based design, programming environments), and applications (concurrent programming, network protocols, robotics, system architecture) to pursue research focused on developing new computational engines for transformation and integration of synthesis artifacts, and effective methods for programmer interaction and feedback. | |||
'''Making Socially Assistive Robots''' | '''Making Socially Assistive Robots''' | ||
* Lead PI: Brian Scassellati, Yale University | * Lead PI: Brian Scassellati, Yale University | ||
* Collaborators: MIT, University of Southern California, Stanford University | * Collaborators: MIT, University of Southern California, Stanford University | ||
* This Expedition will develop the fundamental computational techniques that will enable the design, implementation and evaluation of robots that encourage social, emotional and cognitive growth in children. Critical societal problems require sustained, personalized support that supplements the efforts of educators, parents and clinicians. For example, clinicians and families struggle to provide individualized educational services to children with social and cognitive deficits, whose numbers have quadrupled in the U.S. in the last decade alone. In many schools, educators struggle to provide language instruction for children raised in homes where a language other than English is spoken, the fastest-growing segment of the school-age population. This Expedition aims to support the individual needs of these children with socially assistive robots that help to guide the children toward long-term behavioral goals that are customized to the particular needs of each child and that develop and change as the child does. | |||
This Expedition will develop the fundamental computational techniques that will enable the design, implementation and evaluation of robots that encourage social, emotional and cognitive growth in children. Critical societal problems require sustained, personalized support that supplements the efforts of educators, parents and clinicians. For example, clinicians and families struggle to provide individualized educational services to children with social and cognitive deficits, whose numbers have quadrupled in the U.S. in the last decade alone. In many schools, educators struggle to provide language instruction for children raised in homes where a language other than English is spoken, the fastest-growing segment of the school-age population. This Expedition aims to support the individual needs of these children with socially assistive robots that help to guide the children toward long-term behavioral goals that are customized to the particular needs of each child and that develop and change as the child does. | |||
Revision as of 18:32, 1 September 2012
This pages contains a list of NSF Expeditions projects that were started in 2007 to 2012.
2007
2008
2009
2010
2011
2012
An Expedition in Computing for Compiling Functional Physical Machines
- Lead PI: Daniela Rus, Massachusetts Institute of Technology (MIT)
- Collaborators: University of Pennsylvania and Harvard University
- This project envisions a future where 3-D robotic systems can be produced and designed using 2-D desktop technology fabrication methods. If this feat is achieved, it would be possible for the average person to design, customize and print a specialized robot in a matter of hours. Currently, it takes years and many resources to produce, program and design a functioning robot. This new project would completely automate the process, from sketches on-demand, anywhere, and with the skill of a team of professional engineers, leading to potential transformations in advanced manufacturing.
Making Sense at Scale with Algorithms, Machines and People (AMP)
- Lead PI: Michael Franklin, University of California (UC) Berkeley
- AMP will tackle the challenge known as the Big Data problem, in which current data analytics fall short in making sense of the volume, diversity and complexity of data being generated by computers, sensors and scientific instruments; media such as images and video; and free-form tweets, text messages, blogs and documents. AMP seeks to turn this knowledge into insight, to uncover the keys to solving huge societal problems, from improving productivity and efficiency and creating new economic opportunities, to unlocking discoveries in medicine, science and the humanities. The team will focus on key societal applications, including: cancer genomics and personalized medicine; large-scale sensing for traffic prediction, environmental monitoring, and urban planning; and network security.
ExCAPE: Expeditions in Computer Augmented Program Engineering
- Lead PI: Rajeev Alur, University of Pennsylvania
- Collaborators: Cornell, MIT, University of California Los Angeles, University of Illinois at Urbana-Champaign, University of Maryland, University of Michigan, UC Berkeley, Rice University
- ExCAPE aims to change computer programming from the tedious, error-prone, purely manual task it has always been to one in which a programmer and an "automated program synthesis tool" collaborate to generate software that meets its specifications. Computers have revolutionized daily life, and yet the way computers are programmed has changed little in the last several decades. The ExCAPE team brings together expertise in theoretical foundations (computer-aided verification, control theory, program analysis), design methodology (human-computer interaction, model-based design, programming environments), and applications (concurrent programming, network protocols, robotics, system architecture) to pursue research focused on developing new computational engines for transformation and integration of synthesis artifacts, and effective methods for programmer interaction and feedback.
Making Socially Assistive Robots
- Lead PI: Brian Scassellati, Yale University
- Collaborators: MIT, University of Southern California, Stanford University
- This Expedition will develop the fundamental computational techniques that will enable the design, implementation and evaluation of robots that encourage social, emotional and cognitive growth in children. Critical societal problems require sustained, personalized support that supplements the efforts of educators, parents and clinicians. For example, clinicians and families struggle to provide individualized educational services to children with social and cognitive deficits, whose numbers have quadrupled in the U.S. in the last decade alone. In many schools, educators struggle to provide language instruction for children raised in homes where a language other than English is spoken, the fastest-growing segment of the school-age population. This Expedition aims to support the individual needs of these children with socially assistive robots that help to guide the children toward long-term behavioral goals that are customized to the particular needs of each child and that develop and change as the child does.
