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National Science Foundation
Engineering Directorate
Emerging Frontiers in Research and Innovation
NSF EFRI 2009 Grantees Conference
March 5-6, 2009
Westin Arlington Gateway
Arlington, Virginia

Research Overviews of the
NSF EFRI Grantees:
 
Chose a topic below to download a copy of the research overviews presented in previous NSF EFRI Grantees Conferences
(download a free PowerPoint viewer)

 

Class of 2007

Autoreconfigurable Engineering Systems (ARES) and Cyberinfrastructures.

Controlling the Autonomously Reconfiguring Factory"
Rus, Daniela, Massachusetts Institute of Technology

Embedded Distributed Simulation for Transportation System Management”
Hunter, Michael, Georgia Tech Research Corporation and Georgia Tech

Foundations for Reconfigurable and Autonomous Cyber-Physical Systems:
Cyber-Cities and Cyber-Universities

Dahleh, Munther A., Massachusetts Institute of Technology

Event-Driven Sensing for Enterprise Reconfigurability and Optimization
Cassandras, Christos G. Trustees of Boston University

Theory and Algorithms for Autonomous Reconfigurability of the National Air Transportation System
Barnhart, Cynthia, Massachusetts Institute of Technology

Cellular and Biological Engineering (CBE)

Engineering of cardiovascular cellular interfaces and tissue constructs
Beth Pruitt, Stanford University

Regulating human embryonic stem cell differentiation via the mechanical microenvironment
Sean Palecek, University of Wisconsin-Madison
 
Biological, Chemical and Mechanical Surface Cues for Cell Migration, Proliferation, and Differentiation: An Integrated Approach to Regeneration of New Tissues
Cato Laurencin, University of Connecticut Health Center

A Mulifaceted Approach to the Modeling of Angiogenesis
Roger Kamm, Massachusetts Institute of Technology

Emerging Frontiers in 3-D Breast Cancer Tissue Test Systems
Karen Burg, Clemson University

 “An Integrated Computational and Experimental Model for Biochemical and Electrical Interactions in Ion Channels and the Impact of Sialic Acid on Neuronal Function
Michael Betenbaugh, Johns Hopkins University

Topic B: Biofunctionalized Devices – On Chip Signaling and ‘Rewiring’ Bacterial Cell-Cell Communication
William Bentley, University of Maryland Biotechnology Institute

Class of 2008

RESIN (Resilient and Sustainable Infrastructures)

A Multi-Scale Design and Control Framework for Dynamically Coupled Sustainable and Resilient Infrastructures, with Application to Vehicle-to-Grid Integration
Jeffrey L. Stein, University of Michigan

Resilient and Sustainable Interdependent Electric Power and Communications Systems
Laine Mili, Virginia Tech

21st Century National Energy and Transportation Infrastructures: Balancing Sustainability, Costs, and Resiliency (NETSCORE-21)
James D. McCalley, Iowa State University

Optimization of conjunctive water supply and reuse systems with distributed treatment for high-growth, water-scarce regions
Kevin E. Lansey, University of Arizona

Sustainable Infrastructures for Energy and Water Supply (SINEWS)
John C. Crittenden, Arizona State University

Interdependence, Resilience and Sustainability of Infrastructures for Biofuel Development
Ximing Cai, University of Illinois, Urbana/Champaign

Assessing and Managing Cascading Failure Vulnerabilities of Complex, Interdependent, Interactive, Adaptive Human-based Infrastructure Systems
Robert G. Bea, University of California, Berkeley

The Interface of Infrastructures, Markets, and Natural Cycles - Innovative Modeling and Control Mechanisms for Managing Electricity, Water and Air Quality in Texas
David T. Allen, University of Texas, Austin

COPN (Cognitive Optimization and Prediction)

Neuroscience and Neural Networks for Engineering the Future Intelligent Electric Power Grid
Ganesh K. Venayagamoorthy, University of Missouri, Rolla

Reverse-engineering the Human Brain's Ability to Control the Hand
Francisco J. Valero-Cuevas, University of South California

Dynamics of Neural Networks on a Planar Patch-Clamp Array:  Training, Identification, and Control
Russell L. Tedrake, Massachusetts Institute of Technology

Deep Learning in the Mammalian Visual Cortex
Andrew Y. Ng, Stanford University

 
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