Research Alert

April 30, 2009

Read the research blog Further Findings. This week the blog highlights a quirky but key prop in the Robert De Niro Collection at the Harry Ransom Center.

Research Prizes and Honors

[Have you or a colleague won a research-related prize or honor? Let the Research Alert know.]

ENGINEER ELECTED TO AMERICAN ACADEMY OF ARTS & SCIENCES

Adam Heller, an acclaimed chemical engineering research professor and professor emeritus at The University of Texas at Austin, has been elected a fellow into the American Academy of Arts & Sciences (AAAS), along with Nobel Peace Prize laureate Nelson Mandela, actor James Earl Jones, U.S. Secretary of Defense Robert Gates and singer/humanitarian Bono.

In 2008, Heller received the National Medal of Technology and Innovation for his contributions to electrochemistry and bioelectrochemistry that led to the development of products that have improved the quality of life of millions.

PROFESSOR IN COMPUTATIONAL MECHANICS ELECTED
MEMBER OF THE NATIONAL ACADEMY OF SCIENCES

Thomas J.R. Hughes, an innovator in computational mechanics, has been elected a member of the National Academy of Sciences, one of the highest honors given to a scientist or engineer in the United States.

He was one of 72 elected nationally to the academy this year.

Hughes is a professor in the Department of Aerospace Engineering and Engineering Mechanics in the Cockrell School of Engineering and a member in the Institute for Computational Engineering and Sciences, where he holds the Applied Mathematics Chair III.

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News and Information

RESEARCH RECOGNITION

We want to make sure that the listings on the Research Recognition page are up-to-date and accurate. Please let us know if your name is missing from the listing of an award you received or an organization of which you are a member.

If so, send an e-mail to vpr@www.utexas.edu.

OSP NOTICE REGARDING GRANTS.GOV SUBMISSIONS

Grants.gov continues to have major issues with no end in sight. As we anticipate an increasing volume of Grants.gov proposals associated with the American Recovery and Reinvestment Act of 2009 (ARRA) as well as ongoing deadlines, we must require that proposals in response to opportunities supported by Cayuse be submitted using Cayuse. We will make every effort to remind you when the Proposal Review Form is received but should a Grants.gov application be turned in using Adobe forms when the funding opportunity is available on Cayuse, OSP will return your proposal and request that you upload your proposal on Cayuse. A PowerPoint attachment with step-by-step instructions to view and update opportunities on Cayuse is online.

Cayuse supports over 90 percent of opportunities posted on Grants.gov including the ARRA opportunities. A full list of supported agencies (PDF) is here. (Download Adobe Reader.)

Cayuse is a valuable resource that minimizes the administrative time required for processing proposals, assists PIs in preparing the proposal as it checks for errors as you enter information, and maximizes OSP’s efficiency in reviewing, submitting and validating the proposal. Your cooperation is appreciated.

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Quoted—UT Researchers in the News

[A sampling of recent quotes by university faculty members and researchers. To be included in this section, let the Research Alert know when you or a colleague have been quoted.]

The New York Times
June 9, 2008
April 23, 2009
HEADLINE: Want to Go Faster? You Need a Trainer

The biggest effects are in untrained people, said Hirofumi Tanaka, an exercise physiologist at the University of Texas. ''Elite athletes' performance is getting too close to the ceiling or upper limit,'' he said. ''There is not much space to improve.''

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Research Opportunities

Important university research deadlines:
Awards and Grants
Limited Submissions

AMERICAN RECOVERY AND REINVESTMENT ACT
The University of Texas at Austin Stimulus Package Web page is online.

DEPARTMENT OF ENERGY
Advanced Research Projects Agency-Energy (ARPA-E)
Deadline: Concept paper, June 2, 2009
ARPA-E is a new organization within the Department of Energy, created specifically to foster research and development of transformational energy-related technologies. Transformational technologies are by definition technologies that disrupt the status quo. They are not merely better than current technologies, they are significantly better. Often, a technology is considered transformational when it so outperforms current approaches that it causes an industry to shift its technology base to the new technology. The Nation needs transformational energy-related technologies to overcome the threats posed by climate change and energy security, arising from its reliance on traditional uses of fossil fuels and the dominant use of oil in transportation.

FUNDING OPPORTUNITIES

ENVIRONMENTAL PROTECTION AGENCY

Healthy Indoor Environments Projects
Request for Proposals FY 2009

Deadline: June 16, 2009

NATIONAL INSTITUTES OF HEALTH
Women's Mental Health in Pregnancy and the Postpartum Period

Deadlines: Deadline: June 5, 2009

Pilot Intervention and Services Research Grants (NIMH)

http://grants.nih.gov/grants/guide/pa-files/PAR-09-173.html

Deadline: June 16, 2009

NATIONAL SCIENCE FOUNDATION
Biomolecular Systems Cluster
Deadline: July 12, 2009

Partnerships in Astronomy and Astrophysics Research and Education
Deadline: Aug. 3, 2009

Computing and Communication Foundations: Core Programs
Deadlines (submission windows): Medium Projects: Aug. 1, 2009-Aug. 30, 2009; Large Projects: Nov. 1, 2009-Nov. 28, 2009; Small Projects: Dec. 1, 2009-Dec. 17, 2009

Computer and Network Systems: Core Programs
Deadlines (submission windows): Medium Projects: Aug. 1, 2009-Aug. 30, 2009; Large Projects: Nov. 1, 2009-Nov. 28, 2009; Small Projects: Dec. 1, 2009-Dec. 17, 2009

Information and Intelligent Systems: Core Programs
Deadlines (submission windows): Medium Projects: Aug. 1, 2009-Aug. 30, 2009; Large Projects: Nov. 1, 2009-Nov. 28, 2009; Small Projects: Dec. 1, 2009-Dec. 17, 2009

CISE Cross-Cutting Programs: FY 2010
Deadlines (submission windows): Medium Projects: Aug. 1, 2009-Aug. 30, 2009; Large Projects: Nov. 1, 2009-Nov. 28, 2009; Small Projects: Dec. 1, 2009-Dec. 17, 2009

OTHER FUNDING OPPORTUNITIES
WateReuse Foundation
Social, Environmental, Natural and Other Factors That Influence Judgments and Decisions about
Deadline: May 15, 2009

Brain Tumor Funders’ Collaborative
New Approaches for Developing Tools for Non-Invasive or Minimally-Invasive Monitoring of Pediatric and Adult Gliomas
Deadline: June 15, 2009

Research Project

[Let the Research Alert know about your research projects.]

Pilot: Leveraging Human Creativity with Machine Discovery

RESEARCHER: Risto Miikkulainen, professor, Department of Computer Sciences, principal investigator
AGENCY: National Science Foundation
AMOUNT: $199,967

A challenge in machine learning is to devise methods that allow incorporating human insight into the automated learning process. Current learning methods employ representations that make it difficult to encode simplification and specific examples, and learning is based on random exploration that is difficult to direct.

NEAT is a learning system where the learned decision policy is represented in neural networks and learned through evolutionary optimization, i.e. genetic algorithms. NEAT evolves network structure as well as weights, which makes it possible in principle to incorporate human guidance in three ways: (1) building a gradually more complex network structure through shaping from simple to more complex tasks, (2) training networks with examples of human behavior, and (3) converting human-designed rules into network structures.

These techniques will be developed and evaluated in the domain of designing complex behaviors for autonomous agents in the OpenNERO 3D simulation environment. In a series of human subject experiments, the solutions designed through human-guided neuroevolution will be compared to those designed by human engineers and to those discovered by neuroevolution alone, verifying that (a) the human-guided approach results in better solutions, and (b) those solutions are more creative.

The result of this project is a machine learning approach will allow engineers to generate creative designs to many real-world sequential decision problems. Applications of this approach will lead to safer and more efficient vehicle, traffic and robotic control, improved process and manufacturing optimization, and more efficient computer and communication systems. It will also make the next generation of video games possible, with characters that exhibit realistic and adaptive behaviors; such technology should lead to more effective educational and training games in the future.

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For more information, contact: Tim Green, Office of the Vice President for Research.

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