ASU wins record 14 NSF career awards
ASU wins record 14 NSF career awards
April 28, 2017
April 28, 2017
Arizona State University has earned 14 National Science Foundation early career faculty awards, ranking second among all university recipients for 2017 and setting an ASU record. The awards total $7 million in funding for the ASU researchers over five years.
ASU’s Ira A. Fulton Schools of Engineering earned 10 awards, placing it alongside the University of Illinois at Urbana-Champaign and Georgia Institute of Technology as the top three engineering schools to receive the awards. This year’s award total ranks ASU above top engineering schools including Stanford University, Carnegie Mellon University, California Institute of Technology and the University of California, Berkeley.
The NSF’s Faculty Early Career Development (CAREER) Program identifies the nation’s most promising junior faculty members and provides them with funding to pursue outstanding research, excellence in teaching and the integration of education and research.
To date, Illinois has garnered 17 overall CAREER awards for 2017, the University of Michigan 12, and Georgia Tech, Massachusetts Institute of Technology, and Pennsylvania State University each hold 11 awards. The award process will continue through June.
Ten awards for the Fulton Schools is a record for the nation’s largest engineering school, says Dean Kyle Squires. “I’m proud that ASU attracts faculty and students whose powerful ideas can result in transformational breakthroughs,” he says. “These awards exemplify our faculty’s commitment to impactful research with the CAREER awards enabling novel integration of their research into education and outreach activities, and in ways that impact an enormous array of applications in engineering and computer science. Junior faculty success in the NSF and similar programs with other federal funding agencies indicates the strength and potential growth of our faculty.”
ASU projects funded by this year’s awards include automated detection of computer network vulnerabilities, understanding heart attacks, keeping power grids functioning during disasters and predicting earthquakes and volcanoes.
This year’s ASU NSF CAREER award recipients include:
Ira A. Fulton Schools of Engineering:
Mehdi Nikkhah, assistant professor, School of Biological and Health Systems Engineering: Myocardial infarction (heart attack) is a leading cause of death, but the underlying biological mechanisms that lead to damage to the heart during a heart attack are not well understood. This study seeks to uncover those mechanisms to improve our fundamental understanding of heart disease and its causes.
Adam Doupé, assistant professor, School of Computing, Informatics, and Decision Systems Engineering: Sensitive data breaches are often caused by overlooked vulnerabilities in web applications, and current solutions to identifying them — hiring white-hat human hackers, for example — are not cost-effective. This project advances the state-of-the-art in automated black-box vulnerability analysis tools. By using open-sourced tools and techniques, this approach can find unknown vulnerabilities in any web application cost-effectively.
Hanghang Tong, assistant professor, School of Computing, Informatics, and Decision Systems Engineering: Improving the ability of a network to function during a disturbance (e.g. a power grid during a hurricane or when under attack) is an ongoing challenge. Existing work on network robustness is essentially observational. Through better theories and algorithms that are effective, scalable, applicable and adaptable, this project seeks to design strategies for intervening and improving network robustness, and to validate the proposed techniques in the context of real-world applications such as intelligent transportation systems and online social collaboration networks.
Fengbo Ren, assistant professor, School of Computing, Informatics, and Decision Systems Engineering: Long-term monitoring of the Internet-of-Things (IoT) is constrained by sensor energy efficiency. This project will develop a data-driven, hardware-friendly IoT framework to fill unmet energy efficiency needs, especially for wearable applications. Applications include monitoring air quality, radiation, water quality, hazardous chemicals and other environmental indicators.
Carole-Jean Wu, assistant professor, School of Computing, Informatics, and Decision Systems Engineering: A smartphone's user satisfaction is a balance between computation performance and battery performance; energy efficiency, in turn, is tightly coupled to computation performance and surface temperature management. This research tackles the problem of handheld device design from the perspective of user satisfaction driven by the co-optimization of performance, temperature management and energy efficiency.
Umit Ogras, assistant professor, School of Electrical, Computer and Energy Engineering: Flexible electronics technologies have the potential to transform computing by enabling bendable and stretchable systems at a low cost, including wearable electronics, medical sensing and rolling displays. However, the performance and capabilities of purely flexible electronics are currently much more limited than for silicon technology. Flexible hybrid electronics (FHE) integrates rigid silicon chips and printed electronics to bridge the gap between today's complex systems and flexible electronics. This project provides a systematic approach to designing wearable systems and arbitrarily shaped objects, such as electronic patches that can examine movement disorders outside of clinical environments.
Jae-sun Seo, assistant professor, School of Electrical, Computer and Energy Engineering: This project addresses major hardware and software design challenges inherent in building computers that can perform cognitive tasks (e.g., learning, recognition) as well as humans, taking a major step toward building brain-inspired intelligent computing systems that are ultra-energy-efficient for cognitive tasks in computer vision, speech, robotics and biomedical applications.
Jay Oswald, assistant professor, School for Engineering of Matter, Transport and Energy: This project supports fundamental research on how material structure at the molecular scale affects macroscopic physical properties of semi-crystalline plastics. Its goal is to foster innovation in plastics manufacturing and shorten today’s typical 10- to 20-year development cycle for materials development.
Robert Wang, assistant professor, School for Engineering of Matter, Transport and Energy: Materials that enable advanced control over the transmission of electricity and light are known as electronic and photonic materials, respectively. These materials have made possible numerous modern technologies such as laptops, cellular phones, fiber optics, lasers and microscopes. In contrast, technological control over sound and heat has lagged far behind. This project focuses on creating phononic materials that consist of organized nanoparticle-molecule assemblies that possess vibrational characteristics that do not arise in naturally occurring materials. These novel assemblies will then be used to create filters, mirrors and one-way valves that manipulate the transmission of sound and heat.
Yueming (Lucy) Qiu, assistant professor, The Polytechnic School: Using a dataset from the Phoenix metropolitan area, this project creates a platform for accurate and scalable analysis of home energy efficiency projects, taking into consideration such factors as the interplay of technologies and occupant behaviors, that will translate into statistical evidence of realized energy savings.
College of Liberal Arts and Sciences:
Christy Till, assistant professor, School of Earth and Space Exploration: Monitoring the composition of volcanic gas emissions, local ground surface deformation and the size and location of volcanism-related earthquakes provides a wealth of information about magma storage and movement beneath active volcanoes. Despite the volume of information collected about volcanism-related earthquakes, there is a lack of sufficient context to interpret those data in ways that enable the prediction of coming eruptions. This project will reconstruct detailed histories of magma bodies in the days and years leading to past eruptions at three different explosive volcanoes, which will then be used to develop models for eruption forecasting and volcano hazard assessments.
Ryan Trovitch, assistant professor, School of Molecular Sciences: Long-chain polymer molecules are used in agriculture, food, healthy and safety and food industries. For more than half a century, for example, silicone polymers have been used in consumer products such as contact lenses, flexible tubing and medical implants. This project seeks ways to overcome the significant challenges of making catalysts to prepare polymers from abundant metals, such as manganese, rather than costly precious metals like platinum, iridium and silver. The development of manganese-based catalysts for silicone preparation would represent a significant advance in sustainable chemistry.
Gary Moore, assistant professor, School of Molecular Sciences: Catalysts are chemical substances that provide alternative pathways for chemical reactions, and some are difficult to recover when the process is completed. Attaching these catalysts to a solid surface improves their recoverability and provides additional pathways for use. This project is developing innovative ways to create and assemble polymeric surface coatings that attach molecular catalysts to solids in ways that are useful for solar energy capture and storage. The catalyst-polymer construct stabilizes the component materials and enhances their utility for generating fuels and other value-added chemical products, with minimal environmental impact.
Steve Presse, associate professor, School of Molecular Sciences and Department of Physics: The living cell is an active environment where large biological molecules (such as proteins or DNA) move, collide and react. Current experiments observe these processes indirectly in living systems and, as a result, interpreting these data to understand and mathematically describe what happens inside cells is challenging. This project seeks to contribute to the development of quantitative biology by considering how data-driven models can be inferred from currently available experimental data. This modeling will produce theoretical frameworks that capture how the diffusion of biomolecules and their fluctuating shapes ultimately sustain life.
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