"Engineering Research Advancement"

Researchers in the Ira A. Fulton Schools of Engineering are putting knowledge into action. We look for innovative solutions to global challenges and strive to improve the quality of individual lives. Our research endeavors are use-inspired, entrepreneurial, educational and collaborative.

ASU, NGA to address national security risks posed by climate change

Posted by on Jul 7, 2014 in Faculty, Research | 0 comments

ASU, NGA to address national security risks posed by climate change

Arizona State University (ASU) was selected for a competitive five-year award of $20 million by the National Geospatial-Intelligence Agency (NGA) to launch a research partnership, effective June 1, 2014, to explore approaches for anticipating and mitigating national security risks associated with climate change.

 

Known as the Foresight Initiative, the cooperative agreement venture will explore how the effects of climate change on resources, such as water, food, and energy, could contribute to political unrest and instability and gain insights to sustainability and resilience strategies for mitigating the effects.

Nadya Bliss is the principal investigator for the Foresight Initiative. Bliss is assistant vice president for research strategy with ASU’s Office of Knowledge Enterprise Development, and a professor of practice in the computer science and engineering program in the School of Computing, Informatics, and Decisions Systems Engineering, one of ASU’s Ira A. Fulton Schools of Engineering.

Seven other Fulton Schools of Engineering faculty members are part of the Foresight Intiative team: professor Paul Westerhoff (School of Sustainable Engineering and the Built Environment); professor Gail-Joon Ahn, professor Huan Liu, associate professor Hasan  Davulcu  and assistant professor Ross Maciejewski (School of Computing, Informatics, and Decision Systems Engineering); associate professor Daniel Bliss (School of Electrical, Computer and Energy Engineering); and professor Nancy Cooke (program chair, Cognitive Science and Engineering).

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Research on water resources earns Mays top award by ASCE

Posted by on Mar 19, 2014 in Faculty, Research | 0 comments

Photo of Larry Mays

Larry Mays, professor of civil and environmental engineering in the School of Sustainable Engineering and the Built Environment, one of ASU’s Ira A. Fulton Schools of Engineering

Larry Mays, a professor of civil and environmental engineering at Arizona State University, will receive the Julian Hinds Award for his unparalleled research on water resources and hydrosystems.

Mays is a professor in the School of Sustainable Engineering and the Built Environment, one of ASU’s Ira A. Fulton Schools of Engineering. He began his academic career at the University of Texas at Austin for 13 years followed by 25 years at ASU.

The Julian Hinds Award, presented by the American Society of Civil Engineers, recognizes notable performance, long years of distinguished service or specific actions that advance engineering in the field of planning, development and management of water resources. It is the highest honor for water resources planning and systems analysis researchers in ASCE.

The award citation, from the Society’s Environmental and Water Resources Institute, states that Mays is being recognized “for his research on water resources and hydrosystems engineering, addressing optimization and risk/reliability analysis for their design, management and operation and his authoritative text and reference books that have had worldwide impact.”

Mays will receive the award in June, during the EWRI Congress in Portland, Ore., where he will also deliver the Julian Hinds Lecture.

Mays was nominated by Kevin E. Lansey, head of the Department of Civil Engineering and Engineering Mechanics at the University of Arizona’s College of Engineering.

“[Mays] research on risk methods and, although now commonplace, linking simulation and optimization tools were groundbreaking in the late 1980s,” Lansey wrote. “He provided a basis for risk-based hydraulic design. Many of these concepts are now incorporated in the Corps of Engineers risk-based design approach.”

Lansey also wrote that graduate student mentoring has been a major focus of Mays’ career, and that he had supervised to completion 31 doctoral students.

Mays has been the author, co-author or editor-in-chief of 23 books. His text and reference books are used around the world.

Mays is a fellow of ASCE, and also a fellow of the International Water Resources Association. He has been a representative to the Universities Council on Water Resources and has served as a member and president of the Council’s Board of Directors. Among his other honors, he received a distinguished alumnus award from the Department of Civil Engineering at the University of Illinois.

He is an avid photographer of ancient water systems around the world and has published on this topic. His interests also include alpine skiing, fly fishing, scuba diving, and welding and woodworking projects.

Media Contact:
Judy Nichols, judith.nichols@asu.edu
(480) 965-9248
Ira A. Fulton Schools of Engineering

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Newman’s research aims at more energy-efficient supercomputing

Posted by on Mar 13, 2014 in Faculty, Research | 0 comments

Nathan Newman

Arizona State University engineering professor Nathan Newman.

 

We have progressed far beyond the age of the computer into the age of the supercomputer center, says Arizona State University electrical engineer Nathan Newman.

Governments, economies, healthcare services, power and transportation systems and national security operations now depend increasing on reliable access to the computing technology that enables information gathering, storing and analysis on massive scales that can be provided only by large interconnected clusters of high-powered computers.

With that growing dependence comes growing demand for ever-faster and expanding computing capacity, says Newman, a professor in the School for the Engineering of Matter, Transport and Energy, one of ASU’s Ira A. Fulton Schools of Engineering.

The big challenge in meeting the demand is the great amount of electrical power it would take to increase supercomputing capabilities using current semiconductor technologies and operating systems.

“It has gotten to the point that supercomputer centers cannot do much more than they are capable of doing right now without a paradigm change in how they operate,” Newman explains.

That situation also will make it difficult for popular providers of search engines, web portals and other Internet services, such as Google and Yahoo, to significantly improve and expand upon what they can offer customers, he adds.

Much of his research lab’s effort is now focused on breaking through current technological limits by developing computer logic and memory devices that can enable massive improvements in the speed and capacity of supercomputing facilities.

A team that includes Newman’s research group at ASU, the Northrop Grumman corporation and Michigan State University researchers has recently been selected by the Intelligence Advanced Research Projects Activity (IARPA) — an agency under the office of the Director of National Intelligence — to collaborate on a multimillion-dollar project to make that advance.

The larger supercomputing facilities, such as those run by Yahoo, Google and the National Security Agency, now use an amount of energy equivalent to about 10 percent of the energy that a nuclear power plant can generate – or enough energy to meet the power demands of about 100,000 homes. Increasing the amount of computing by a factor of 10 is prohibitive due to the tremendous cost of this much additional energy alone, Newman says.

Newman’s research team is optimizing the use of new superconducting materials to develop a new kind of digital circuit. The circuit could potentially enable supercomputer systems to require much less energy to operate effectively. The new digital circuits can be developed using current fabrications facilities, Newman says.

His group’s work with digital-circuit technology has recently led to development of a computer memory device that operates more rapidly and more energy-efficiently. It could enable supercomputing systems to operate as much as 50 times faster and perform 50 more times the number of operations while using 50 times less energy, Newman says.

The advances spring in large part from work began decades ago by physicist John Rowell and his colleagues at Bell Laboratories, which achieved several breakthroughs that paved the way for today’s advanced electronics and computing technology.

Rowell, a member of the National Academy of Engineering and the Royal Society and the National Academy of Sciences, has joined ASU as a research professor in the School for Engineering of Matter, Transport and Energy, and teamed with Newman’s research group.

Rowell was a pioneer in revealing the basic physics involved in the workings of superconducting devices and discovering what materials enabled the devices to perform most effectively, Newman says.

Newman, the Lawrence Professor of Solid State Science at ASU completed a two-year term in January as chair of the U.S. Committee on Superconductor Electronics. He has authored or co-authored more than 200 technical papers published in science and engineering research journals and been awarded 12 U.S. patents.

Newman is a Fellow of the American Physical Society and the Institute of Electrical and Electronics Engineers (IEEE), and editor for materials science and engineering subject matter for the journal IEEE Transactions of Applied Superconductivity. He is a winner of the IEEE Van Duzer Prize for awarded annually for the best research paper published in that journal.

Media Contact:
Joe Kullman, joe.kullman@asu.edu
(480) 965-8122
Ira A. Fulton Schools of Engineering

 

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‘Big data’ reveals human interests, behavior

Posted by on Mar 11, 2014 in Faculty, Research | 0 comments

YingCheng Lai

Arizona State University engineering professor Ying-Cheng Lai

Information technology advances are leading to ever-growing accumulations of “big data,” making it feasible to quantify more things long thought immeasurable.

Arizona State University professor Ying-Cheng Lai and his research partners are combining expertise in computer science, engineering, mathematics, statistics and physics in analyzing big data to explore human-interest dynamics.

They want to see if it’s possible to identify patterns in what motivates people to become interested in particular things, what makes them maintain certain interests and what causes them to lose interest.

“Big data now provides a platform for exploring the dynamics of why people change their minds about certain things,” Lai says. “Are there intrinsic rules that govern when something interests people, and what influences us to become interested?”

Learning what attracts and holds peoples’ interests is a door to better understanding and predicting human behavior – providing knowledge that can be valuable to business, economics, social sciences, healthcare, even national defense, Lai says.

Lai is a professor in the School of Electrical, Computer and Energy Engineering, one of ASU’s Ira A. Fulton Schools of Engineering.

He is working on the human-interest dynamics project with ASU electrical engineering research scientist Zi-Gang Huang and graduate student Zhi-Dan Zhao.

Huang is also a researcher with the Institute of Computational Physics and Complex Systems at Lanzhou University in China. Zhao is also with the Web Sciences Center at the University of Electronic Science and Technology of China.

Other team members are Zimo Yang, Tao Zhou and Zike Zhang, all with the Web Sciences Center in China. Zhang is also with the Institute for Information Economy at Hangzhou Normal University in China.

The team is working with large data sets being provided by three large companies in China – two e-commerce companies and a mobile communications business.

Those data sets are big enough to eventually give researchers a credible indication of about how much of peoples’ decision-making follows patterns, or if it’s mostly random and chaotic, Lai says.

By examining and analyzing how millions of people are making decisions online or on mobile phones about using the companies’ services, researchers expect to understand how a wide variety of factors attracts, or fails to attract, individuals’ interest.

Lai, who brings a physics perspective to solving engineering challenges, is providing a key aspect to the project: the application of a statistical physics approach to the study of big data.  As he explains, trying to analyze a large amount of data to seek trends and patterns is similar to what physicists do when examining millions of particles of matter and trying to understand the nature of all the interactions of the particles and the affects of those interactions.

“It is difficult to pin down the exact relationships between all the particles and how all the variables are changing, particularly when changes in the microscopic particles are having an impact on a large macroscopic system,” he says. However, it is possible to deduce from microscopic interactions how macroscopic variables depend upon each other, the so-called “scaling relations,” he adds.

Having information on the massive scale provided by big data can enable researchers to get a clearer picture despite the variables and randomness in peoples’ decision-making.

“We should be able to develop some predictive capability,” Lai says.

Such predictive findings about human-interest dynamics could aid psychiatrists in better diagnosing patients’ conditions and prescribing more effective mental-health therapies.

Using knowledge of what drives interest to predict human behavior could also be valuable in devising national security and defense strategies, and in guiding the engineering and design of transportation systems and similar high-interaction environments.

By providing a deeper understanding of what shapes and changes consumer interests and behavior, the research promises to offer advertising, marketing and product-development industries a more solid basis for long-term business planning and strategy.

Lai says the project is the first thoroughly systematic attempt to probe the intricacies of the dynamics at work when people develop – or lose – interest in various things. “We expect our findings to have applications in many more areas.”

To read more details about the project, see the research paper by Lai’s team published in journal Scientific Reports.

Media Contact:
Joe Kullman, joe.kullman@asu.edu
(480) 965-8122
Ira A. Fulton Schools of Engineering

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Fainekos’ work on embedded cyber-physical systems earns NSF CAREER award

Posted by on Mar 3, 2014 in Faculty, Research | 0 comments

Georgios Fainekos

Assistant professor Georgios Fainekos

Highly complex automation and autonomously controlled machinery are certain to be ever more present in daily life. Transportation, energy, manufacturing and aerospace systems, healthcare equipment and household appliances are among increasingly self-operated technologies.

Such advances are made possible by intricate networks of interacting computing components embedded in the control systems of automobiles, aircraft, electric power grids, medical devices and more.

Such technology-controlling networks are known as cyber-physical systems – systems in which computing devices both send information to the larger systems in which they are integrated and receive information from the immediate environment that guide computers’ reactions in response to varying external conditions.

Finding ways to ensure cyber-physical systems can be made to operate more safely, reliably and economically is among the research pursuits of Arizona State University computer scientist Georgios Fainekos, an assistant professor in the School of Computing, Informatics, and Decision Systems Engineering, one of ASU’s Ira A. Fulton Schools of Engineering.

Fainekos is the director of the Cyber-Physical Systems Laboratory at ASU and is an affiliate with the university’s Center for Embedded Systems.

Fainekos will expand his research with support from a prestigious National Science Foundation (NSF) CAREER Award he recently received. The awards are bestowed on younger faculty members considered to be emerging leaders in research and teaching in their fields. The award provides his project more than $430,000 over the next five years.

He will seek to improve the software that drives embedded computing systems, enabling the software to better reveal and eliminate errors in the design, modeling and implementation of cyber-physical systems.

He wants to create the tools for more dependable testing of such systems, as well as better methodologies to verify the systems meet quality and regulatory standards.

One big challenge, Fainekos says, will be finding ways to update testing and analysis methodologies even as more complex software continues to be developed to improve the performance of embedded systems.

Solving the challenge will become more critical to helping prevent the kinds of design and testing errors that could eventually cost industry billions of dollars due to product defects.

Even more, Fainekos says, improvements in cyber-physical systems are essential “so that we can have confidence in the new technologies we are going to depend on for many things in our lives.”

His project results will find their way into classrooms. One goal is to develop curriculum for teaching about cyber-physical systems advancements in online education programs for practicing engineers who need to update their training in the field.

In addition, his research findings are to eventually be used to develop new graduate and undergraduate courses.

Fainekos earned master’s and doctoral degrees in computer and information science from the University of Pennsylvania. He earned bachelor’s and master’s degrees in mechanical engineering from the National Technical University of Athens, Greece.

Before joining ASU, he was a postdoctoral researcher at NEC Laboratories Inc., a U.S.-based global network of research laboratories.

Media Contact:
Joe Kullman, joe.kullman@asu.edu
(480) 965-8122
Ira A. Fulton Schools of Engineering

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‘Big data’ advances could help solve health, energy challenges

Posted by on Feb 24, 2014 in Faculty, Research | 0 comments

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Professor Selçuk Candan

Two teams of Arizona State University computer science researchers are working to develop the next generations of data-driven predictive systems to improve our ability to respond to epidemics and more effectively manage buildings and their energy systems.

Both teams are led by K. Selçuk Candan, a professor in the School of Computing, Informatics, and Decision Systems Engineering, one of the ASU’s Ira A. Fulton Schools of Engineering.

Candan has been awarded two National Science Foundation (NSF) grants to support the research, as well as a grant from Johnson Controls, Inc., a global company that provides products and services to optimize building operations, including energy systems.

His team is striving to devise better ways to analyze, integrate, and index large volumes of data that will be used to produce simulations. Researchers use the simulations to derive accurate information and predictions necessary to design more effective systems.

Candan’s team for the building and energy management systems project includes Maria Luisa Sapino, an adjunct professor of computer science at ASU and a professor at the University of Torino, Italy, and Youngchoon Park, a technical fellow with Johnson Controls, Inc.

The epidemic management team includes Sapino and Gerardo Chowell-Puente, an associate professor in ASU’s School of Human Evolution and Social Change, whose expertise includes epidemiology, mathematics, computer modeling and statistics.

Removing obstacles

According to the U.S. Energy Information Administration, buildings consume more energy than any other sector, accounting for 48.7 percent of overall energy consumption. In addition, building energy consumption is projected to grow faster than consumption by industry and transportation sectors.

Candan’s team hopes to create a new building energy data management system (e-SDMS) that helps reduce energy dependency, consumption and costs. Accomplishing that goal will help remove major obstacles to environmentally sustainable development, particularly in developing countries, Candan says.

Computational models for the spatio-temporal dynamics of emerging infectious diseases, and data- and model-driven computer simulations of the spread of diseases, are increasingly critical in predicting the geo-temporal evolution of epidemics, Candan says. These models are used to effectively manage such health emergencies through a diverse set of pharmaceutical and non-pharmaceutical control measures.

The new data-driven epidemic simulation system (epiDMS) the team is developing will be part of a system to address the key data challenges underlying epidemic-spread simulations that hinder real-time analysis and decision-making during outbreaks of epidemics. Such problems slow reaction to fast-spreading epidemics such as Swine Flu and severe acute respiratory syndrome (SARS).

Complex dynamics

The two NSF grants are providing $500,000 for each of the two projects – the building/energy management system and the epidemic management system.

The Johnson Controls grant of $50,000 to ASU’s Center for Embedded Systems – an NSF Industry/University Cooperative Research Center – will also provide the Center and Candan with research data and building energy systems domain expertise, and help to deploy the project.

Candan’s work focuses on solving the “big data” computational challenges that arise from the need to model, index, search, visualize and analyze – in a scalable manner – large volumes of data sets from observations and simulations.

While very powerful simulation software exists, Candan explains, the software presents two major challenges: creating models to support such simulations and analyzing simulation results are both extremely costly. Simulations involve hundreds of parameters, affected by complex dynamic processes operating at different spatial and temporal resolutions, he says. This means simulations and observations cover days to months of data and may be considered at different granularities of space and time.

New parameters, new contexts

For input, building energy simulations, for example, use building models –describing the building structure, materials used, cooling/heating units, heat-transfer characteristics and energy costs. A single building model may involve hundreds of parameters tracked for hundreds of thousands of time steps. Multiple simulation results, with varying parameter settings, often need to be interpreted and possibly compared with real-world observations to make effective decisions, Candan says.

Candan’s team is developing systems to support data-driven simulations that can potentially guide design decisions and management strategies and enable experts to explore and analyze models and simulations from diverse parameters and at multiple scales.

He says the data-management software will enable significant savings in modeling, execution, and analysis through modular re-use of existing simulation results in new settings – such as recontextualization of models and simulation results under new parameters and new contexts. The data encoding, partitioning and analysis algorithms will be efficiently computable and leverage massive parallelism to tackle scalability challenges.

Producing more ‘big data’ experts

Candan is also helping to develop new graduate-level computer science studies with concentrations in “big data” systems. The program will help meet the growing need for data scientists and engineers who can design, build, implement and manage large data systems for industry and scientific discovery, he says.

The “big data” concentrations will enable to students to gain expertise in designing scalable (parallel, distributed, and real-time) systems for acquiring, storing, securing and accessing large-scale heterogeneous multi-source data over its life cycle, teaching them to use analytical tools to mine information from the data.

Courses will include research, case studies and presentations from industry and government experts who can provide students diverse perspectives on the course topics.

The projects Candan’s teams are working on with the support from the three new grants will also have an impact on these computer science concentrations. The challenges his teams face and the outcomes of their research will be incorporated into the curricula.

These studies will introduce computer science students to “big data” management, indexing and analysis, and parallel data processing, as well as familiarize them with challenges in the area of energy, sustainability and epidemic response management.

Written by Mayank Prasad and Joe Kullman

Media Contact:
Joe Kullman, joe.kullman@asu.edu
(480) 965-8122
Ira A. Fulton Schools of Engineering

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Sankar receives NSF CAREER award to conduct privacy research

Posted by on Feb 24, 2014 in Faculty, Fulton Schools, Research | 0 comments

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Assistant professor Lalitha Sankar

Arizona State University engineering faculty member Lalitha Sankar has received the National Science Foundation (NSF) Faculty Early Career Development Award, or CAREER Award.

Sankar is an assistant professor in the School of Electrical, Computer and Energy Engineering, one of ASU’s Ira A. Fulton Schools of Engineering.

The award provides $455,000 for Sankar’s research project, Privacy-Guaranteed Distributed Interactions in Critical Infrastructure Networks. The project will develop information-sharing protocols between distributed, and often competitive, entities in critical infrastructure networks such as the electric grid.

Such protocols can enable better monitoring of the grid while allowing control over what, and how much, information is revealed.

Information sharing is essential for situational awareness and for ensuring timely response to changing events. It can be the difference in whether your air conditioning stays on during a heat wave, for example.

Sankar calls this information-sharing problem competitive privacy.

The award, described by NSF as its most prestigious for junior faculty, supports those who are teacher-scholars conducting outstanding research and demonstrating excellent teaching. Faculty members given these awards are expected to become leaders in integrating education and research.

The NSF uses CAREER awards to foster innovative developments in science and technology, increase awareness of careers in science and engineering, give recognition to the scientific missions of the participating agencies, enhance connections between fundamental research and national goals, and highlight the importance of science and technology for the nation’s future.

“I am just delighted with the opportunity to work on these topics,” Sankar said.

Sankar also acknowledged the valuable feedback she received from her mentors and colleagues, as well as the support of “amazing” ASU and Fulton Engineering staff members.

The U.S. energy grid is a patchwork of competitive private and public entities connected from coast to coast. While those entities need to communicate to keep electricity flowing, they also are concerned about revealing proprietary information. At the same time, the grid has to become more flexible, incorporating energy from renewable sources such as wind and solar.

“Extreme weather patterns are leading to dynamic and ever-increasing demands on the grid,” Sankar said. “The grid needs to be more responsive and resilient to avoid catastrophic outages.

“My goal is to develop optimal communication protocols so that the network operators can share just enough data for reliable functioning in a distributed manner.”

Given the competitive nature of the entities involved, Sankar’s research also will develop incentive mechanisms for operators and other data-centric entities in the electric grid to share information. She said she believes that the project results have broader applicability to other cyber-physical systems, including electronic healthcare, transportation and water-distribution systems.

Graduate students will be assisting Sankar in further developing her research ideas. She is also incorporating her research into an advanced graduate class, Cyber-security and Privacy in the Smart Grid, which she recently introduced at ASU.

The CAREER award also requires education outreach efforts with focus on STEM (science, technology, engineering and math) education for K-12 students. Sankar plans to work with middle-school students, particularly girls, to explore the idea of privacy and their use of social media applications such as Facebook.

Sankar has a doctoral degree in electrical engineering from Rutgers University. Her master’s degree is from the University of Maryland and her bachelor’s degree is from the Indian Institute of Technology, Bombay. Prior to joining ASU, she was a science and technology postdoctoral fellow and research scholar at Princeton University.

Media Contact:
Judy Nichols, judith.nichols@asu.edu
(480) 965-9248
Ira A. Fulton Schools of Engineering

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