Innovative UA Research Recognized with NSF CAREER Awards

Innovative UA Research Recognized with NSF CAREER Awards

Four professors at The University of Alabama received one of the National Science Foundation’s most prestigious honors for early-career faculty.

The NSF CAREER Award recognizes scientists and engineers who show leadership at the intersection of education and research. The awards provide funding to support projects that advance science alongside national priorities and serve the community through education and outreach.

Across campus, 37 active faculty have received CAREER awards during their tenure. These high-performing faculty are joined this year by Dr. Nilesh Kumar, assistant professor of metallurgical and materials engineering; Dr. Mizan Rahman, assistant professor of civil, construction and environmental engineering; Dr. Tibor Szilvasi, assistant professor of chemical and biological engineering and Dr. Shunqiao Sun, assistant professor of electrical and computer engineering.

Understanding How Materials Fail

Stress corrosion cracking describes one of the ways materials break down with time and use. The simultaneous presence of stress and a caustic environment can initiate and accelerate the process, and when that happens the effects can be catastrophic. Despite all of our technological advances, sometimes bridges collapse, aircraft engines fail and pipelines burst.

Dr. Nilesh Kumar received a CAREER Award to support his work to understand SCC at the atomic level and build a comprehensive method for understanding how these materials perform over time. His method will capture and document what happens to materials over time, under stress or corrosive conditions, at the atomic level.

The traditional process would stress the material in a caustic environment until it breaks, and then understand what happened. Kumar proposes to examine how the microstructure changes during its entire life cycle so that the conditions that cause cracking can be understood before the failure occurs. In the long term, his work will lay a foundation for an analytical method that will save thousands of hours in the lab and offer a tool to better predict and avert these disasters.

Cyber Resilience in Autonomous Vehicles

Fully autonomous driving systems for ground vehicles hold the promise of saving 36,000 lives annually, preventing 2 million injuries and saving $190 billion in accident-related health care costs every year. However, many challenges remain in making autonomous vehicles resistant to outside threats and corresponding uncertainties.

Dr. Mizan Rahman’s CAREER Award-supported work will address both unintentional interference and deliberate cyber threats to the autonomous vehicle navigation system. Autonomous vehicles rely on Global Navigation Satellite Systems integrated with various techniques, such as inertial navigation systems, for cyber-resilient global positioning and navigation tasks, but integrated GNSS is susceptible to unintentional interference (e.g., atmospheric effects) and deliberate cyber threats (e.g., jamming and spoofing).

Rahman proposes integrating in-vehicle sensors with GNSS to provide more robust systems that can adjust to various deliberate cyber threats and unintentional interference. His group will evaluate the vulnerabilities of navigation systems and develop threat detection and navigation methods in a GNSS-contested environment by modeling cyber-attacks on autonomous vehicles. This work will address a critical need to prevent and fight cyber threats to autonomous vehicles’ GNSS-based navigation systems. 

Networking Automotive Radar

Automotive radar for use in autonomous driving has key advantages, namely that it has a superior range to other perception sensors in use and performs better in poor weather conditions. However, it is vulnerable to interference from other radar sources and cannot sense at a fine enough scale to ensure real-time detection and classification of road obstructions, especially pedestrians and cyclists.

An NSF CAREER Award will enable Dr. Shunqiao Sun to begin developing a high-resolution, adaptive radar imaging system. “Currently, automotive radars perceive each other as sources of interference, lacking any collaborative mechanisms,” Sun said. “We propose an automotive radar network for collaborative sensing that exploits constructive interference to collectively improve the overall radar sensing coverage and resolution.”

Through strong collaboration with the automotive sector, Sun intends to attract underrepresented researchers and translate his work more quickly to real-world use in the industry.

Designing Better Catalysts

Catalysts are involved in making more than 90% of all materials in everyday life, and many of these reactions consume a great deal of energy. With funding from the CAREER Award, Dr. Tibor Szilvási will apply advanced computational tools to the development of new and more efficient catalysts.

Catalyst design in the lab is a slow process, but Szilvási has developed unique computational methods that harness machine learning to investigate catalysis at the atomic level. “When we understand these reactions at the atomic scale, we can design better ones that will require less energy consumption,” he said. His methods will be applicable across the chemical industry as researchers will be able to quickly screen for desired properties and behavior.

The project includes the development of new courses to provide advanced programming expertise to chemical engineering students.