Four Engineering and Computer Science Faculty Receive NSF CAREER Awards in the 2021-2022 Academic Year

Sara Eftekharnejad, Ferdinando Fioretto, Zhao Qin and Teng Zeng

College of Engineering and Computer Science Professors Sara EftekharnejadFerdinando FiorettoZhao Qin and Teng Zeng received CAREER awards from the National Science Foundation (NSF) Faculty Early Career Development program during the 2021-22 academic year.

The highly competitive NSF Faculty Early Career Development (CAREER) program supports early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. Activities pursued by early-career faculty should build a firm foundation for a lifetime of leadership in integrating education and research.

Eftekharnejad and Fioretto are members of the Department of Electrical Engineering and Computer Science. Qin and Zeng teach in the Department of Civil and Environmental Engineering.

Eftekharnejad’s project, “Modeling and Quantification of the Interdependent Power Grid Uncertainties,” examines how conditions impact the U.S. electric power grid and looks at developing better methods of predicting grid disruptions. She is using statistical modeling of power grid failures to help predict power outages within rapid timeframes. Another focus is modeling power-generation uncertainties from various types of energy supplies, including those that are weather dependent. She and her team are working on using system measurements of grid status and condition uncertainties to find a dynamic model that adjusts in real time to help predict power outages before they occur.

In his project, “End-to-End Constrained Optimization Learning,” Fioretto is researching new models for solving computer optimization problems by accelerating data-driven learning. In that effort, he and his research team are approximating near-real-time integration of constrained optimization principles into machine learning algorithms. Optimized algorithms can improve an array of computer-based processes used in industrial applications that affect everyday life, such as meeting electricity demands efficiently, matching organ donors with receivers, scheduling flights and finding a nearby driver at a ride-sharing service.

Qin’s project, “Multiscale Mechanics of Mycelium for Lightweight, Strong and Sustainable Composites” seeks to reveal the fundamental principles that govern the multiscale mechanics of mycelium-based composites and integrate research into an educational program. Mycelium, produced during mushroom growth as the main body of fungi, plays an essential role in altering soil chemistry and mechanics, enabling a suitable living environment for different plant species.

Inland lakes in the northeastern United States have shown inconsistent trends of browning, a shift toward darker water color. Many of these lakes also receive inputs of organic contaminants originating from human activities within the lake watersheds. For “Impacts of Lake Browning on the Photochemical Fate of Organic Micropollutants,” Zeng is studying the sunlight-driven transformation of organic contaminants in the context of browning. The project is a collaboration with a volunteer lake monitoring and education program. He plans to develop new data and knowledge that will support development of adaptative lake monitoring programs and water treatment practices.

A total of nine Syracuse University faculty members received CAREER awards during the 2021-22 academic year. This is the largest number of the prestigious NSF awards earned in a single year.