Guest, Work Win NSF CAREER Awards
Jeremy Guest and Dan Work, both CEE assistant professors, have won National Science Foundation (NSF) CAREER awards. Administered under the Faculty Early Career Development Program, CAREER awards are the NSF’s most prestigious form of support and recognition for junior faculty who “exemplify the role of teacher-scholars through outstanding research, excellent education and the integration of education and research within the context of the mission of their organizations.”
Guest received a five-year, $400,000 grant through NSF’s Energy for Sustainability program for his proposal, "CAREER: Advancement of Microalgal Biotechnology via Quantitative Sustainable Design: An Integrated Research and Education Plan.”
“The overarching goal of this work is eliminate energy consumption, and nitrogen and phosphorus losses at wastewater treatment plants,” Guest said. “This will be achieved through the development of microalgae-based treatment processes that could enable energy positive nutrient recovery from wastewater. Research will integrate experimentation, modeling and sustainable design to identify a path forward for technology development, and results from research will be used in educational tools that more effectively teach environmental engineering and sustainable design.”
Work received a five-year, $400,000 grant through NSF’s Civil Infrastructure Systems program for his proposal, “CAREER: Modeling and Estimation Methods for Complex Traffic.”
“The objective of this project is to investigate the dynamics of complex traffic,” Work said. “Complex traffic is characterized by heterogeneous vehicle types, for example bikes and cars, that vary in size and performance characteristics but share the same roads. These features are increasingly common in the U.S. during extreme congestion generated by special events.”
Work’s research postulates that advances in mathematical models, informed by and validated with large volumes of traffic data, are key elements to unlock the full understanding of complex traffic. This research focuses on the development of mathematical models of heterogeneous traffic, modeling and analysis of human-directed traffic and the development of fast and accurate estimation algorithms to integrate data into city-scale models. Data to validate the models and estimation algorithms are obtained through a new traffic sensing technology developed by Work called TrafficTurk.