Dr. Wally Fulweiler Receives the Simons Foundation Pivot Fellowship
Dr. Robinson Fulweiler recently received the 2024 Simons Foundation Pivot Fellowship. The program supports researchers who have a strong track record of success and achievement in their current field, as well as a deep interest, curiosity, and drive to make contributions to a new discipline, in fields of natural sciences, mathematics, engineering, data science and computer science at academic institutions or equivalent positions elsewhere.
Dr. Fulweiler is a professor in the Department of Earth and Environment and the Department of Biology. She leads the Coastal Ecology and Biogeochemistry Laboratory, which focuses on answering fundamental questions about energy flow and biogeochemical cycling of nitrogen, phosphorus, silicon, carbon and oxygen in the environment. She is especially interested in how anthropogenic activities affect the ecology and elemental cycling of ecosystems on a variety of scales, from local nutrient loading to global climate change. Her latest research is centered on the transformations of elements across the land-ocean continuum, the ultimate fate of nitrogen in the marine environment, the impact of climate change on benthic-pelagic coupling and the role of coastal systems in greenhouse gas budgets. More recently, her group has been developing new instrumentation to enhance measurements of key biogeochemical processes. This instrumentation will aid in constraining coastal nutrient and carbon budgets and will help increase access to low-cost technology for democratizing science.
Dr. Fulweiler will use the Simons Foundation Pivot Fellowship to lay the foundations of a research program in data science. She will be mentored by Mark Crovella, a professor in the Department of Computer Science at Boston University and an expert in data science and machine learning, with a focus on computational biology, social impacts of computing and computer networking. Together, they will use cutting-edge data science methods to answer the following questions: How do we distinguish quantitatively between different types of coastal systems? How can we place the discussion of coastal system types into a taxonomy with objectively testable criteria? These questions are important because coastal ecosystems have a disproportionate impact on the functioning of our planet and are also on the front line of human impacts. By using the available data and harnessing the power of machine learning models, they will define emergent ecosystem properties for the creation of a data-driven taxonomy for coastal environments.