
About
Nick Duffield is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, holding the Royce E. Wisenbaker Professorship I and serving as Director of the Texas A&M Institute of Data Science. He specializes in data science and network science, focusing on applications of probability, statistics, and machine learning to large-scale datasets in networks and beyond. His research bridges foundational data science with practical applications in transportation, hydrology, and network resilience.
Education: B.A. (Cambridge, 1982), M.Math. (Cambridge, 1983), Ph.D. (University of London, 1987).
Research Interests: Graph stream sampling, network measurement, machine learning for traffic prediction, soil moisture analysis, and public safety data science. He leads initiatives like the Texas A&M Data Science Bootcamp and collaborates on projects such as AI in construction and precision agriculture.
Recent Articles Highlight: Focus on machine learning-driven solutions in agriculture (e.g., UAV-based cotton yield prediction), transportation (e.g., electric truck feasibility studies), and disaster response (e.g., social media analysis for damage estimation).
Awards: ACM, IET, IEEE, and AT&T Fellowships; co-recipient of ACM Sigmetrics Test of Time Award (2012/2013).
Grants/Advising: Over $20M in funding from NSF, NIH, and industry. Advises on 10+ student projects, including work on graph neural networks and hydrology.
Labs/Teams: Texas A&M Institute of Data Science (TAMIDS), collaborations with Texas Transportation Institute, and hydrology teams analyzing soil moisture via machine learning.
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