Caleb Phillips is a data scientist with the Computational Science Center at NREL. Phillips comes from a background in computer science systems, applied statistics, predictive modeling, machine learning, and optimization. His work supports projects across disciplines at NREL, including advanced and alternative-fuel vehicle technologies, transportation systems, materials science, photovoltaics, strategic energy analysis, wind power, and energy efficient high-performance computing. Phillips maintains an adjunct appointment at the University of Colorado, Boulder, where he has also done work in sustainability science (food systems), medical research (orthopedics and wilderness medicine), human computer interaction (power control), and artificial intelligence (assistance systems).

Education

Ph.D., Computer Science, University of Colorado

M.S., Computer Science, University of Colorado

B.S., Computer Science, Portland State University

A.S., Computer Science, Portland Community College

Featured Work

Evaluation of Obstacle Modelling Approaches for Resource Assessment and Small Wind Turbine Siting: Case Study in the Northern Netherlands, Wind Energy Science (2022)

Research Data Infrastructure for High-Throughput Experimental Materials Science, Patterns (2021)

An Open Combinatorial Diffraction Dataset Including Consensus Human and Machine Learning Labels with Quantified Uncertainty for Training New Machine Learning Models, Integrating Materials and Manufacturing Innovation (2021)

A Modeling Framework for Designing and Evaluating Curbside Traffic Management Policies at Dallas-Fort Worth International Airport, Transportation Research Part A: Policy and Practice (2021)

A Data-Driven Operational Model for Traffic at the Dallas Fort Worth International Airport, Journal of Air Transport Management (2021)