Juliette Ugirumurera is a computational scientist at NREL. Her area of expertise is simulation and optimization of complex systems, including transportation and power systems. She also has background in fair AI, explainable AI, high performance computing and their application in complex systems. Previously, at Lawrence Berkeley National Laboratory, she developed high-performance computing algorithms and simulations for large-scale traffic assignment problems.  She has also done work in developing models and algorithms for green microgrids and electric vehicle grid planning.

Research Interests

Modeling and Simulation

Optimization

Fair AI

Explainable AI

High Performance Computing

Education

Ph.D., Computer Science, University of Texas Dallas

M.S., Computer Science, University of Texas Dallas

B.S., Computer Engineering, Oklahoma Christian University

Professional Experience

Postdoctoral Fellow, Berkeley Lab (2017–2018)

Research Assistant, University of Texas Dallas - Wireless Networks Lab (2013–2017)

Co-founder and Secretary, rwandans4water (2010–2012)

Computer Engineer, GE Transportation (2011)

Featured Work

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)

Deploying a Model Predictive Traffic Signal Control Algorithm-A Field Deployment Experiment Case Study, IEEE ITSC Conference (2022)

Optimal Capacity Sizing for Completely Green Charging Systems for Electric Vehicles, IEEE Transactions on Transportation Electrification (2017)

A Unified Software Framework for Solving Traffic Assignment Problems, IEEE ITSC Conference (2018)

Awards and Honors

NREL President's Team Award (2022)

Outstanding Academic Performance (2017)