Monte Lunacek is a part of the Data Analysis and Visualization Group within the Computational Science Center where he uses high-performance computing and data science to improve future mobility. This includes a variety of work like the Athena project that guides mobility transformations at the Dallas-Fort Worth Airport and the Connected Autonomous Vehicles project that uses high-performance computing to make learning to drive autonomous and connected vehicles more efficient. Monte enjoys sharing his knowledge with the community through various tutorials on data analysis, visualization, and machine learning.
Data optimization and analysis
Ph.D., Computer Science, Colorado State University
M.S., Computer Science, Colorado State University
B.S., Applied Mathematics, University of Colorado Colorado Springs
Online certificates in:
- Convolutional Neural Networks
- Neural Networks and Deep Learning
- Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
- Sequences, Time Series, and Prediction
- Structure Machine Learning Projects
- Introduction to Big Data Apache Spark
Understanding biases in pre-construction estimates, The Science of Making Wind from TORQUE (2018)
Transactive home energy management systems, IEEE Electrification Magazine (2016)
Application of an evolutionary algorithm for parameter optimization in a gully erosion model, Journal of Environmental Modelling and Software (2016)
View all NREL publications for Monte Lunacek.