Nathan Martindale
Nathan Martindale is a data scientist in the Nuclear Nonproliferation Division at Oak Ridge National Laboratory. Nathan completed both his B.S. (2018) and M.S. (2020) degree in computer science at Tennessee Tech University, with his graduate studies focusing on machine learning. His recent research interests have included visual analytics, system dynamics, and knowledge management, and he has released several open source libraries supporting research experiment management, system dynamics model creation and analysis, and interactive machine learning.
Session
Modeling and simulation enable iterative hypothesis testing and encoding subject matter expertise into reusable tools. While the Python community has a variety of libraries for modeling, few exist for system dynamics, a paradigm for top-down analysis of material and information flows over time. Reno is an open-source package combining creation, visualization, and analysis of system dynamics models with techniques for Bayesian inference through integration with PyMC, supporting probability distributions in system variables and MCMC sampling to produce posterior distributions based on observed values. This approach enables simulation and refinement of time series models where variables, policies, or knowledge are uncertain, and data/observations are sparse.