3rd SMD and ETD Workshop on A.I. and Data Science: Leaping Toward Our Future Goals

Nicholas LaHaye earned his PhD. in Computational and Data Sciences from Chapman University while working as a Data Scientist with the Processing Algorithms and Calibration Engineering group at JPL, where he has been since 2013. His research focuses include applying unsupervised deep learning to large multi-sensor datasets, to segment and track objects in low and no-label environments (smoke plumes, algal blooms, burn scars, etc.). 

He is also currently working on fast retrievals of water quality parameters and uncertainties using DL and ML-based MCMC acceleration for the operationalization of physical models. He is generally passionate about applying machine-learning-based solutions to help better understand and mitigate the climate crisis, natural hazards, and biodiversity loss.