Mark Bartlett, Ph.D., P.E., Data Science and Machine Learning Practice Lead, brings years of experience in data science and machine learning to The Water Institute and the Analytics, Computing, Technology (ACT) Team. Mark’s work spans from developing a rapid flood forecasting tool that can be replicated across landscape types and locations to creating data models for agricultural purposes.

Mark’s expertise ranges from hydrology and hydraulics to stormwater management, ecohydrology, and water quality by bringing new techniques to engineering practices. His experience includes work with the National Oceanic and Atmospheric Administration (NOAA) on the Geophysical Fluid Dynamics Laboratory (GFDL) climate model and work with the United States Department of Agriculture (USDA) as a fellow in the National Institute of Food and Agriculture.

Prior to joining The Water Institute, Mark was the lead data scientist and machine learning engineer at Stantec, after working for several years as a fellow at the National Institute of Food and Agriculture where his research included creating a model that consistently represented all three types of photosynthesis.

Mark received his bachelor’s degree in civil engineering from Brown University, his master’s in environmental engineering from the University of Southern California, and his Ph.D. in civil and environmental engineering from Duke University.