Juliane (Julie) Mai is a Research Associate Professor at the University of Waterloo focusing on the use of Machine Learning to improve hydrologic, land- surface, and ecologic models while developing data portals providing large-scale research results to fellow researchers and the wide public. Prior to this, she was a Research Lead between the Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany and the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Leipzig, Germany and a Research Assistant Professor in the Department of Civil and Environmental Engineering at the University of Waterloo in Canada.

She is an applied mathematician by training, and her scholarship is motivated by the desire of improving the performance of complex environmental models, such as hydrologic and land-surface models using methods like automatic model calibration, sensitivity and uncertainty analysis, and data assimilation. These methods are computationally expensive requiring advanced expertise in high-performance computing as well as big data science and management.

Her contributions have led to more than 50 publications, an h-index of 26, with over 2400 citations to date, and 10 invited talks. Her papers have been published in highly prestigious venues, including Nature Communications, Bulletin of the American Meteorological Society, and Water Resources Research. Several of these publications were selected as journal highlight articles, spotlights, and have been featured through the Faculty of Engineering and Water Institute at the University of Waterloo.