ABOUT STAHY 2023
The International Commission on Statistical Hydrology (ICSH) of the International Association of Hydrological Sciences (IAHS) is organizing the 13th International Workshop on Statistical Hydrology (STAHY2023), which will be hosted by Northeastern University in Boston, Massachusetts (USA), from 8-10 November 2023. The event is sponsored by The Institute for Experiential AI at Northeastern University.
The STAHY 2023 workshop brings together the international statistical hydrology community for vibrant scientific discussions and debates on advanced statistical methods for hydrological applications. This year’s theme aims to provide a bridge between the environmental statistics and artificial intelligence communities with methodological discussions, exchange of knowledge, and identification of opportunities for mutual support to solve climate, water, and sustainability issues.
Full details of the workshop, including the registration link via Copernicus, are available at https://iahs.info/Commissions–W-Groups/ICSH-Statistical-Hydrology/News-and-Events/stahy-workshop-2023/
Registration is now open.
The full program can be found here.
EARLY CAREER WORKSHOP DETAILS:
We are pleased to announce that the Early Career representation for the International Commission on Statistical Hydrology (ICSH) have organized two excellent instructors for the Early Career Workshop, which will be offered on Wednesday, 8 November. Our instructors will be:
Professor Auroop Ganguly, Northeastern University, who will describe the challenges associated with hydrologic data, their implications for domain-aware high-performance computing, and how next-generation artificial intelligence may be able to provide solutions and where further developments may be necessary.
Professor Richard Vogel, Tufts University, who will discuss the theoretical implications of developing datasets with high spatial and temporal resolution and offer practical solutions for dealing with these statistical issues.
Dr. Grey Nearing, Google, who will share perspectives on the future of hydrology, artificial intelligence, and machine learning and discuss potential career paths at the intersection of hydrology and artificial intelligence.
Professor Ana Barros, University of Illinois at Urbana-Champaign
Dr. Corrine Bowers, Stanford University and U.S. Geological Survey
Professor Jennifer Dy, Northeastern University
Dr. Grey Nearing, Google
Dr. Karen Ryberg, U.S. Geological Survey