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This NSF-funded symposium emphasizes building a community that has common goals and shared resources. It will attempt to demystify machine learning (ML) for those new to the field, build up machine learning expertise, encourage collaboration among those already involved, and build a ML community and organization for all participants. We encourage newcomers to ML, especially those from backgrounds which are underrepresented in hydrology!
Activities: Events will include plenary and lightning talks, poster presentations, ML tutorials and hackathons, networking opportunities (e.g. ice-breakers and group dinners) and fun events like ping-pong and soccer tournaments! It will be a fun and bonding few days! Research topics cover all areas in hydrology, e.g., hydrometeorology, watershed science, ecohydrology, soil hydrology, subsurface hydrology, water quality, human dimensions. Methods of interests include supervised & unsupervised machine learning (deep or non-deep), physics-informed machine learning (including differentiable hydrology), big data, generative and graph networks, explanatory AI, etc.
Final Products: Breakout sessions will discuss pre-selected important questions regarding future directions in ML. The outcomes from the discussions will be one or several collective papers that serve as positional statements. Further journal publication plans will be considered if there are sufficient high-quality submissions. Tutorials will provide participants with workable examples and exercises to start their ML journey. Hopefully, you can also find friends who can walk the same journey with you.