Conveners
Lightning talk II: Science for data-driven discovery
- Mark Stephen Neubauer (Univ. Illinois at Urbana-Champaign)
- Aidong Zhang
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Philip Coleman Harris (Massachusetts Inst. of Technology (US))02/10/2023, 15:00
Developments in modern computation and instrumentation have led to the possibility of recording enormous amounts of data, the data revolution. Along with this incredible data flow, a new demand has emerged for algorithms that can run on all this data to “Harness the Data Revolution.” Large datasets are rapidly encompassing many scientific domains, including high-energy physics, Astronomy,...
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Daniel Angles-Alcazar (University of Connecticut)02/10/2023, 15:10
The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project aims to overcome major obstacles limiting our understanding of the fundamental properties of the Universe by (1) providing thousands of state-of-the-art hydrodynamic simulations of cosmological structure formation covering a broad range of sub-grid models for the physics of galaxy formation and (2) developing...
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Shirley Ho (Flatiron Institute)02/10/2023, 15:20
In recent years, the fields of natural language processing and computer vision have been revolutionized by the success of large models pretrained with task-agnostic objectives on massive, diverse datasets. This has, in part, been driven by the use of self-supervised pretraining methods which allow models to utilize far more training data than would be accessible with supervised training. These...
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Dr Peetak Mitra (Excarta)02/10/2023, 15:30
Conventional AI/ML metrics (such as RMSE) for optimization often do not translate well for weather/climate-specific applications including for energy grid management, or modeling key physical prognostics that are driven by an underlying dynamical process. In this short talk, we will explore the importance of using domain-aware metrics for model training, post-training evaluation and eventual...
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Yuhan "Douglas" Rao (Cooperative Institute for Satellite Earth System Studies/NOAA National Centers for Environmental Information)02/10/2023, 15:40
In this lightning talk, we will provide an overview of NOAA Center for AI's approach to foster an open community discussion that gather members from academic researchers, industry leaders, and government researchers and managers around the topics of AI development in environmental sciences. Since 2022, the annual NOAA AI workshop transitioned into an open community forum where all interested...
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Dr L. Ruby Leung (Pacific Northwest National Laboratory)02/10/2023, 15:50
This presentation briefly summarizes a workshop convened by the National Academies of Sciences, Engineering, and Medicine on February 7, 10, and 11, 2022, on the opportunities and challenges of using ML/AI to advance Earth system science, including their ethical development and use. The workshop explored how ML/AI approaches can contribute to improving understanding, analysis, modeling,...
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Lai-Yung Ruby Leung (PNNL)
Lai-Yung (Ruby) Leung (PNNL)
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