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projects [2019/08/30 15:12]
Jaroslaw Zola
projects [2019/09/06 11:44] (current)
Jaroslaw Zola
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 [[https://​www.nsf.gov/​awardsearch/​showAward?​AWD_ID=1910539|OAC Core: Small: Scalable Non-linear Dimensionality Reduction Methods to Accelerate Scientific Discovery]] [[https://​www.nsf.gov/​awardsearch/​showAward?​AWD_ID=1910539|OAC Core: Small: Scalable Non-linear Dimensionality Reduction Methods to Accelerate Scientific Discovery]]
  
-[[https://​github.com/​ubdsgroup/​meads|MEADS]] - Manifolds for Extreme-scale Applied Data Science - is the joint project with the [[https://​cse.buffalo.edu/​ubds/​|University at Buffalo Data Science (UBDS)]] group of [[https://​cse.buffalo.edu/​~chandola/​|Dr. Varun Chandola]] and research group of [[http://​www.owodo.org/​|Dr. Olga Wodo]].+[[https://​github.com/​ubdsgroup/​meads|MEADS]] - Manifolds for Extreme-scale Applied Data Science - is the joint project with the [[https://​cse.buffalo.edu/​ubds/​|University at Buffalo Data Science (UBDS)]] group of [[https://​cse.buffalo.edu/​~chandola/​|Dr. Varun Chandola]] ​(lead PI), and research group of [[http://​www.owodo.org/​|Dr. Olga Wodo]].
  
 This multidisciplinary research project aims at developing scalable end-to-end non-linear dimensionality reduction solutions to accurately learn the dynamic behavior of complex systems (e.g., described by PDEs). The project is centered around the following topics: This multidisciplinary research project aims at developing scalable end-to-end non-linear dimensionality reduction solutions to accurately learn the dynamic behavior of complex systems (e.g., described by PDEs). The project is centered around the following topics:
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