Grant: Canada Research Chairs
Dalhousie University
$200,000.00
Spatiotemporal Ocean Data Analytics
EF 2019-20
Résumé
Ocean research is undergoing a data revolution with new data streams coming online and constantly increasing in volume. Emerging research in data analytical methods needs to be tailored to the specific challenges of ocean data, including heterogeneous data types, spatial and temporal dependencies, and high-volume streaming data. The proposed research aims to develop novel spatiotemporal learning algorithms to obtain models useful in areas such as biodiversity analysis, ocean / atmospheric interactions, and ship tracking. Collaborations with domain experts and end users in industry and government will maximize the impact of the research, and create new opportunities for multidisciplinary training.
Programme
Canada Research Chairs
Bénéficiaire
Emplacement
Nova Scotia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
1000232099-2018
Name nom
Torgo, Luis
Department département
Faculty of Computer Science
Organization id
79
Institution établissement
Dalhousie University
Province en
Nova Scotia
Province fr
Nouvelle-Écosse
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2018
Award amount
200000
Program id
CRC
Program name en
Canada Research Chairs
Program name fr
Chaires de recherche du Canada
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
9998
Committee name en
Canada Research Chair Selection Committee
Committee name fr
Comité de sélection des Chaires de recherche du Canada
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Installment
NA
Partie
0
Nb partie
NA
Application title
Spatiotemporal Ocean Data Analytics
Keyword
NSERC
Application summary
Ocean research is undergoing a data revolution with new data streams coming online and constantly increasing in volume. Emerging research in data analytical methods needs to be tailored to the specific challenges of ocean data, including heterogeneous data types, spatial and temporal dependencies, and high-volume streaming data. The proposed research aims to develop novel spatiotemporal learning algorithms to obtain models useful in areas such as biodiversity analysis, ocean / atmospheric interactions, and ship tracking. Collaborations with domain experts and end users in industry and government will maximize the impact of the research, and create new opportunities for multidisciplinary training.
