CREXDATA aims to develop a versatile platform for real-time critical situation management, adaptive action planning, and agile decision-making powered by extreme-scale and complex data.
OBJECTIVES
Develop an extreme-scale data ingestion and fusion toolbox and realistic simulation models and tools
Create real-time predictive knowledge
and forecasts including federated
learning, complex event forecasting
under uncertainty and techniques for
Prediction-as-a-Service
Reduce perceived
complexity via
graphical workflow
design and visual
anlaytics coupled
with eXplainable AI approaches and
augmented reality
under uncertainty
USE CASES
Weather
emergencies
use case
Ingest and fuse extreme data to
improve situation awareness that
informs decisions in weather emergency
scenarios
Health crisis
use case
Integration of epidemiological and
multi-scale simulation models with machine learning to support
decision-making in health crises
Maritime
use case
Real-time route forecasting to
ensure safeter navigational routes
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Presentation at the “10th International Conference on Data Science and Advanced Analytics (DSAA)”
The IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA) is the premier data science forum jointly supported by IEEE, ACM, ASA and CCF. DSAA is recognized by CORE and CCF conference rankings, top-20 in data mining and analysis in Google...
30th International Symposium on Temporal Representation and Reasoning
Since 1994, the TIME International Symposium brings together researchers from different disciplines of Computer Science working on temporal aspects of computational systems. The 30th TIME edition 2023 will take place at the National Centre for Scientific Research...