Name
Title | ||
|---|---|---|
Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research |
Abstract | ||
|---|---|---|
ABSTRACTHuman-natural systems involve complex interdependent processes, but domain specific processes are traditionally studied in non-overlapping research silos. The Predictive Risk Investigation SysteM (PRISM) for multi-layer dynamic interconnection analysis is a group of collaborators across multiple domains who work to discover data driven connections specifically among domain risks. We bring our inter-disciplinary approach to risk assessment to our KDD'21 workshop. Our workshop is a step toward a holistic approach to systemic risk analysis by welcoming speakers in applied and technical research at the forefront of risk and complex systems. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3447548.3469480 | Knowledge Discovery and Data Mining |
Keywords | DocType | Citations |
associated anomalies, complex systems, data-intensive risk assessment, human-natural systems, systemic risk, volatility | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Toryn L. J. Schafer | 1 | 0 | 0.34 |
| Ryan M. McGranaghan | 2 | 0 | 0.34 |
| Mila Getmansky Sherman | 3 | 0 | 0.34 |
| Mei-Ling E. Feng | 4 | 0 | 0.34 |
| Olukunle O. Owolabi | 5 | 0 | 0.34 |
| Sean E. Ryan | 6 | 0 | 0.34 |
| Marie-Christine Düker | 7 | 0 | 0.34 |
| Michael Jauch | 8 | 0 | 0.34 |
| David S. Matteson | 9 | 13 | 5.08 |