Graph analytics applies multimodal graph analysis to transactions and interactions in both virtual and geospatial realms. We offer leading expertise in spatiotemporal analytics and crypto asset forensics.
Our scientific focus lies on developing multimodal graph analytics methods that help understand transactions and interactions in both virtual and geospatial realms (covering, e.g., transaction networks in eCommerce as well as interactions in spatial networks). We offer leading expertise in spatiotemporal analytics, such as analysis of trajectories from a variety of tracking systems, including GPS, cellular, and video-based (providing, e.g., anomaly detection solutions for maritime safety), as well as in crypto asset forensics through our on-going cooperation with the Complexity Science Hub in the areas of cryptofinance and crypto asset forensics (providing, e.g., development of the open-source GraphSense framework for crypto asset analytics).
Goals
- Develop advanced spatiotemporal analytics tools
- Expand our frameworks to additional large-scale graph- and network-based domains
Application Domains
- Law enforcement: cryptofinance and crypto asset forensics
- Mobility and transport data analytics
