Visual Analytics Lab

The Visual analytics lab was established in 2015. Its main purpose is to conduct basic and applied research in the field of big data analysis. The activities of the lab are focused on the robust conversion of heterogeneous and huge amount of data in tangible and understandable visual representations that facilitate their interpretation and analysis. In this context, pioneer research is conducted the research staff for delivering interactive exploration techniques through emerging data analytics methods. Research activities of the lab are related to:

  • Deployment of machine learning and artificial intelligence methods for the processing and mining of important information-related features as well as to identify patterns through deep neural networks, multimodal optimization, clustering, etc.
  • Self-training algorithms fully exploiting historical data with robust capabilities for detecting patterns in real-time, including technologies for predictive analytics.
  • Techniques for delivering distributed computational intelligence fully coupled with decentralized ledger architectures (block-chain) for delivering privacy-preserving and personalized data analysis among trusted ecosystems.
  • Intuitive human machine interaction interfaces that fully employ interactive visualizations and enable cooperative schemes in real-time for improving decision making process.
  • Novel decision support systems that encapsulate hypothesis testing methods as well as research on innovative decision support models that are based upon simulation of real business processes and market conditions.
  • Development of hypothesis testing framework in various domains such as health, energy, cybersecurity, IoT, etc.

In the laboratory, there is also active a working group in Remote Sensing, with a focus on the research and development of applications and computational processes for earth surfaces observation, registration of changes in their coverage and quantitative characteristics, and prediction of imminent changes; thus, contributing to the sustainable management of natural resources. The aim of the group is to provide reliable Earth Observation services and products of high benefit, capable of feeding in decision-making chains and models describing processes in the geosphere.

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