My current scholarly interests range from
specific aspects of data mining, namely the development of spatio-temporal and
stream mining algorithms, especially in big data systems. I am also working on the development of data management and analysis platforms for the
Internet of Things and how these analysis platforms can be strengthened via the
promising field of Big Data Analytics. The investigation of these two themes
led me to discovering the emerging area of urban informatics. Urban informatics leverages information and
communications technology to achieve a better understanding of the needs,
challenges, and opportunities of the city. This leverage can be achieved via
the use of existing city as well as citizen data to improve service delivery
and to actively participate in solving the city’s problems. In addition,
designing new forms and sources of data can be pursued for better operational
and planning decisions. This latter strategy can be carried out via the design
of platforms and applications that collect data in real time, either from sensing
systems and smart devices, or via citizen crowdsourcing. The targeted services
involve contexts ranging from traffic, city infrastructure, health care, to
supporting and planning emergency services during natural disasters. My Master research focused on the adaptation and development of data mining techniques for network intrusion detection. My PhD research focused on location and information verification mechanisms for vehicular networks and Vehicular Ad hoc NETworks (VANETs); an instantiation of the more general Mobile Ad hoc NETworks (MANETs).
I'm currently interested in the following areas of research:
I'm currently interested in the following areas of research:
- Big data, data analytics, and data mining
- Data management
- Mobile and vehicular networks
- Urban Informatics
- The Internet of Things
- m-Health Systems