In my Ph.D. studies, I am concentrated on privacy issues related to the indicators in smartphone ecosystems. With the rapid accumulation and processing of personal data by numerous organizations, it is of paramount importance to protect people from adverse uses of their data, while allowing them to enjoy the benefits the use of these data can possibly provide. For this reason, it is an essential need to provide mechanisms to support smartphone users to make informed-decisions. I intend to provide approaches to measure the privacy protection level of the existing applications in smartphone ecosystems (by getting help from machine learning techniques) to help users to understand and perceive to which level each application can threaten their privacy. Furthermore, I aim to efficiently alarm users about how much and to which extent their personal data are being accessed, collected, and used by different applications.
In my M.Sc. studies, I focused on wireless communications, more specifically, wireless sensor networks. My goal was to measure the potential congestion at each node to effectively mitigate it by proposing innovative approaches with regards to the buffer occupancy and total packet input/output rate. In addition, I also studied about clustering protocols to propose efficient energy-aware solutions by using evolutionary algorithms to provide fruitful methods in terms of energy consumption, packet delivery/loss ratio.
I have also this experience to work on other cutting-edge technologies like quantum computing, 5G networks, and mmWave communications.