Dr lina Stankovic (Nee Fagoonee)
My research interests are in the general area of coding, machine learning and their applications:
· wireless communications,
· underwater communications,
· network coding,
· sparse coding
· cooperative communications
· distributed source coding,
· optical/magnetic recording.
I also work on multifunctional systems incorporating coding with other signal processing tasks such as equalization, synchronization, MIMO communications.
More applied interests are:
· Distributed signal processing and coding in wireless sensor networks,
· Asset monitoring and intelligent data gathering via wireless sensor networks
· Joint source-channel coding for multimedia distribution
· Smart appliances and smart home
· Data mining
· Spectrum sensing, sampling and coding for communications
· Compressive sampling
I strongly believe that bridging the gap and multi-disciplinary approaches to research is the way forward. This is because similar signal processing and mathematical tools are being used across disciplines for solving different problems that can be broken down into simpler, similar problems. Additionally, instead of simply putting two tools together (in series or parallel) and viewing each one as a black box, it is preferable to integrate them to deliver enhanced performance. This requires revisiting fundamentals, understanding and exploiting the commonalities among various algorithms and thus require engagement from researchers from various disciplines.
Researchers who have been trained in problem-solving tools (e.g. coding, graphical inference, information theory etc.) have much to offer to those solving higher-level problems, and can learn much from different applications to find synergies among these problems, provided that everyone concerned keeps an open mind.