I am genuinely interested in any research topic that involves data mining, machine learning, and knowledge discovery. This interest naturally extends to the intelligent software systems engineering.

Data mining and machine learning

Currently, a vast amount of IoT devices, wearable and mobile devices, and various research instruments generate large amounts of temporal data which may shed a light on many real-life phenomena through previously unknown associations. Discovering these associations requires the development of self-learning intelligent systems that are capable of big data summarization and extraction of phenomena-characteristic features. I enjoy working on the design and implementation of intelligent systems that enable the discovery of novel features and their associations.

Software process engineering

In my opinion, the successful software development - the one which delivers a functional software in time and under budget - is the result of a development discipline that is a combination of appropriate tools, processes, attitude, and habits. An effective combination of these enables teams and individuals not only to reach their goals efficiently, but to deliver reliable and performant software systems and components. The understanding of these "magic mixtures", and specifically habits (which are recurrent behavioral patterns), is my very next research interest.


Accidentally, years ago, I become involved in bioinformatics after I've got a research assistant job at ASGPB -- my special thanks to Dr. Alam! Ten years later, I still work in the field. The best part about bioinformatics is an extremely rewarding and enriching collaboration with researchers from a variety of scientific disciplines -- we have biologists, physicists, mathematicians, statisticians, and computer scientists working within the same project. Moreover, it involves data mining, machine learning, and software engineering. And soon, as the sequencing gets cheaper and the interest for studying of genetic data dynamics forms, it shall incorporate the temporal data mining.

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