I am genuinely interested in any research topic that involves data mining, machine learning, and knowledge discovery, which naturally extends to engineering intelligent software systems and algorithms design.
Data mining and machine learning
Currently, a vast amount of IoT devices, wearable and mobile devices, and various research instruments (such as next-generation sequencing) generate large amounts of temporal data which may shed 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 data summarization, abstraction, and extraction of phenomena-characteristic features. I am enjoying working on the design of algorithms and software systems for high-throughput data acquisition, assimilation, and its analysis, targeting the discovery of novel features and their associations.
Software process engineering
My PhD research was focused on finding software-process distinctive features. Working on this subject, I spent much time looking into vast amounts of software process artifacts and their measurements searching for a way to capture process-specific "behaviors" in a systematic way. Reflecting my experience and findings, I believe, that 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 (i.e., recurrent behavioral patterns), became the focus of my post-doctorate research.
Years ago, I become a research assistant at ASGPB and was accidentally involved in bioinformatics -- my special thanks to Dr. Alam -- ten years later, I still work in the field. The best part about doing bioinformatics is the collaboration with researchers from a variety of scientific disciplines -- we have biologists, physicists, chemists, mathematicians, statisticians, and computer scientists working within the same project. I find the everyday interactions within the team and with external collaborators very rewarding and enriching. Moreover, bioinformatis has it all -- data mining, machine learning, and software engineering.