My educational background:
I have a Master’s degree from the University of Tartu, where I am continuing my studies as a PhD student. My primary field of interest fluctuates among machine learning, bioinformatics, social network analysis, general data management and analysis, robotics, software engineering and teaching, with each of those topics regularly coming up in various contexts and projects.
Cool applications of big data I’ve come across:
Concepts of “big data” and “innovative” are somewhat vague for me. If we consider great data-driven applications in general, I find that various kinds of search and reasoning engines, both simple and advanced (e.g. Google Search, Wolfram Alpha, Watson) and modern statistical machine translation (i.e. Google Translate), are perhaps the most clear examples of truly big data truly changing our everyday lives. Various hardware solutions ranging from tools for the visually impaired to self-driving cars, perhaps not always “big-data”-driven, are also on my list of cool applications of data analysis techniques. Finally, most modern science is steadily moving to be one huge “big data” analysis project. Bioinformatics, particle physics, astronomy, chemistry, even social sciences are all into data mining nowadays.
My greatest achievements to date:
Once I learned to walk on my hands, which is certainly a great achievement. For all practical purposes, apart from various scientific and software development projects I participated in, I find that some of my teaching and student supervision practice has probably been among the most useful achievements so far from the perspective of the overall good.
Where my passion for big data comes from:
I like to tinker. Working with data is just one of the ways to do it.
My life away from work:
Being still a PhD student, most of my life is in one way or another related to the university, computers and data anyway, and I enjoy it a lot. Besides that, I have a wide range of hobbies away from the university and computer to choose from whenever I have the time (ballgames, watersports, running, billiards, skiing, dancing, music, etc.)