Why I got involved in TEXATA:
I thought that I have nothing lose, but much to gain by participating. I feel like competitions like TEXATA offer a unique experience that helps me grow in a way that is not given by university education.
My educational background:
Generalist approach: from pure mathematics training (topology, algebraic geometry) to applied math (statistics, graph theory, optimization) to core CS including some applied areas (IT-Security, Algorithms). Actively self-teaching more knowledge in areas such as Machine Learning, Data Mining, and Deep Learning.
The most innovative application of big data I’ve seen:
In a narrow sense: Crop yield estimation by satellite remote sensing is an interesting application. In a wider sense: systems that gather, yield, and process huge amounts of personal data – think NSA/Google – that ultimately open up possible new ways to control and govern populations.
The best advice I’ve received at work:
Let people do their mistakes and THEN help them NOT the other way around.
Why I’m passionate about big data:
I got interested early into cognitive systems and neuronal networks. Now the computation power is there to use them. Also, I like how mathematical methods together with technical expertise can shape the world.