Data Science Economy: Data Driven
3 keynotes / 16 talks / 32 speakers
Meet the Speaker!

17. – 18.05. 2018, @HUB385, Zagreb, Croatia
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CEO and CoFounder of ORACLUM Intelligence Systems

Vuk Vuković

His primary interests are data warehouses and business intelligence in distributed systems, on which his MSc thesis was focused and which are continued on his PhD studies, having bigger focus on integrating Big Data with structured data.

Vuk is the CEO and co-founder of Oraclum Intelligence Systems Ltd, a Cambridge-based company that uses the power of social networks, machine learning, and big data to predict election outcomes and uncover patterns of consumer behavior.

In addition to his role at Oraclum he is completing a DPhil in Politics at the University of Oxford, Pembroke College.  He holds a Master of Science degree from the London School of Economics, in the field of political economy and received a BA in economics from the University of Zagreb, from which he graduated magna cum laude. During his studies he attended summer schools at the University of California at Berkeley and at Harvard University. He was a visiting scholar at the University of Cambridge, Clare College during the summer of 2013.


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Keynote Session



Keynote

The polls were wrong! Our predictions were wrong! How can we fix that?

“Predictions are hard, especially about the future“, so said the famous NY Yankees player Yogi Berra. Why are we so bad at making predictions? We rely on, make, and listen to forecasts every day. Making predictions is a natural response in overcoming the knowledge deficit in a world filled with uncertainty. Survival has encouraged us to fight uncertainty and lack of knowledge with our limited approximations of reality. In other words what we think we know which is very often clouded by our own personal biases, sets of beliefs, and misconceptions.
So if we know that people are prone to biases and overconfidence, can we still trust them to make good predictions?
We at Oraclum say – yes we can! In fact we can use the people’s own groupthink biases to improve their predictions. How? Find out at the DSE2018!

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