Munich DataGeeks - July 2015 Edition

Format:

• 2 presentations (each ca. 30-40 min incl. discussion)
• Of course time for networking + food + drinks before, in between and especially after the presentations
• Talks are held in English

The Line-Up (detailed description of the talks below):

Torsten Schön - Teaching a slime mold to train a Bayesian Network

Christian Essling - When less can be more: Setting technology levels in the computer games industry

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Speaker: Torsten Schön (yes it's me)

Title: Teaching a slime mold to train a Bayesian Network

Abstract: If you try to teach a computer system intelligent behaviour, there is often some blueprint to be found in nature. As the slime mold physarum polycepahlum, which is able to solve the NP hard shortest path problem very efficiently. Some people train dogs, some horses. I failed in training my cats, so I tried to start with a simpler creature, the slime molds.

Bio: I studied Bioinformatics at the University of Applied Science in Freising and spend one semester in Sydney at the University of New South Wales. During my Diploma thesis, I started working with machine learning algorithms. After a small period of plain software development, I did my PhD at the Computational Intelligence & Machine Learning Group of Prof. Lang at the University of Regensburg. After some time at data analysis companies in Munich, I switched to Audi, where I work with data received from cars.

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Speaker: Christian Essling

Title: When less can be more: Setting technology levels in the computer games industry

Abstract: This presentation is essentially about the economics of computer games. Particularly, their technological sophistication. Games with realistic physial effects and fancy graphics might be more attractive (which means more gamers would like to buy it) but come with higher system requirements (which means that fewer gamers can play it). This research shows how the trade-off should (economically) be solved and what role time and technological progress play.

Bio: I studied Economics at the University of Munich and always had a faible for two things: data and strategy. After a short period of (proper) work, I decided to pursue a PhD at the ifo Institute for Economic Research in Munich. Here, I could combine both of my interests by empirically researching strategic issues, e.g. in the computer games or airline industry. Since mid-2014 I work as a senior data scientist at Alexander Thamm GmbH.