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Alexander Kagoshima
Data Scientist, Pivotal

Website

Alexander Kagoshima received a M.S. in Economics and Engineering from TU Berlin in 2012. In graduate school his focus was on machine learning and statistics. In his bachelor thesis he worked on applying Gaussian Processes to currency exchange rates. For his master thesis, Alex developed and evaluated a change-point detection algorithm that operates on wind data, to enable a new kind of intelligent wind-turbine control systems.

He gained practical experience in the application of machine learning methods as a working student at Volkswagen, his task was to analyze data of a test fleet of fuel-cell cars. Since December 2012 he works as a Data Scientist at Greenplum (now Pivotal) as the first Data Scientist in the EMEA team. In his spare time, he tries to find new ways to analyze soccer games through statistics.

Sessions

Machine Data
Mission City M
Ian Huston (Pivotal), Alexander Kagoshima (Pivotal), Noelle Sio (Pivotal)
Average rating: ****.
(4.00, 1 rating)
With increased road congestion around the globe and growing amounts of car data we need more intelligent analytical methods to beat the traffic. This talk presents our work on traffic velocity and travel disruption analytics. We describe our approach in detail, how we went from idea to implemented algorithm and how our methods can be applied to gain deep insight into influential factors. Read more.