Chris is a professor in Data Science and Analytics; his doctorate involved Artificial Intelligence and Complex Adaptive Systems.
At the Telekom Data Intelligence Hub he is a development executive responsible for partner on-boarding, data innovation, and mobility & automotive.
Prior to joining Deutsche Telekom, he founded a business analytics startup, co-founded the Peter Drucker Customer Lab at Claremont Graduate University, and the Special Interest Group on Agent-based Systems of the Association for Information Systems (AIS) / “Wirtschaftsinformatik.” He began his career as a consultant with Accenture and later joined the faculty of the University of Southern California (USC) in Los Angeles. His research has been funded by Microsoft and Intel, among others; results have been published in leading publications, such as in journals of the Institute of Electrical and Electronics Engineers (IEEE), Information Systems Research and Communications of the ACM. Over the last two decades, Chris has become known for his success with data science and analytics for Fortune Global 100 clients in the US, Europe and China.
Mistakes slow down production and cost money. To avoid this and to make the production process as efficient as possible, errors must be identified and eliminated at an early stage. Wouldn’t it be ideal to have a digital image that identifies defects prior to production?
Intelligent mobility is being used more and more. But to create this intelligence, a large amount of data is needed. In order to remain competitive as an OEM, data must be collected, analyzed and used efficiently. But how do you actually obtain the data?
New mobility frees up space, how to use it? Behavioral data can provide answers.
In data analytics today, more than 80% of the time budget is spent on data processing alone. With the “data sandbox” you can generate results faster.
Intelligently networked machines improve the process chain and products in manufacturing companies. The DIH makes Industry 4.0 possible.
The Data Intelligence Hub solves mobility problems through data diversity. With Analytics, individually required information are filtered and processed.
Digitizing the production line of a Hidden Champion in 100 days?
The launch of the Data Intelligence Hub will be complemented with a “DIH University Initiative.”