Martin Biermann

Contextual adaptation is key to the integrative success of Mobile into the human life. Today there is no development pattern available to succeed static personalization of digital content to deeper reasoning about user context and situative environment. It is this foundation this project aims at for an intelligent digital evolution of human civilization.
In this project I move forward with research for an executable design pattern to allow web and native mobile application software to adapt… Mehr anzeigen

Contextual adaptation is key to the integrative success of Mobile into the human life. Today there is no development pattern available to succeed static personalization of digital content to deeper reasoning about user context and situative environment. It is this foundation this project aims at for an intelligent digital evolution of human civilization.
In this project I move forward with research for an executable design pattern to allow web and native mobile application software to adapt to contextual reasoning. A scientific paper will follow to share underlying principles for further development of the approach into contextual response frameworks. Weniger anzeigen

The core advantage of a mobile device being part of every second of our lives is that it enables our digital evolution. The key aspect of that co-existence is the personalisation and foremost contextual adaptation of a mobile device's content within our human interaction in a fast moving world.
Apart of various integrations of Mobile into our real world within the internet of things, Mobile systems have access to so much more information to be utilised at a much greater integrative level to… Mehr anzeigen

The core advantage of a mobile device being part of every second of our lives is that it enables our digital evolution. The key aspect of that co-existence is the personalisation and foremost contextual adaptation of a mobile device's content within our human interaction in a fast moving world.
Apart of various integrations of Mobile into our real world within the internet of things, Mobile systems have access to so much more information to be utilised at a much greater integrative level to empower our digital integration. Data about our situative environment, such as location, motion, noise and luminosity, as well as user pre-knowledge and expectations lead to a much more powerful experience in Mobile.
For that, in the research group of the University of Potsdam, we are developing a unique framework to encounter those contextual parameters in any Mobile application context and establish a breakthrough platform approach for the ultimate Mobile integration of tomorrow. Weniger anzeigen

Research in the development of algorithms and general strategies in the field of cross-platform user characteristics and behaviour analysis. This includes methodologies to accomplish proper tracking over multiple data sources, data integrity management, relational storage in graph storage models as well as real-time and batch analytics.

A personal project that covers an iOS mobile app with cloud-support using machine learning algorithms for feed content processing to enable individual information consumption of the next generation.

Research project to create a distributed operating system in peer-to-peer robotics hardware, which seamlessly integrates new components without downtimes. Hardware infrastructure is provided by iRobot.

A scientific project to analyse empirical evidence for linear complexity of transaction time with growing traversal paths in a distributed graph data storage facility.
The project features a sophisticated architecture with fully deployment in a Virtual Private Cloud (VPC) in Amazon Web Services. The architecture has a VPN and NAT connection management between the public and the private subnet in the VPC. Automated deployment is handled using Chef and Jenkins. The architecture contains an API… Mehr anzeigen

A scientific project to analyse empirical evidence for linear complexity of transaction time with growing traversal paths in a distributed graph data storage facility.
The project features a sophisticated architecture with fully deployment in a Virtual Private Cloud (VPC) in Amazon Web Services. The architecture has a VPN and NAT connection management between the public and the private subnet in the VPC. Automated deployment is handled using Chef and Jenkins. The architecture contains an API for business entity access. The API is connected to a distributed Titan graph database backed by a Cassandra cluster for massive scale on data and I/O (potentially 1bn daily tx at 100m edges in the graph). The architecture also features a monitoring infrastructure using StatsD, CollectD, DataStax OpsCenter and Graphite for realtime graph plotting.

Software that was developed during the project (API, Chef provisioning scripts, AWS deployment automation tools, benchmark load simulator) is Open Source and licensed under the MIT license. It can be found here: https://github.com/Streambot.

Paper available on request. Weniger anzeigen