I am a geospatial data scientist and engineer deriving actionable insights from big data. In my approach I combine a Discrete Global Grid System to organize, merge,
and visualize large spatial datasets and Artificial Neural Networks (ANN) to crunch through the data make predictions.
To gain valuable geographic insights from data, multiple data sources need to be combined and analyzed at multiple scales. As big data from earth observation, location-based services (LBS), internet of things (Iot) and other sensors
as well as citizens becomes more and more abundant a data platform such as a DGGS and machine learning algorithms like ANNs are needed to process data and produce insights.
I studied Geography/Geomatics at Ruhr-University Bochum in Germany and joined the UN Operational Satellite Applications Program (UNOSAT) of
the United Nations Institute for Training and Research (UNITAR) in Geneva, Switzerland 2009. I worked there for about 1.5 years before moving to the State Key Laboratory for Information Engineering in Surveying Mapping and Remote Sensing (LIESMARS) at
Wuhan University, China, to pursue my doctoral degree of engineering in photogrammetry and remote sensing. My dissertation is about Shanghai's urban vibrancy using a multi-source data approach with SAR satellite imagery and location
based social media messages. Currently, I am working as a Postdoc at LIESMARS.