About me: I am a data scientist with a PhD in spatial information systems and am working on causal inference in spatial processes. I studied Bachelor of Engineering and GIScience for my master’s degree. I have experience in marketing, environmental, health, human behaviour, and data management projects. I also have more than seven years of teaching experience.

My interests: Spatial Analysis, Causal Inference, Agent-Based Modelling, Mobility Analysis, GeoMarketing, Spatial Data Mining, and Spatial Data Management

Technical skills: Teamwork, Leadership, Programming Languages( Python and R), Tools and software (ArcGIS Pro, QGIS, FME, ENVI, Tableau, Shiny in R & Python, and ERDAS)

Currently, I am working on: Developing a Python package related to my PhD research and finalizing the thesis

Currently, I am learning: ML with Spark, AWS and Deep Learning on Spatiotemporal Data

I love Spatial Data Science because ⬇️

“Spatial data science can be viewed as a subset of generic “data science” that focuses on the special characteristics of spatial data, i.e., the importance of “where.” Data science is often referred to as the science of extracting meaningful information from data. In this context, it is useful to stress the difference between standard (i.e., non-spatial) data science applied to spatial data on the one hand and spatial data science on the other. The former treats spatial information, such as the latitude and longitude of data points, as simply an additional variable, but otherwise does not adjust analytical methods or software tools. In contrast, “true” spatial data science treats location, distance, and spatial interaction as core aspects of the data and employs specialized methods and software to store, retrieve, explore, analyze, visualize and learn from such data. In this sense, spatial data science relates to data science as spatial statistics to statistics, spatial databases to databases, and geocomputation to computation.” (Luc Anselin, 2019, “Spatial Data Science” in The International Encyclopedia of Geography: People, the Earth, Environment, and Technology.)

👨🏻‍💻Please feel free to to contact via this email!💁🏻‍♂️ Email or find me in this social medias: ⬇️