๐ Hello! I’m Shuang Song, a postdoctoral researcher at Max Planck Institute of Geoanthropology. I currently serve for two departments: the Department Structural Changes of the Technosphere and the Department of Co-evolution of Land Use and Urbanisation.
My research primarily uses water as a link to study the co-evolution between human society and the natural environment. Based on my interdisciplinary background in Physical Geography and the Study of History, I currently focus on the long-term evolution of water management (e.g., irrigation, flood control, and water supply) and its impact on human society, currently focusing on the Yellow River Basin, China.
My approach mainly involves modeling and data analysis. I developed the open-source Agent-based Modeling framework for real-world SES simulation ABSESpy
and led PaperBell
team, an academic note-taking workflow for researchers based on Obsidian.
My research is highly interdisciplinary; I welcome scholars and students from Geography, Archaeology, History, Sociology, Computer Science, and Psychology to collaborate. The team offers fully remote positions, feel free to get in touch by email or online meeting.
Learn more about me through the below materials:
Ph.D. of Physical Geography, 2018-2023
Beijing Normal University
Study of History (2nd Major), 2014-2018
Sun Yat-Sen University
B.S. of Physical Geography, 2014-2018
Sun Yat-Sen University
I master programming in Python for years. Recently, I work on an open-sourced package ABSESpy
.
I am proficient in using LaTeX for papers.
Proficient in geographic information tools QGIS
and ArcGIS
.
The most classic agent-based modeling software, but I now think mesa
and ABSESpy
are better.
I can analyze raster datasets with popular packages like xarray
, rasterio
, gdal
.
I’m passionate about making beautiful charts.