Hello! I'm

Geoinformatics graduate and GIS professional

“So learn that you may full and faultless learning gain,
Then in obedience meet to lessons learnt remain”.

This verse from the ancient Tamil text “Thirukkural” has stayed with me since childhood. It reminds me to learn thoroughly and to apply knowledge with discipline and responsibility. That mindset shaped my long-term interest in Earth sciences, where observations and models help us understand complex systems and respond to challenges such as climate change and air quality.

I am a Geoinformatics graduate from the University of Münster (Westfälische Wilhelms-Universität Münster) and currently work at Forschungszentrum Jülich (FZJ), IBG-3 as a Research Software Engineer. My work focuses on scientific software and FAIR research data infrastructures for environmental and Earth system applications. I contribute to the development of the Sensor Management System (SMS), the Time Series Management (TSM) self-service portal, a metadata editor, and the TERENO-DOI web application. I also work on a chatbot that supports users by retrieving relevant project documentation and structured information. My day-to-day development uses Python for data processing and automation and Vue.js/Nuxt.js for modern web front-end development.

Before joining FZJ, I started my research work in Germany at the German Aerospace Center (DLR) in Braunschweig, where I worked as a student assistant and completed my Master’s thesis. This experience strengthened my interest in reproducible software, simulation-driven workflows, and applied geospatial analysis. Throughout my academic path, I also gained experience in remote sensing and environmental data processing, which further motivated me to work at the interface of data science and Earth system research.

My current academic direction focuses on applying data science in earth sciences, especially where modelling and observational data come together. I am particularly interested in model–data fusion, parameter estimation, and machine-learning-based surrogates/emulators to improve efficiency in numerical modelling. I am also interested in satellite remote sensing and radiance-based approaches for atmospheric applications, including aerosols and air quality prediction.

In general, I enjoy working on:

• Scientific software engineering and open-source development


• FAIR research data infrastructures (metadata, quality control, pipelines)


• Spatio-temporal environmental data analysis and geospatial modelling


• Remote sensing and satellite data workflows for Earth system applications


• Machine learning methods for model integration and prediction

I enjoy collaborating in interdisciplinary teams, writing clear documentation, and building tools that others can use reliably. Looking forward to connecting.