Professional summary

I am environmental professional with a Geoscience background. Since 2014, I have been active in the water and environmental sector, gaining experience both in industry and during my Master’s training. Over the past three years, I have developed a strong passion for GIS, Data Science, and programming, focusing on modelling, and creating tools to enhance efficiency in environmental and Geoscience work. I did my master’s thesis on environmental radon modelling using machine learning techniques, thereby acquiring knowledge of environmental modelling techniques. I am always eager to learn new tools and skills, which equipp me with a diverse skillset of varying knowledge level.

I am currently employed as a “Wissenschaftliche Mitarbeiter” by Technische Universität Darmstadt, working at HLNUG. My tasks include search for and analyse reports that are suitable for Underground Hydrogen Storage (UHS) in Hessen. I am also developing a workflow to combine 3D geological models and groundwater - including exploring methods to estimate porosity and permeability. In addition, I also develop tools with python when required.

Domain knowledge and expertise

Hydrogeology and Environmental Engineering: Professionally involved in the water sector since 2017 as a Supervision Consultant, I developed technical and administrative skills through surveys, design, and supervision of water points such as borewells, mini dams, rainwater harvesting schemes, and liaising with stakeholders. During my Master’s training, I acquired theoretical knowledge in water management, and practical works in water chemistry, sampling and modeling. I also have knowledge about spatial modelling of environmental parameters using geostatistics or machine learning approaches.

Tools : Hydrus, SWMM, MODFLOW-Model Muse, PHREEQC, and SWAT

Geoscience and GIS: A background in Geoscience, equpped me with an understanding of geological and hydrogeological systems. Therefore, I am capable of handling geological and hydrogeological data, and use appropriate tools either for geostatistical analysis or modelling.

Tools :GOCAD/SKUA and GeoDin (beginner), Google Earth Engiene, ArcGIS Products (ArcGISPro, ArcGIS Online, Survey123, Dashboards, and StoryMaps)

Programming and Data Science : Experienced in Python programming and Data Science, having led, or collaborated projects in water, environmental, and geoscience tasks. I have varying experience in developing and deploying machine learning and deep learning models for prediction, forecasting, and image detection tasks, either for Industry or for research. I am also skilled in creating PDF automation scripts, data cleaning scripts, and custom Streamlit apps.

Tools : SciKit-Learn, Tensoflow/Keras, GeoServer and Leaflet, PostgreSQL/PostGIS

Current projects I am currently working on/interested in the projects below.

Poro-Perm : Methods of estimating porositty and permeability spatially. Exploring both analytical and data-driven methods. These petrophysical properties are important for water/oil exploration, underground gas storage, as well as radon emanation.

HydroChemPy : A python package for calculating and processing hydrochemical data. Standalone app or integration as a toolbox into ArcGisPro

Aquadeep AI : ML-physics model combining 3D subsurface structures, ML and physics conbstraints for groundwater simulation. This is a long-term project, and I’m trying to put ideas together. Inputs are highly welcomed.

BlockCVPy : A package to perform spatial cross validation in python

Personal Interests: Outside of my professional work, I code for fun, watch Football and go to the gym.

For more details, feel free to look at documentation of my diverse skills in my portfolio and my curriculum vitae.

Contact

I am open to opportunities for collaborations. Feel free to reach out to me via my contacts at the side bar of this page.

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