Undergraduate in Chemistry, then, masters in Earth System Science followed by Ph.D. in Earth System Science in METU, Turkey for 4 years and terminated it in 2022.

I was interested in Analytical Chemistry most, and I diverged my career a bit for utilizing this for environmental management, observations, and remediation studies. Throughout the process, I also involved in numerical models, fluid mechanics, and machine learning topics, especially for remote sensing purposes. Especially spectroscopy, fluorescence, polarimetry techniques in analytical chemistry has so many things in common with the current optical remote sensing satellite sensors, that's why, I did not have much difficulty in working in the larger scale (from several millimeter cuvettes to 600-800 km altitude). Since 2019, I have been utilizing and processing satellite remote sensing data. Particularly, I have utilized data decomposition, unsupervised and supervised classification techniques for plant cover identification on land and water, object and change detection over land and water, and water quality retrieval especially for lakes. The satellite data I used were Landsat 5 TM, Landsat 8 OLI and TIRS, Sentinel-2 MSI, Sentinel-3 OLCI, Terra and Aqua MODIS, Suomi NPP VIIRS, and Planet Scope. I have used R and Python for processing them, and mostly decided to continue with Python for its practical nature in API availability and with my other works, like astropy package in Python.

In general, I have academic, governmental, private, and non-governmental organization sector experiences. These were largely in water resources management, environmental management in general, and in agriculture with a focus on high-end research works. Currently, I am more involved to scientific research part but still have connections with businesses and policy/citizen dimensions.