My research interest is a cumulative effect of multiple disciplines I am curious about. It mainly involves remote sensing, geodesy, statistics, machine learning and mathematics. I am always eager to learn new scientific, philosophical and political fields, so multi-disciplinary approach solutions fascinate me. My research goal is to learn as much as possible and use it to solve real-world problems, especially in natural hazards.
In particular, I am good at the following scientific fields; for other approaches and scientific fields, I need to google stuff before I come to conclusions:
I work with multitudes of deep and machine-learning models and actively develop them, primarily focusing on modelling earth surface processes.
A substantial part of my research also involves using mathematical modelling approaches such as solving forward and inverse problems, bayesian statistics, and geo-statistics.
As my background is in remote sensing and geodesy, most of the data that I work with comes in one way or another from remote sensing. I have been working with both optical and microwave remote sensing tools.
My scientific and application research focuses on the hydro-meteorological problems in the developing world because of the unique and multidisciplinary challenges in those regions.