I have worked on various project over my early career, spanning from early projects on feeding behaviour of red kites (Milvus milvus), a bird of prey, in Germany over smaller landscape planning projects in New Zealand using geographical information systems (GIS). My more recent projects started probably with working under Prof. Falk Huettmann at the University of Alaska Fairbanks where I started to develop my interest in machine learning algorithms and applying them to ecological questions. I started working on predicting mossy habitats on Haida Gwaii, BC, Canada which are invaluable for marbled murrelets (Brachyramphus marmoratus) as nesting sites. At the same time I started working with Grant Humphries on the seabirds.net project. We also started on working on projects that deal with recruitment of young scientists into professional societies, with a manuscript being submitted soon. Back in Alaska I furthered my interest into marine science that had been sporadic before. This is when I wrote my master’s thesis on predicting vertical and horizontal zooplankton distribution into the future. This was accomplished by analyzing a vast pan-Arctic dataset of physical oceanography parameters provided by Prof. Igor Polyakov and predicting oceanographic layers such as the mixed layer depth into the future. Using those layers as well as future data from the Canadian Earth System Model (CanESM2) RCP85 on chlorophyll concentration and similar I predicted the zooplankton features into the year 2100. For the modeling, the machine learning algorithms RandomForest and TreeNet were used. Groundbreaking algorithms developed by Leo Breiman (University of California Berkeley) and Adele Cutler (Stanford University) for RandomForest and Jerome H. Friedmann for TreeNet. I got hooked on marine science and went to Québec, Canada for a PhD in marine oceanography under Prof. Louis Fortier. Now, my prime research is on optical imaging of Arctic zooplankton with an in-situ camera system that produces a continuous stream of detailed images of planktonic organisms that I analyze then using machine learning algorithms to automate species recognition. I then look at the forcing of biotic and abiotic environmental parameters on this fine scale vertical distribution as well as the coupling between the primary and secondary production.
More on some research in the designated fields below.