Jan Wegner, Prof. Dr.

Damien Robert, Dr.

Vivien Sainte Fare Garnot, Dr.

Vivien is a PostDoc at the EcoVision Lab, Department of Mathematical Modeling and Machine Learning (DM³L) at the University of Zurich since 2022. He received his PhD in Geospatial Computer Vision in January 2022 at the French mapping agency (IGN, Gustave Eiffel University). His thesis explored novel deep learning architectures for crop type mapping from satellite image time series. Among other aspects, it focused on leveraging the temporal dimension of such data with attention mechanisms. The thesis also proposed a novel method to leverage the hierarchical structure of the crop type taxonomy, and showed how to address crop type mapping as a panoptic segmentation task. For his PostDoc, he is involved in the development of machine learning methods for forest monitoring, and other ecological applications. More broadly, Vivien is interested in methods that leverage remote sensing data to improve our understanding of the Earth’s evolution.

Lukas Drees, M.Sc.

Lukas joined the EcoVision Lab, Department of Mathematical Modeling and Machine Learning (DM³L) in June 2024 after working on his PhD in the remote sensing group at the University of Bonn, focusing on data science for crop systems. There, he also studied at the Institute for Geodesy and Geoinformation. In recent years, he was part of the PhenoRob cluster of excellence, researching machine learning solutions for sustainable agriculture. His emphasis was on image analysis and generating drone images of crop mixtures. In his doctoral thesis entitled “Data-driven Image Generation for Crop Growth Modeling”, he used generative neural networks to create reasonable and applicable images of future growth stages based on images of early growth stages and growth-influencing variables. For his postdoc, he will keep the focus on UAV-based plant data when it comes to detecting and segmenting invasive species in Switzerland. Methodologically, he will mainly deal with data imbalances, modeling uncertainties, and integrating multi-modalities and prior knowledge into neural networks.

Johannes Dollinger

Johannes joined the EcoVision Lab, Department of Mathematical Modeling and Machine Learning (DM³L) as a PhD student in 2023. He received his MSc from ETH Zurich in the Computer Science - Machine Intelligence track, and his BSc in Computer Science plus Computational Linguistics from the University of Munich (LMU). During his master thesis, he worked on a biologically-inspired alternative to backpropagation. His main research interests are applying advancements in deep learning to applications in ecology and specifically biodiversity. Johannes' current research is focused on modeling the distribution of species using satellite imagery. In times of drastic climate change he believes that university research can have a significant impact on solving enviromental problems. Tangentially to his main research, he is interested in advancing the state of the art of deep learning, and its societal and political impact.

Emilia Arens

Emilia is a PhD student at the EcoVision Lab, Department of Mathematical Modeling and Machine Learning (DM³L) at the University of Zurich since 2024. She received her Bachelor's degree in Cognitive Science from the University of Osnabrück and her Master's degree in Data Science with an interdisciplinary minor in Climate Science from ETH Zurich. During her master's thesis, she worked with the EcoVision lab on automatic damage detection in armed conflict areas where high-resolution data is scarce. Her research now evolves around the use of remote sensing data to address and investigate environmental problems such as biodiversity loss and the spread of invasive species.

Kaan Karaman, M.Sc.

Kaan Karaman is a PhD student at the EcoVision Lab, Department of Mathematical Modeling and Machine Learning (DM³L) at the University of Zurich since 2021. He received his Master's degree in Electrical and Electronics Engineering (EEE) at Middle East Technical University (METU) in February 2021 after completing two BSc degrees with high honors in both EEE and Physics at METU. His research interests include but are not limited to computer vision, deep metric learning, and remote sensing.

Marc Katzenmaier, M.Sc.

Marc is a PhD student at the EcoVision Lab, Department of Mathematical Modeling and Machine Learning (DM³L) at the University of Zurich since 2021. He received his Master’s degree in Robotics, Cognition, Intelligence from the Technical University of Munich. His research interests are computer vision and machine learning. Currently he is working on tree cell instance segmentation using microscopic images.

Yuchang Jiang, M.Sc.

Yuchang Jiang is a PhD student at the EcoVision Lab, Department of Mathematical Modeling and Machine Learning (DM³L) at the University of Zurich since 2021. She received the M.Sc degree in Geomatics from ETH Zurich in 2021 and obtained a B.Sc degree in Geomatics from The Hong Kong Polytechnic University in 2019. During her master thesis, she worked on tracking small fast-​moving objects in challenging environments across multiple cameras. During her PhD, she is working on global vegetation parameter assessments with satellite images. Her research interests lie in computer vision, deep learning, and remote sensing.