Prof. Dr. Verónica Krapovickas
Humboldt Research Fellow
My research areas
I am interested in the co-evolution of animals and their environments, particularly in how ecosystem composition has changed through time and in response to major events in the history of the Earth. I use animal-sediment interactions as a proxy for investigating such questions. More recently my research has been focused on the reconstruction of the posture and gait of extinct mammals and dinosaurs through experimental studies, computational modeling, and simulation, validated by exceptionally preserved fossil footprints.
Home University / Research Institute
IDEAN – CONICET – Laboratorio de Paleontología de Vertebrados. Departamento de Ciencias Geológicas, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires.
Host research group
Prof. Dr. Björn Eskofier, Machine Learning and Data Analytics (MaDLab), Department Artificial Intelligence in Biomedical Engineering, FAU
Research period at the Faculty of Engineering, FAU
My research will develop at FAU during June – August 2023 and repeat during the same period in 2024 and 2025.
What is the focus of your research during your visit?
We recently discovered more than 1000 footprints produced by extinct mammals moving across volcanic landscapes in southern Patagonia. These footprints display a wide spectrum of gait styles and represent valuable direct information about the locomotion of early Mesozoic mammals. However, little is known about how the first mammals stood and moved.
The main goal of this project is to reconstruct the posture and gait patterns used by early mammals through experimental studies, modeling, and simulation approaches to validate using diverse and excellent-preserved fossil footprints. To our knowledge, this will be the first multiproxy approach using experimental motion analysis, deep neural networks, and simulation to decipher a 170 Myr old fossil footprint mystery.
I choose FAU because
The host institute, Machine Learning and Data Analytics Lab (MaDLab) at FAU combines the application of human gait analyses with experimental studies, engineering, and biomedical science, including machine learning, signal processing, and musculoskeletal modeling interacting dynamically. It is one of very few chairs worldwide that combine expertise in biomechanics and movement analysis with expertise in machine learning, and data analytics. Therefore, it is an ideal location to expand my expertise, and the field of ichnology, in both directions.
Prof. Dr. Björn Eskofier
Machine Learning & Data Analytics