Philip Stoll | MaD Lab

Philip Stoll, M. Sc.

Alumnus

Department Artificial Intelligence in Biomedical Engineering (AIBE)
Lehrstuhl für Maschinelles Lernen und Datenanalytik

Room 01.020
Carl-Thiersch-Straße 2b
91052 Erlangen

Email: philip.ps.stoll@fau.de

Since 01/2023	Researcher and PhD Candidate Machine Learning and Data Analytics Lab Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
04/2020 – 09/2022	M.Sc. in Medical Engineering (Medical Image and Data Processing) Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Master’s Thesis: Long-Term Automated Behaviour Monitoring of Captive Polar Bears
04/2022 – 09/2022	Student assistant Innovation Lab for Wearable and Ubiquitous Computing
10/2016 – 09/2020	B.Sc in Medical Engineering Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Bachelor’s Thesis: Semantic Segmentation of the Human Eye for Driver Monitoring

VERA

2024

Zürl M., Stoll P., Brehm I., Sueskind J., Raab R., Petermann J., Zanca D., Simon R., von Fersen L., Eskofier B.:
Automated long-term monitoring of stereotypical movement in polar bears under human care using machine learning
In: Ecological Informatics (2024), p. 102840
ISSN: 1574-9541
DOI: 10.1016/j.ecoinf.2024.102840
BibTeX: Download

2022

Zürl M., Stoll P., Brehm I., Raab R., Zanca D., Kabri S., Happold J., Nille H., Prechtel K., Wünsch S., Krause M., Seegerer S., von Fersen L., Eskofier B.:
Automated Video-Based Analysis Framework for Behavior Monitoring of Individual Animals in Zoos Using Deep Learning—A Study on Polar Bears
In: Animals 12 (2022), p. 692
ISSN: 2076-2615
DOI: 10.3390/ani12060692
BibTeX: Download

Courses

Innovation Lab for Wearable and Ubiquitous Computing

Year	Type	Student	Title