Matthias Zürl

Matthias Zürl, M. Sc.

Researcher & PhD Candidate

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

Room: Room 01.010
Carl-Thiersch-Straße 2b
91058 Erlangen

Academic CV

Since 07/2019 Researcher at the Machine Learning and Data Analytics Lab
Friedrich-Alexander-Universität Erlangen-Nürnberg
07/2019 – 03/2023 Head Coach of the Innovation Lab for Wearable and Ubiquitous Computing
Friedrich-Alexander-Universität Erlangen-Nürnberg
04/2016 – 12/2018 Research assistant at the Chair of Applied Physics
Friedrich-Alexander-Universität Erlangen-Nürnberg
10/2016 – 01/2019 Masters Degree in Physics
Friedrich-Alexander-Universität Erlangen-Nürnberg
Master Thesis: “Fabrication and Investigation of Homodyne Detectors for Terahertz Radiation
10/2011 – 04/2017 Study program for High school teaching in Math and Physics
Friedrich-Alexander-Universität Erlangen-Nürnberg
10/2011 – 10/2015 Bachelors Degree in Math and Physics
Friedrich-Alexander-Universität Erlangen-Nürnberg
Bachelor Thesis: “Entwicklung und Aufbau eines Experiments für das physikalische Praktikum für Fortgeschrittene: Transporteigenschaften von Ladungsträgern in Halbleitern – Hall-Effekt”

Research Projects






Innovation Lab for Wearable and Ubiquitous Computing

Supervised Projects:

Term Title
Winter Term 2022 / 23 Insecrecy
Summer Term 2022 ChampTrack
Winter Term 2021 / 22 VitalSense
Summer Term 2021 Dungineers
Winter Term 2020 / 21 Argus
Summer Term 2020 Stress+
Winter Term 2019 / 20 Smart City Greens



  • Mittsommernacht Tiergarten Nürnberg, Künstliche Intelligenz in der Zoo-Forschung, Nürnberg, 28.07.2023
  • Tierpatentreffen Nürnberg, Eisbären und Künstliche Intelligenz, Nürnberg, 21.07.2023
  • CVPR, CV4Animals, PolarBearVidID: A Video-Based Re-Identification Benchmark Dataset for Polar Bears, Vancouver, 18.06.2023
  • European Association for Aquatic Mammals, Dolphin-Welfare Evaluation Tool (WET): Current Status and Future Digital Development, Valencia, 10.03.2023
  • Master Digital Business Administration, An Introduction into Deep Learning, Erlangen, 21.01.2023
  • KI-Days, Keynote on Artificial Intelligence, CodeCamp:N, Nürnberg, 20.10.2022
  • Dolphin WET Conference, Invited Speaker on Computer Science in Biology, Nürnberg, 03.10.2022
  • Tech|Day on Deep Learning, Workshop, Zollhof, Nürnberg, 17.05.2022
  • PintOfScience Festival, Talk, Nürnberg, 09.05.2022
  • Master Digital Business Administration, Lecture and Exercises in Machine Learning, Erlangen, 12.03.2022
  • Tech|Day on Deep Learning, Workshop, together with Stefan Seegerer, Zollhof, Nürnberg, 01.12.2020


In the context of several workshops on Deep Learning, which I have conducted together with my colleague Stefan Seegerer, we have developed a cheatsheet for Pytorch, which turned out to be pretty helpful:



Student Supervision

Year Type Student Titel
2023 Master Project Jie Yi Tan

Re-Identification for Orcas

2023 Master Thesis Sara Zarifi

Lynx Re-Identification from Camera Trap Images in the Wild

2023 Master Project Robert Schröter

Gallery Size Investigation for Polar Bear Re-ID

2023 Master Thesis Nils Steinlein

Video-based Dataset for Animal Re-Identification

2023 Master Thesis Jonas Süßkind

Video-based Behavior Analysis of Polar Bears Under Human Care

2023 Master Thesis Julian Deyerler

Wing Print: Automated Bat Re-Identification Through Distinct Wing Membrane Patterns

2022 Master Thesis Paul Maas

Ubiquitous Investigation of Overall State of Health Using a Smart Toothbrush in Palliative Care

2022 Master Thesis Jonas Beyer

Unsupervised Polar Bear Re-Identification

2022 Master Thesis Philip Stoll

Long-Term Automated Behavior Monitoring of Captive Polar Bears

2021 Master Thesis Richard Dirauf

Video-based Re-Identification of captive Polar Bears

2021 Master Thesis Wenyu Zhang

Classification of localized defects on silicon carbide (SiC) wafers using domain adaptation techniques

2020 Bachelor Thesis Daniel Seitz

Unsupervised learning for the classification of process steps in spatial-temporal data