Thomas Altstidl

Thomas Altstidl, M. Sc.

Researcher & PhD Candidate

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

Room 01.012
Carl-Thiersch-Straße 2b
91052 Erlangen

Phone number: +49 9131 85-27921
Email: thomas.r.altstidl@fau.de

Microsoft Teams

📷 ul95odob@fauad.fau.de

Academic CV

Since 04/2021	Ph.D. Student Machine Learning and Data Analytics Lab at Friedrich-Alexander-University Erlangen-Nürnberg
04/2020 – 06/2020	Student Research Assistant Friedrich-Alexander-University Erlangen-Nürnberg, Machine Learning and Data Analytics Lab
10/2018 – 03/2021	M.Sc. in Computer Science Friedrich-Alexander-University Erlangen-Nürnberg Master Thesis: “Scale-invariant Convolution Kernels”
04/2019 – 03/2020 & 11/2020 – 01/2021	Student Research Assistant Fraunhofer Society, Precise Positioning and Analytics Department
04/2017 – 08/2017 & 10/2017 – 02/2018	Student Teaching Assistant Friedrich-Alexander-University Erlangen-Nürnberg, Distributed Systems and Operating Systems Group
10/2015 – 04/2019	B.Sc. in Computer Science Friedrich-Alexander-University Erlangen-Nürnberg Bachelor Thesis: “Application of Deep Learning Methods to Process Natural Phenomena”

Research Projects

DigiOnko

Publications

2022

Hecht D., Pfahler T., Ullmann I., Altstidl TR., Amer N., Jin Y., Eskofier B., Vossiek M.:
In Vivo Skin-Type Classification Using Millimeter-Wave Near-Field Probe Spectroscopy
2022 52nd European Microwave Conference (Milan, 27. September 2022 - 29. September 2022)
In: Institute of Electrical and Electronics Engineers (IEEE) (ed.): 2022 52nd European Microwave Conference, Milan: 2022
DOI: 10.23919/EuMC54642.2022.9924376
BibTeX: Download

2021

Altstidl TR., Kram S., Herrmann O., Stahlke M., Feigl T., Mutschler C.:
Accuracy-Aware Compression of Channel Impulse Responses using Deep Learning
International Conference on Indoor Positioning and Indoor Navigation (IPIN2021) (Lloret de Mar, Spain, 29. November 2021 - 2. December 2021)
In: Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN 2021) 2021
DOI: 10.1109/IPIN51156.2021.9662545
BibTeX: Download

Teaching

SS 2022	Machine Learning for Engineers I Machine Learning for Engineers II
WS 2021/2022	Machine Learning for Engineers I Machine Learning for Engineers II
SS 2021	Machine Learning for Engineers I Machine Learning for Engineers II

Students

12/2021 – 04/2022	Juliane Hoffmann (Bachelor Thesis) Annotation-efficient learning of surgical instrument activity
01/2022 – 06/2022	Stefan Kraft (Master Thesis) Self-supervised Learning of Monocular Depth Estimation in Crane Environments
01/2022 – 06/2022	Sven Steinkemper (Master Thesis) Machine Learning for Systems Biology: Data Analysis of IBD Patients’ Microarray Data
06/2022 – 11/2022	Christopher Kraus (Master Thesis) Compression of spatial information in wideband channel measurements using generative models