Martin Gölz

Martin Gölz

Martin Gölz

Member of the Signal Processing Group at the Institute of Telecommunications, TU Darmstadt.

Merckstr. 25
64283 Darmstadt

Office: S3|06 251

+49 6151 16-21351
+49 6151 16-21342

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Office Hours: Mondays, 1-3 p.m.

Martin received his B.Sc. in Electrical Engineering and Information Technology with major in Communication Engineering and Sensor Systems (CES) from Technische Universität Darmstadt in September 2016. In his bachelor's thesis, he dealt with bootstrapping sequential probability ratio tests. He received the “Rohde & Schwarz-Preis” for the best graduate of the year in CES and Computer Engineering in his faculty. Afterwards, he spent half a year as a research assistant at Aalto University, Finland, to work on nonparametric detection methods in the group of Prof. D.Sc. (EE) Visa Koivunen.

At the beginning of his master's in Electrical Engineering and Information Technology at Technische Universität Darmstadt, he was accepted into the Future Minds Student Program by Siemens AG and consequently started working part-time in the project management department of Siemens Mobility Division in Mannheim. For his master's thesis on spatial inference in large-scale sensor networks, he moved back to Finland to continue the collaboration with Aalto University. He received his M.Sc. with honors from Technische Universität Darmstadt in March 2019.

In April 2019, he started working towards his PhD with the Signal Processing Group. His research interest is in the field of (robust) statistical signal processing, in particular in detection and model order selection.


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Number of items: 5.


Gölz, M. ; Muma, M. ; Halme, T. ; Zoubir, A. M. ; Koivunen, V. (2019):
Spatial Inference in Sensor Networks using Multiple Hypothesis Testing and Bayesian Clustering.
In: 27th European Signal Processing Conference (EUSIPCO), A Coruña, Spain, September 2 to 6, 2019, [Konferenzveröffentlichung]

Halme, T. ; Gölz, M. ; Koivunen, V. (2019):
Bayesian Multiple Hypothesis Testing for Distributed Detection in Sensor Networks.
Minneapolis, MN, USA, In: IEEE Data Science Workshop, [Konferenzveröffentlichung]

Gölz, M. (2019):
Spatial Inference in Large-Scale Sensor Networks Using Multiple Hypothesis Testing and Bayesian Clustering.
Espoo, Finland, S. 83, [Online-Edition:],


Gölz, M. ; Koivunen, V. ; Zoubir, A. M. (2017):
Nonparametric Detection Using Empirical Distributions and Bootstrapping.
In: 25th European Signal Processing Conference (EUSIPCO), [Konferenzveröffentlichung]

Gölz, M. ; Fauß, M. ; Zoubir, A. M. (2017):
A Bootstrapped Sequential Probability Ratio Test for Signal Processing Applications.
In: Proc. of the IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), [Konferenzveröffentlichung]

This list was generated on Fri Sep 20 06:19:55 2019 CEST.