Dr.-Ing. Michael Muma
Member of the Signal Processing Group at the Institute of Telecommunications, TU Darmstadt.
Office: S3|06 264
work +49 6151 16-21346
fax +49 6151 16-21342
Office Hours: Tuesday, 14-17h
Since 2014, Michael Muma works as a Postdoctoral Research Fellow, Lecturer, and Athene Young Investigator for the Signal Processing Group at TU Darmstadt. He has the right to supervise PhD students.
The topic of Michael's research is in the area of robust statistical signal processing with an emphasis on distributed signal processing, correlated and multi-sensor data.
Michael Fauß, Abdelhak Zoubir, nd Michael Muma will give a tutorial entitled Robust Data Science: Modern Tools for Detection, Clustering and Cluster Enumeration at the IEEE ICASSP 2020.
In May 2019, Michael has been appointed Associate Editor for the IEEE Transactions on Signal Processing.
Michael Muma is Guest Editor of the 2019 Elsevier Signal Processing Special Issue on Statistical Signal Processing Solutions and Advances for Data Science: Complex, Dynamic and Large-scale Settings.
In December 2018, Dr.-Ing. Muma was appointed lecturer for the lecture Robust Signal Processing With Biomedical Applications and the project seminar Robust and Biomedical Signal Processing.
In October 2018, the book Robust Statistics for Signal Processing by Abdelhak M. Zoubir, Visa Koivunen, Esa Ollila and Michael Muma was published with Cambridge University Press.
Abdelhak M. Zoubir, Visa Koivunen, Yacine Chakhchoukh and Michael Muma received the 2017 IEEE Signal Processing Magazine Best Paper Award for the article Robust Estimation in Signal Processing: A tutorial-style treatment of fundamental concepts.
From October 2017 on Dr.-Ing. Muma is appointed as Athene Young Investigator of Technische Universität Darmstadt. Dr.-Ing. Muma's proposed research project is entitled “Robust Statistics for Advanced Signal Processing”. The Athene Young Investigator Fellowship also provides Dr.-Ing. Muma with the right to supervise PhD students. The Athene Young Investigator program encourages the independence of outstanding established researchers at Technische Universität Darmstadt who pursue an academic career as a professor.
In 2016 he co-organized the Joint IEEE SPS and EURASIP Summer School on Robust Signal Processing Rüdesheim (Rhine), Germany. Material and further information can be found here:
He was project leader of the workpackage “Robust Distributed Multi-Source Detection and Labelling” of the EU Future and Emerging Technologies (FET) project HANDiCAMS (Heteregenous Ad-Hoc Networks for Distributed, Cooperative, and Adaptive Multimedia Signal Processing). The objective of the research is to develp robust decentral signal processing algorithms for wireless sensor networks. Further information on the project can be found at: www.handicams-fet.eu
Michael was the supervisor of the Technische Universität Darmstadt student team who achieved first place in the international IEEE Signal Processing Cup 2015. The IEEE Signal Processing Cup is a prestigious competition in which more than 50 teams from around the world compete in a challenging and interesting signal processing task. This year's competition topic was “Heart Rate Monitoring During Physical Exercise Using Wrist-Type Photoplethysmographic (PPG) Signals”.
Michael was a Research Associate in the Signal Processing Group from 2009 to 2014. The focus of his doctoral work was on robust statistical methods for signal processing with applications in biomedical and array signal processing. In 2014, he successfully defended his PhD with summa cum laude on “Robust Estimation and Model Order Selection for Signal Processing” (Download PhD thesis here).
His diploma project was to develop a time-frequency dependent coherence analysis to examine the role of the cardiopulmonary system (pulse and respiration) in the dynamics of eye's aberrations. This research was done at the School of Optometry in Brisbane, Australia.
Michaels student thesis was about parameter estimation for the detection of eyelids in videokeratoscopic images.
- Robust Signal Processing With Biomedical Applications (SS 2019)
- Robust and Biomedical Signal Processing(WS 2019/2020)
- Biomedical Lab(WS 2019/2020)
- Adaptive Filters (SS 2011)
- Speech and Audio Signal Processing(WS 2011/2012)
- Stochastic Signals and Systems (SS 2009, SS 2010, SS 2011)
- Digital Signal Processing Lab (WS 2009/2010, SS 2010, WS 2010/2011)
- Signal Detection and Parameter Estimation(SS 2013, WS 2018/2019)
- Advanced Topics in Statistical Signal Processing (SS 2014, SS 2018)
Supervision of PhD, Masters and Bachelors Projects
Current PhD Projects
- Jasin Machkour Robust and Adaptive Statistical Learning for High-Dimensional Data
Completed PhD Projects
- Freweyni Teklehaymanot Robust and Distributed Cluster Enumeration and Labelling (2019)
- Tim Schäck Photoplethysmography-Based Biomedical Signal Processing (Co-Supervision), 2018.
- Marlene Dejá Response Synchrony and Response Patterning of Psychophysiological Parameters in Emotion (Co-Supervision), 2018.
- Lala Khadidja Hamaidi Robust Distributed Multi-Source Detection and Labelling in Wireless Acoustic Sensor Networks (Co-Supervision), 2018.
Current Masters and Bachelors Projects
- Felicia Ruppel Robust Statistical Learning for High-Dimensional Data With Outliers
- Christian Schroth Robust Bayesian Cluster Analysis
- Sarosh Manzoor Detection of Road Defects for Autonomous Driving
Completed Masters and Bachelors Projects
- Mahmoud El-Hindi Online Speaker Identification With Limited Training Data 10/2019
- Jin He Machine Learning Methods for PPG Based Cardiovascular Parameter Estimation 08/2019
- Peter Paulat Early Detection of Adverse Health Events in Humans with Type I Diabetes (Co-Supervision) 08/2019
- Jasin Machkour Robust and Adaptive Statistical Learning for High-Dimensional Data 05/2019
- Martin Gölz Spatial Inference in Large-Scale Sensor Networks using Multiple Hypothesis Testing and Bayesian Clustering 03/2019
- Lisa Dawel PPG Based Cardiovascular Parameter Estimation: A Nonlinear Sparse Regression Approach 01/2019
- Ilaria Failla Robust Clustering and Cluster Enumeration Methods for Multi-View Imaging 01/2019
- Shuo Liu Emotion Classification from Physiological Signals 01/2017
- Bastian Alt Robust and Adaptive Methods for Linear and Sparse Inverse Problems 12/2016
- Burak Celik Heart Rate Tracking Algorithms for Wriste-Type Photopletysmographic Signals 10/2016
- Björn Achenbach Non-negative Blind Source Separation for Voice Activity Detection 10/2016
- Jack Dagdagan Localization of Speech Sources and Receiver Nodes in Uncalibrated Acoustic Sensor Networks 06/2016
- Christian Sledtz Advanced Methods for Heart Rate Extraction from Photoplethysmographic Signals 06/2016
- Burak Celik Implementation of an Algorithm for Heart Rate Monitoring using Wriste-Type Photopletysmographic Signals 06/2016
- Jun Liu Diffusion-Based Cluster Enumeration in a Distributed Sensor Network 05/2016
- Jasin Machkour Robust and Adaptive Regression for Linear and Sparse Models 04/2016
- Fabian Scheidt Fast Methods for Cooperative Localization in Wireless Sensor Networks 03/2016
- Burak Celik Modelling and Analysis of Photoplethysmographic (PPG) Signals 08/2015
- Jasin Machkour Bootstrap and Robust Regression 08/2015
- Hauke Radtki Demonstrator for Simulating Intracranial Pressure (ICP) Signals 07/2015
- Fabian Scheidt Cooperative Localization Using Sum-Product Algorithms Over Wireless Sensor Networks 01/2015
- Patricia Binder Distributed Robust and Adaptive Signal Classification in Wireless Sensor Networks 01/2015
- Daniel Kalus Distributed Robust and Adaptive Signal Detection in Wireless Sensor Networks 01/2015
- Keerati Suibkitwanchai Programming Work for a Biomedical Signal Processing Lab Experiment (SITT intern, Bangkok) 06/2014
- Stefan Vlaski Robust Bootstrap Methods for Signal Processing 07/2013
- Stefan Vlaski Implementation and Comparison of Robust Bootstrap Methods for Confidence Intervals 07/2013
- Jack Dagdagan Stationarity Testing in Presence of Outliers 06/2013
- Johannes Weise Feature Extraction for Emotion Quantification for Psychophysiological Signals 06/2013
- Stefan Richter Emotion Classification Based on Psychophysiological Features 06/2013
- Tim Schäck Parameter Estimation for Psychophysiological Signals in Presence of Artifacts 03/2013
- Jack Dagdagan Musical Instrument Identification Approaches 01/2013
- Stefan Richter Signal Modeling for Heart Rate Variability and a Comparison of known Features 12/2012
- Johannes Weise A Comparison of Spectral Coherence Estimators for Biomedical Signals 12/2012
- Bin Han Non-stationary Medical Signal Forecasting: Signal Decomposition and Robust Statistics 04/2012
- Tim Schäck Robust Model Based Detection of Eyelids in Videokeratoscopic Images 01/2012
- Falco Strasser Motion Artifact Removal in ECG Signals 12/2011
- Thanh Minh Vu Robust Estimation for Dependent Data 11/2011
- Andrea Schnall Robust Model Order Selection for Corneal Topography 10/2011
- Nevine Demitri Binaural Feedback Cancellation 04/2011
- Falco Strasser Robust Filtering of Autoregressive Processes 10/2010
- Ivan Derwin Detection of Deterministic Signals in Impulsive Noise 09/2010