Scholar
Michael Muma
Google Scholar ID: liTQko4AAAAJ
Prof. Dr.-Ing., Technische Universität Darmstadt
Citations & Impact
Citations
1,164
H-index
16
i10-index
24
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Recipient of the 2021 Early Career Award from EURASIP; Since 2022, Chair of the Technical Area Committee on Theoretical and Methodological Trends in Signal Processing of EURASIP; Organizer of the Statistical Learning for Signal and Image Processing (SLSIP) Workshop; Co-author of the paper 'An Unsupervised Approach for Graph-based Robust Clustering of Human Gait Signatures' which received the IEEE Radar Conference Student Best Paper Award; Delivered a tutorial titled 'Robust Data Science: Modern Tools for Detection, Clustering and Cluster Enumeration' at IEEE ICASSP 2020; Served as Associate Editor for the IEEE Transactions on Signal Processing from 2019-2023 and currently an Associate Editor for the IEEE Open Journal of Signal Processing; 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, appointed lecturer for the course 'Robust Signal Processing With Biomedical Applications' and the project seminar 'Robust and Biomedical Signal Processing'; In October 2018, co-authored the book 'Robust Statistics for Signal Processing' published by Cambridge University Press; 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'; Appointed as Athene Young Investigator of Technische Universität Darmstadt since October 2017, with the proposed research project 'Robust Statistics for Advanced Signal Processing', which also grants the right to supervise PhD students.
Research Experience
- Principal Investigator of the ERC Starting Grant 'ScReeningData'; Member of the LOEWE center emergenCITY and the BMBF Cluster for Future curATime; General Chair of the European Signal Processing Conference EUSIPCO 2027; Lecturer of the course 'Robust Data Science with Biomedical Applications'.
Background
- Head of the Robust Data Science Group at the Institute of Telecommunications, TU Darmstadt. His research focuses on new robust data science theory and methods with applications in signal processing and machine learning, particularly in biomedicine and engineering.
Co-authors