Nicki Holighaus studied mathematics and theoretical computer sciences at Justus–Liebig–University, Gießen, Germany. He graduated in 2010. After three years of doctoral studies at the University of Vienna, Austria, where he worked as a research assistant at the Numerical Harmonic Analysis Group (NuHAG), he successfully defended his PhD thesis "Theory and implementation of adaptive time-frequency transforms” in October 2013.
Since August 2012 he is part of the Acoustic Research Institute's workgroup "Mathematics and Signal Processing in Acoustics", where he works on theoretical and applied aspects of frames and adapted time-frequency representations.
His research focuses on advanced time-frequency methods in signal processing, including time-frequency analysis, the mathematical theory and design of adaptive and adapted time-frequency representations, time-frequency processing in acoustics and the use of time-frequency representations in machine learning for acoustics.
Current research projects: MERLIN
- Theory and application of warped time-frequency representations
- Function spaces and discretization for structured continuous frames
- Structure of time-frequency phase
- Signal processing with time-frequency phase
- Deep learning with time-frequency features
- Neural audio generation
- Audio inpainting with generative neural networks
- Time-frequency processing and perception
- Holighaus N. (2013) Theory and implementation of adaptive time-frequency transforms. . University of Vienna, .
- Wiesmeyr C.; Holighaus N.; Sondergaard P. (2013) Efficient algorithms for discrete Gabor transforms on a nonseparable lattice. IEEE Trans. Signal Process., Bd. 61, S. 5131 - 5142.
- Perraudin N.; Holighaus N.; Sondergaard P.; Balazs P. (2013) Gabor dual windows using convex optimization. Proceedings of the SampTA 2013. Bremen, Germany S. 33-36.
- Necciari T.; Balazs P.; Holighaus N.; Sondergaard P. (2013) The ERBlet transform: An auditory-based time-frequency representation with perfect reconstruction. Proceedings of the 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013). Vancouver, Canada S. 498-502.