About
Maria Sandsten is a Professor at the Department of Mathematical Statistics, Faculty of Engineering (LTH), Lund University. She serves as a senior researcher in multiple interdisciplinary initiatives including eSSENCE: The e-Science Collaboration, NanoLund, and ELLIIT, with a focus on AI, digitalization, and engineering health. Her research centers on statistically robust methods for audio and acoustic analysis, particularly optimal time-frequency techniques.
- Lund University (LTH) - Professor, Department of Mathematical Statistics
- NanoLund: Centre for Nanoscience - Principal Investigator
- ELLIIT: Linköping-Lund IT Initiative - Professor
- Sentio: Sustainable Manufacturing - Professor
Research Interests: Maria's work bridges time-frequency analysis, spectral estimation, and multitaper methods to develop noise-robust signal processing tools. Recent projects include adaptive change-point detection for sound event labeling and differentiable log-mel spectrogram layers in neural networks.
Selected Scientific Contributions: Her 2024 publications highlight advancements in:
- EEG-based speech tracking for hearing-impaired listeners
- Interdisciplinary machining sustainability frameworks
- Deep learning integration for enhanced time-frequency representations
- Coherence measures for neuroacoustic applications
