MSc in Electronics & Telecommunications (ISEL) · Acoustic/Speech Signal Processing · Machine Learning
My research interests lie at the intersection of signal processing, machine learning and statistical pattern analysis. I am particularly interested in interpretable feature representations, robust generalisation, and understanding why models succeed or fail. My recent work has focused on speech-based voice pathology classification, leading to two peer-reviewed publications (CISTI 2023, CENTERIS 2025).
Research interests
- Signal processing from first principles
- Voice pathology discrimination
- Biomedical signal processing
- Digital communications (OFDM, beamforming, channel modelling)
- Time-series analysis and forecasting
- Feature engineering and multimodal feature fusion
- Statistical learning and interpretable machine learning
- Cross-dataset generalisation and robust ML
- Root-cause analysis rather than benchmark-driven optimisation
Research portfolio
- ⚙️ voice-pathology-mfbm-acoustic-fusion-intracorpus — Intra-corpus evaluation of spectral-acoustic fusion across sMEEI and USP databases using SVM classifiers.
- ⚙️ voice-pathology-mfbm-acoustic-fusion-intercorpus — Cross-corpus generalisation and domain shift analysis, evaluating how feature fusion and PCA affect decision boundaries.
- 🔬 paper-voice-pathology-mfbm-acoustic-fusion — Reproducibility package for our spectral-acoustic fusion paper published in Procedia Computer Science (CENTERIS 2025).
- 🔬 paper-voice-pathology-mfbm — Code and assets for our MFBM-based voice biomarker analysis (CISTI 2023).
📍 Portugal (Centro)
Open to: DSP/ML roles: on-site (Central Portugal) · hybrid (Portugal/Spain) · remote