Shirin Najdi is a PhD candidate of the electrical and computer engineering department at Nova university of Lisbon. She is also a researcher at CA3- Computational Intelligence Research Group of UNINOVA.

Shirin has receivedher MSc degree in signal processing in 2011 from university of Tabriz, Iran.Her master thesis topic was about efficient audio fingerprinting using discrete wavelet transform.

Currently, in her PhD, she is focused on biomedical signalprocessing, specifically on the application of recent data mining techniquesfor sleep data representation.

• Biomedical Signal Processing
  
• Data Mining
  
• Feature Extraction and Selection
  
• Deep Learning
  

• Deep Sleep

• [1] Najdi, S., Gharbali, A. A., & Fonseca, J. M. (2016). Feature Ranking andRank Aggregation for Automatic Sleep Stage Classification: A Comparative Study. Submitted to BioMedical Engineering OnLine.
• [2] Batista, A. G., Najdi, S., Godinho, D. M., Martins, C., Serrano, F. C.,Ortigueira, M. D., & Rato, R. T. (2016). A multichannel time-frequency and multi-wavelet toolbox for uterine electromyography processing and visualisation. Computers in Biology and Medicine, 0(0), 1215–1222.

• [1] Gharbali, A. A., Fonseca, J. M., Najdi, S., & Rezaii, T. Y. (2016). Automatic EOG and EMG Artifact Removal Method for Sleep Stage Classification. In Technological Innovation for Cyber-Physical Systems (pp. 142–150). Springer.
• [2] Najdi, S., Gharbali, A. A., & Fonseca, J. M. (2016). A Comparison of Feature Ranking and Rank Aggregation Techniques in Automatic Sleep Stage
  Classification Based on Polysomnographic Signals. In Bioinformatics and Biomedical Engineering (pp. 230–241). Springer.
• [3] Najdi, S., Ebrahimi, A. (2013). Audio fingerprinting based on multiresolution analysis of Discrete Wavelet Transform. In 2013 10th International ISC Conference on Information Security and Cryptology (ISCISC) (pp. 1–5). IEEE.

• Camarinha-Matos, L. M., Falcão, A. J., Vafaei, N., & Najdi, S. (2016). Technological Innovation for Cyber-Physical Systems: 7th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2016, Costa de Caparica, Portugal, April 11-13, 2016, Proceedings. Springer International Publishing