Professor Saeid Sanei

BSc, MSc, PhD, DIC, SMIEEE, FBCS

 

 

 

Current Position

Visiting Professor (Digital Health)

Communications and Signal Processing Group

Electrical and Electronic Engineering Department

Imperial College London,

Exhibition Rd., London SW7 2AZ, UK

s.sanei@imperial.ac.uk

Google Scholar: https://scholar.google.co.uk/citations?user=zUaubUQAAAAJ&hl=en

SHORT BIOGRAPHY

Saeid Sanei received his PhD from Imperial College London in 1991. He worked in National University of Singapore, King’s College London, Cardiff University, University of Surrey, Nottingham, and Imperial College London (as a Visiting Professor in Digital Health since Jan. 2017). He is a Fellow of British Computer Society (FBCS), Senior Member of IEEE (SMIEEE) and has been a member of prestigious IEEE MLSP and SPTM Technical Committees. His research involves development of adaptive and nonlinear systems including consensus and adaptive diffusion networks, tensor factorisation, graph signal processing, compressive sensing, subspace analysis, machine learning including deep neural networks, and many others mostly with applications to biological signals and systems. 

        He has served as the Director of Digital Signal Processing Centre in Cardiff University and the Deputy Head of Computer Science Department in University of Surrey.

       He developed four UG and MSc programs and many teaching modules and lectured more than 30 different subjects across Electrical Engineering, Computer Science, and Bioengineering.

       He served as the External Examiner to Glasgow University, London Southbank University, University of Mauritius, Singapore Institute of Management, and currently Royal Holloway University of London (RHUL), where he also serves as the External Assessor of the Academic Promotion Panel.

       Saeid has 4 patents (another two are in pipeline), published 5 books, 7 Edited Books, 8 book chapters, and over 440 peer-reviewed papers (Google Scholar citation can be found Here).

       He also presented 32 keynote talks, tutorials, and workshops, and over 60 invited talks in prestigious international conferences and institutions and received several best paper awards.

      Saeid, internationally known for his brain research, has supervised 6 Postdocs and 44 successful PhD students as the main supervisor. He has been a Distinguished Lecturer to Nanyang Singapore and served as the REF Assessor and External to Hong Kong Polytechnic University during 2018-2019.

      He has been an Associate Editor for the IEEE Signal Processing Magazine, IEEE Signal Processing Letters, and Journal of Computational Intelligence and Neuroscience and several others. He organized and chaired several reputed conferences including IEEE ICASSP 2019.

      He collaborates with world renown research laboratories such as RIKEN in Japan, Temasek Laboratory in Singapore, and GIPSA-Lab in France as well as many Neuroscience and other clinical departments in the UK hospitals and worldwide.

      Last but not least, he is a Co-Founder of Brain Aware Charity.

 

CONTENT:

  • Current Research

  • Conference Organisation

  • Editorial Activities and International Recognition

  • Publications

  • Adverts for Journal Special Issues Currently Open for Submissions

 

   Current Research:

  • Brain-Computer Interfacing (BCI)
  • Seizure Identification by Analysis of Interictal Epileptiform Discharges (IED) and Brain Response to Single Pulse Electrical Stimulation (SPES),
  • EEG Signal Processing & Machine Learning,
  • Infant's Lung Sound Analysis and Automated Diagnosis,
  • Heart Murmur Identification and Classification,
  • Processing of other Biosignals  and Medical images,
  • Cooperative Networks for BCI, Body Sensor Networks, Source Localisation, Crowd Modelling, and Robot Swarming.

 

 

Conference Organisation (Leadership & Networking)

 

1. Co-organizer and Finance Chair of IEEE Statistical Signal Processing Workshop, SSP2001, Singapore

2. Organizing Chair, 15th Int. Conf. on Digital Signal Processing, DSP 2007, July 2007, Cardiff, UK.

3. General Chair and Organizer, IEEE Statistical Signal Processing Workshop, SSP2009, Aug-Sept 2009, Cardiff, UK.

4. Honorary Chair, Third Int. Conf. on Bio-inspired Systems and Signal Processing, 2010, Valencia, Spain

5. General Chair, IEEE International Workshop on Machine Learning for Signal Processing (MLSP), UK, 2013 (and LVA/ICA 2013).

6. General Chair and Organizer of Seizure Engineering Conference, Surrey, UK, 2015

7. Technical Program Co-Chair of European Signal Processing Conference, EUSIPCO 2016, Budapest, Hungary.

8. Honorary Chair, 1st Int. Conf. on Emerging Trends in Electrical, Electronic, and Communication Engineering (ELECOM 2016) Mauritius, 2016.

9. General Chair and Organizer of the 22nd Int. Conf. on Digital Signal Processing, DSP 2017, London, UK.

10. International Chair of the 2nd Int. Conf. on Emerging Trends in Electrical, Electronic, and Communication Engineering (ELECOM 2018) Mauritius, 2018.

11. General Chair and Organizer of the 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019, Brighton, UK.

12. Member of Advisory Committee of IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop 23-26 June 2020, Nafplio, Greece.

13. International Chair of the 3rd Int. Conf. on Emerging Trends in Electrical, Electronic, and Communication Engineering (ELECOM 2020) Mauritius, 2020.

14. Tutorial Co-Chair of 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022, Singapore.

15. Technical Program Chair; International Forum on Signal Processing (IFSP 2021) in Sanya, China, January 1-3, 2021.

16. International Chair of the 4th Int. Conf. on Emerging Trends in Electrical, Electronic, and Communication Engineering (ELECOM 2022) Mauritius, 2022.

17. Award Panel Chair of Digital Signal Processing Conference, DSP 2023, Rhodes Island, Greece.

18. Special Sessions Chair of the IEEE Statistical Signal Processing 2023 (SSP 2023), Hanoi, Vietnam

19. Advisory Board Chair of IEEE Machine Learning for Signal Processing (MLSP 2024), London, UK.

20. Honorary Chair of the 16th International Conference on Signal Processing Systems (ICSPS 2024) will be held in Kunming, China during November 15-17, 2024.

21. International Chair of the 5th Int. Conf. on Emerging Trends in Electrical, Electronic, and Communication Engineering (ELECOM 2024) Mauritius, 2024.

 

Editorial Activities and International Recognition

 

1. Associate Editor of Journal of Computational Intelligence and Neuroscience.

2. Guest Editor of the EURASIP Journal of Computational Intelligence and Neuroscience special issue in EEG/MEG Signal Processing,

3. Associate Editor; IEEE Signal Processing Letters, May 2009-May 2011.

4. Guest Editor; Majlesi Journal of Electrical Engineering, 2010.

5. Guest Editor of the EURASIP Journal of Computational Intelligence and Neuroscience special issue on Bioinspired Systems and Cognitive Signal Processing,

6. Guest Editor: Springer Journal special Issue on Machine Learning for Signal Processing, 2013. 

7. Guest Editor of Elsevier Journal of Computers and Electrical Engineering; Special Issue on Biomedical Signal and Image Processing and Biometrics, 2013-2014.

8. Associate Editor of IEEE Signal Processing Magazine, for Columns & Forum; since 2014.

9. Editorial Board Member; Journal of Frontiers in Biomedical Technologies, since 2013.

10. Guest Editor of the Sixth Special Issue on Advances in Biomedical Signal and Image Processing, and Biometrics, Elsevier Journal of Computers and Electrical Engineering (2015-2016).

11. Guest Editor of the Journal of Bioengineering, Special Issue in Biomedical Signal Processing, 2016.

12. Editorial Board Member of Journal of Neurodevelopmental Cognition, Since Nov. 2016

13. Editorial Board Member of Journal of Signals, Since March 2017. 

14. Associate Editor of Elsevier Journal of Sciencia Iranica, since 2017.

15. Guest Editor of Journal of Computer Networks and Communications, 2018.16. 

16. Guest Editor of Elsevier Journal of Computers and Electrical Engineering Special Issue on Recent Advancements in Biomedical Engineering, 2019-2020. 

17. Guest Editor of Journal of Biosensors (together with H. Costin), Special Issue on Intelligent Biosignal Processing in Wearable and Implantable Sensors, 2020.

18. Guest Editor of Journal of Sensors (together with S. Kouchaki and X. Ding), Special Issue on AI and IoT Enabled Solutions for Healthcare, 2021-2022.

19. Guest Editor of Journal of Biosensors (Together with H. Costin), Special Issue on Applications of AI and Wearable Biosensors in Precision, Personalized and Predictive Medicine, 2022-2023.

20. Guest Editor for the Special Issue Body Sensor Networks and their applications to healthcare and health technology for Elsevier Journal of Smart Health, 2023-2024 (https://www.sciencedirect.com/journal/smart-health/about/call-for-papers). 

21. Guest Editor of Journal of Bioengineering (Together with T. KM Lee), Special Issue on Surrogate Biomedical Data Generation, 2024 (https://www.mdpi.com/journal/bioengineering/special_issues/8GN99VCI60).

 

 

 

Publications

 

Books (monograms):

 

  1. S. Sanei and J. A. Chambers, EEG Signal Processing and Machine Learning, John Wiley & Sons, 2021, ISBN-10: 978-1119386942; ISBN-13: 978-1119386940.
  2. S. Sanei, D. Jarchi and A. G. Constantinides, Body Sensor Networking, Design and Algorithms, John Wiley & Sons, 2020, ISBN-10: 978-1-119-39001-5 (eBook), ISBN-13: 978-1-119-39002-2 (hardcopy).
  3. S. Sanei and H. Hassani, Singular Spectrum Analysis of Biomedical Signals, CRC Press, 2015, ISBN-10: 1466589272.
  4. S. Sanei, Adaptive Processing of Brain Signals, John Wiley & Sons, 2013, ISBN- 10: 0470686138.
  5. S. Sanei and J. A. Chambers, EEG Signal Processing, John Wiley & Sons, 2007, ISBN-10: 0470025816.

 

Books (editorial)

 

  1. S. Sanei, J. Chambers, J. McWhriter, Y. Hicks, and A. G. Constantinides, Proceedings of the 15th Int. Conf. on Digital Signal Processing (Eds.), 2007.
  2. S. Sanei, J. Chambers, and J. McWhriter, Proceedings of the 2009 IEEE Int. Workshop on Statistical Signal Processing (Eds.), 2009.
  3. F. Babiloni, A. Cichocki, S. Sanei, L. Astolfi, F. Cincotti, and S. Gonzalez Andino, Computational Intelligence & Neuroscience; Selected papers from the 4th International Conference on Bioinspired Systems and Cognitive Signal Processing, 2011.
  4. S. Sanei, P. Smaragdis, A. Nandi, A. T. S. Ho, and J. Larsen: Proceedings of the International Workshop on Machine Learning for Signal Processing (MLSP) 2013, IEEE Press, (Eds.) Sept. 2013.
  5. P. Fleming, N. Vyas, S. Sanei, and K. Deb, Emerging Trends in Electrical, Electronic and Communications Engineering: Proceedings of the First International Conference on Electrical, Electronic and Communications Engineering (ELECOM 2016), Bagatelle, Mauritius, November 25 -27, 2016 - Lecture Notes in Electrical Engineering 416. 
  6. P. Fleming, N. Vyas, S. Sanei, K. Deb, and A. Jackobsson, Smart and Sustainable Engineering for Next Generation Applications: Proceeding of the Second International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM 2018), November 28-30, 2018, Mauritius - Lecture Notes in Electrical Engineering 561
  7. H. Costin and S. Sanei, Intelligent Biosignal Processing in Wearable and Implantable Sensors, A special issue of Biosensors (ISSN 2079-6374), MDPI, 2022.

 

 

Book Chapters:

 

  1. A. Prochazka,  M. Kloubcov´a, S. Sanei, T. Dostalova, J. Charvat, O. Vysata, D. Mandic, H. Charvatova, and V. Marık, Computational Intelligence and Augmented Reality in Stomatology, Augmented and Virtual Reality in Healthcare, Wiley Scrivener Pub., H. Murthy, K. P. Kumar, A. Unal, T. P. Fowder (Eds), June 2024.
  2. S. Sanei, Data-Driven Approaches for Processing of Epileptic Electroencephalograms, Book: Deep Learning in Signal Processing, for Continuing Education, Editors: Wan-Chi Siu, Anthony Chan, Man Wai Mak, and S. Y. Kung (in print), 2024.
  3. M. K. Islam, A. Rastegarnia, and S. Sanei, Signal Artifacts and Techniques for Artifacts and Noise Removal. In: Ahad M.A.R., Ahmed M.U. (eds) Signal Processing Techniques for Computational Health Informatics. Intelligent Systems Reference Library, vol 192. pp. 23-79, 2021, Springer, Cham. https://doi.org/10.1007/978-3-030-54932-9_2.
  4. S. Sanei, S. Monajemi, A. Rastegarnia, O. Geman, and S.-H. Ong, “Multitask Cooperative Networks and their Diverse Applications”, Chapters 15-05, Learning Approaches in Signal Processing" Pan Stanford DSP Book Series, 2018 (Editors: Wan-Chi Siu, Lap-Pui Chau, Liang Wang, Tieniu Tan).
  5. S. Monajemi, S. Ensafi, S. Lu, A. A. Kassim, C. L. Tan, S. Sanei and S-H Ong, “Adaptive Distributed Dictionary Learning for HEp-2 Cell Classification”, In Biomedical Signal Processing in Big Data. Florida, USA: Taylor & Francis Group, LLC, a State of Delaware limited liability company, 2017.
  6. A. Khalili, A. Rastegarnia, W. M. Bazzi, and S. Sanei, Maximum Correntropy based Distributed Estimation of Adaptive Networks, Advances in Computer Communications and Networks - from Green, Mobile, Pervasive Networking to Big Data Computing, River Publisher, Eds. Aaron Striegel, Min Song, and Kewei Sha, 2016.
  7. S. Sanei and B. Makkiabadi, Tensor Factorization with Application to Convolutive Blind Source Separation of Speech, Machine Audition: Principles, Algorithms and Systems, IGI-Global Pub., Edited by W. Wang, 2009.
  8. M. Jing and S. Sanei, Simultaneous EEG-fMRI Analysis with Application to Detection and Localizaion of Seizure Signal Sources, Recent Advances in Signal Processing, IN-TECH Pub., ISBN 978-953-307-002-5, Edited by A. A. Zaher, 2009.

 

Published Journal Papers                 Conference papers (appx. 300) can be found HERE

 

154. S. Shirani, B. Abdi-Sargezeh, A. Valentin, G. Alarcon, and S. Sanei, “Do interictal epileptiform discharges and brain responses to electrical stimulation come from the same location? An advanced source localization solution, IEEE Transactions on Biomedical Engineering, DOI. 10.1109/TBME.2024.3392603.

153. S. Kouchaki, X. Ding, and S. Sanei, (eds.) AI- and IoT- Enabled Solutions for Healthcare, Sensors, 24(8), 2607; 2024.

152. A. Falcon-Caro, E. Peytchev, and S. Sanei, “Adaptive network model for assisting disables through crowd monitoring and control,” MDPI Journal of Bioengineeing (Feature Paper), Bioengineering, Vol. 11, Issue 3, 10.3390/bioengineering11030283, (IF=4.6).

151. A. Khalili, A. Rastegarnia, A. Farzamnia, S. Sanei, and A. Tinati, “Tracking analysis of maximum Versoria criterion based adaptive filter, IEEE Access, vol. 12, 30747-30753, Doi. 10.1109/ACCESS.2024.3370471.

150. A. Mobaien, R. Boostani, and S. Sanei, "Improving the performance of P300-based BCIs by mitigating the effects of stimuli-related evoked potentials through regularized spatial filtering" Journal of Neural Engineering, 2024 Jan 31.  doi: 10.1088/1741-2552/ad2495 [IF=5]

149. A. Falcon-Caro, S. Shirani, J. Farriera, J. Bird, and S. Sanei, “Formulation of common spatial patterns for multitask hyperscanning BCI,” IEEE Transactions on Biomedical Engineering, published online 22/01/2024, DOI: 10.1109/TBME.2024.3356665.

148. B. Abdi-Saegezeh, S. Shirani, S. Sanei, et al., "Detection of interictal epileptiform discharges from EEG: A review of signal processing and machine learning approaches," Elsevier Journal of Computers in Biology and Medicine, vol. 168, Jan 2024, 107782, DOI. 10.1016/j.compbiomed.2023.107782 [IF=7.7].

147. S. Kouchaki, X. Ding, and S. Sanei, (eds.) AI and IoT Enabled Solutions for Healthcare, Biosensors, 2024. 

146. A. Sam, R. Boostani, S. Hashempour, M. Taghavi, and S. Sanei, “Depression identification using EEG signals via a hybrid of LSTM and spiking neural networks,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pp. 4725-4737, Dec. 2023, doi. 10.1109/TNSRE.2023.3336467.

145. A. Zandbagleh, H. Azami, S. Mirzakouchaki, M. R. Daliri, S. Sanei and P. Premkumar, “Multiscale fluctuation dispersion entropy of EEG as a physiological biomarker of schizotypy,” IEEE Access, vol. 11, pp. 110124-110135, 2023, doi. 10.1109/ACCESS.2023.3321868.

144. A. Zandbagleh, S. Mirzakuchaki, M. R. Daliri, A. Sumich, J. D. Anderson and Saeid Sanei, “Graph-based analysis of EEG for schizotypy classification applying flicker Ganzfeld stimulation,” Journal of Nature Schizophrenia, Schizophrenia vol. 9, No. 64, pp. 1-10, 2023.

143. S. Shirani, B. Abdi-Sargezeh, A. Valentin, G. Alarcon, and S. Sanei "Localization of epileptic brain reponses to single-pilse electrical stimulation by developing an adaptive iterative linearly constrained minimum variance beamformer," International Journal of Neural Systems, Vol. 33, Issue No. 10, Article No. 2350050, 2023 [IF=8].

142. I. Boukhennoufa, D. Jarchi, X. Zhai, V. Utti, S. Sanei, T. K. M. Lee, Jo Jackson, and K. D McDonald-Maier, “TS-SGAN - an approach to generate heterogeneous time series data for post-stroke rehabilitation assessment,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pp. 2676-2687, 2023. DOI: 10.1109/TNSRE.2023.3283045.

141. S. Shirani, A. Valentin, G. Alarcon, F. Kazi, and S. Sanei, "Separating inhibitory and excitatory responses of epileptic brain to single-pulse electrical stimulation," International Journal of Neural Systems, 33:2, 2023, 2350008 (9 pages), DoI. 10.1142/S0129065723500089 [IF=8]

140. A. Mobaien, R. Boostani, M. Mohammadi, and S. Sanei, “ERP detection based on smoothness priors” IEEE Transactions on Biomedical Engineering, 70(3), pp. 867-876, 2023, Doi. 10.1109/TBME.2022.3204506 (IF=5.04).

139. S Shirani, A Valentin, G Alarcon, F Kazi, S Sanei, "Response to the Discussion on S. Shirani, A. Valentin, G. Alarcon, F. Kazi and S. Sanei, Separating Inhibitory and Excitatory Responses of Epileptic Brain to Single-Pulse Electrical Stimulation, International Journal of Neural Systems, Vol. 3, No. 2 (2023) 2350008.

138. A. Zandbagleh, S. Mirzakuchaki, M. R. Daliri, P. Premkumar, Luis Carretie and S. Sanei, “Tensor factorization approach for ERP-based assessment of schizotypy in a novel auditory oddball task on perceived family stress,” Journal of Neural Engineering, 19 066028, 2022 10.1088/1741-2552/aca69f.

137. H. Azami, S. Sanei, and T. K. Rajji, “Ensemble entropy: A low bias approach for data analysis”, Journal of Knowledge-Based Systems, online: vol. 28 Nov. 2022, 109876, Doi. 10.1016/j.knosys.2022.109876.  (IF=8.038).

136. N. Goshtasbi, R. Boostani, and S. Sanei, “SleepFCN: A fully convolutional deep learning framework for sleep stage classification using single-channel electroencephalograms,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 30, pp. 2088-2096, 2022, 10.1109/tnsre.2022.3192988 (IF=3.8)

135. B. Abdi-Sargezeh, A. Valentin, G. Alarcon, D. Martin-Lopez, and S. Sanei, "Sparse common feature analysis for detection of interictal epileptiform discharges from scalp EEG using concurrent intracranial-scalp recordings," IEEE Access, vol. 10, pp. 49892-49904, doi. 10.1109/ACCESS.2022.3167433.

134. S. Hashemipour, R. Boostani, and S. Sanei, “Continuous scoring of depression from EEG signals via a hybrid of convolutional neural networks, IEEE Transactions on Neural Systems and Rehabilitation, vol. 30, 176-183, 2022, doi. 10.1109/TNSRE.2022.3143162.

133. A. Zandbagleh, S. Mirzakuchaki, M. R. Daliri, P. Premkumar, and S. Sanei, “Schizotypy assessment via evaluation of brain connectivity,” International Journal of Neural Systems, Vol. 32, No. 4 (2022) 2250013 (17 pages) [IF=8]

132. V. Vahidpour, A. Rastegarnia, A. Khalili, W. M. Bazzi, and S. Sanei, “Energy-efficient diffusion Kalman filtering for multi-agent networks in IoT" IEEE Internet of Things Journal, vol. 9, no. 8, 6277-6287, 2022. Doi. 10.1109/JIOT.2021.3111593 [IF=9.936].

131. Y. Pourasad, V. Vahidpour, A. Rastegarnia, P. Ghorbanzadeh, S. Sanei, “State estimation in linear dynamical systems by partial update Kalman filtering,” Circuits, Systems, and Signal Processing, 41 (2), 1188-1200, 2022, doi. 10.1007/s00034-021-01815-5. (IF=2.225).

130. H.-N. Costin and S. Sanei, “Intelligent Biosignal Processing in Wearable and Implantable Sensors, Biosensors; biosensors-1785189, Editorial, Accepted on June 8, 2022

129. B. Abdi-Sargezeh, A. Valentin, G. Alarcon, D. Martin-Lopez, and S. Sanei, “Higher-order tensor decomposition based scalp-to-intracranial EEG projection for detection of interictal epileptiform discharges,” Journal of Neural Engineering 18 (6), 066039, 2021, doi. 10.1088/1741-2552/ac3cc4.

128. M. Mahmoodi, B. Makkiabadi, M. Mahmoudi, and S. Sanei, “A new method for accurate detection of movement intention from single channel EEG for online BCI,” Computer Methods and Programs in Biomedicine Update, Available online 20 August 2021, 100027, 10.1016/j.cmpbup.2021.100027, [IF=5.428].

127. S. Afshar, R. Boostani, and S. Sanei, “A combinatorial deep learning structure for precise depth of anesthesia estimation from EEG Signals,” IEEE Journal of Biomedical and Health Informatics, vol. 25, issue 9, pp. 3408-3415, Doi, 10.1109/JBHI.2021.3068481, Apr. 26, 2021[IF=5.18].

126. B. Abdi-Sargezeh, A. Valentin, G. Alarcon, and S. Sanei, “Incorporating uncertainty in data labeling into automatic detection of interictal epileptiform discharges from concurrent scalp EEG via multi-way analysis,” International Journal of Neural Systems (IJNS), Vol. 31, Issue 08, Article No. 2150019, Year 2021, 10.1142/S0129065721500192. [IF=8].

125. D. Jarchi, J. Kaler, and S. Sanei, “Lameness detection in cows using hierarchical deep learning and synchrosqueezed wavelet transform,” IEEE Sensors Journal, vol. 21, Issue: 7, pp. 9349-9358, Apr. 2021 [IF=3.3].

124. A. Khalili, V. Vahidpour, A. Rastegarnia, and S. Sanei, “Partial diffusion Kalman filter with adaptive combiners" IEEE Transactions on Aerospace and Electronic Systems, vol. 57, no. 3, pp. 1972-1980, 2021, doi. 10.1109/TAES.2020.3046085.

123. B. Abdi-Sargezeh, S. Sanei, Advances in epilepsy monitoring by detection and analysis of brain epileptiform discharges., Psychology & Neuroscience, 15(4), 375–394, 2022.  

122. A. Khalili , V. Vahidpour, A. Rastegarnia, A. Farzamnia, K. Teo Tze Kin, and S. Sanei , “Coordinate-descent adaptation over Hamiltonian multi-agent networks,” Sensors 2021 Nov 20;21(22):7732.  doi: 10.3390/s21227732.

121. P. Modares-Haghighi, R. Boostani, M. Nami, and S. Sanei, “Quantification of pain severity using EEG-based functional connectivity,” Elsevier Journal of Biomedical Signal Processing and Control, Volume 69, August 2021, 102840. (IF=3.14).

120. S. Sanei, Editorial; A Multidisciplinary and Interdisciplinary Journal for a Wider Community Under a Pioneering Cross-disciplinary Research Leader, International Journal of Neural Systems (IJNS), Vol. 31, No. 03, 2103002 March 2021.

119. A. Pouradabi, A. Rastegarnia, S. Zandi, W. Bazzi and S. Sanei, “A class of diffusion proportionate subband adaptive filters for sparse system identification over distributed networks,” Springer Journal of Circuit, Systems, and Signal Processing, pp. 1-23, June 2021, doi. 10.1007/s00034-021-01766-x, (IF=2.225).

118. D. Jarchi, J. Andreu-Perez, M. Kiani, O. Vyšata, J. Kunchynka, A. Procházka, and S. Sanei, “Recognition of patient groups with sleep related disorder using bio-signal processing and deep learning,” Sensors, 20(9) 2594, 2020.

117. H. Giv, A. Khalili, A. Rastegarnia, and S. Sanei, “A robust adaptive estimation algorithm for Hamiltonian sensor networks,” IEEE Control Systems Letters 5 (4), 1243-1248, 2020.

116. V. Vahidpour, A. Khalili, A. Rastegarnia, W. Bazzi, and S. Sanei, “Variants of partial update augmented CLMS algorithm and their performance analysis,” IEEE Transactions on Signal Processing, vol. 68, no. 1, pp. 3146-3157, 2020 (doi: 10.1109/TSP.2020.2993938).

115. M. Latifi, A. Khalili, A. Rastegarnia, and S. Sanei, “A robust scalable demand-side management based on diffusion-ADMM strategy for smart grid,” IEEE Internet of Things (IoT) Journal, vol. 7, no. 4, pp. 3363-3377, DOI. 10.1109/JIOT.2020.2968539, 2020 (IF=9.52).

114. M. Latifi, A. Khalili, A. Rastegarnia, W. M. Bazzi, and S. Sanei, “A self-governed online energy management and trading for smart micro/nano-grids,” IEEE Transactions on Industrial, Electronics, vol. 67, issue 1, pp. 7484-7498, 2020, 10.1109/TIE.2019.2945280. (IF = 7.5).

113. V. Vahidpour, M. Latifi, A. Khalili, A. Rastegarnia, and S. Sanei, “Performance analysis of distributed Kalman filtering with partial diffusion over noisy network,” IEEE Transactions on Aerospace and Electronic Systems, 56(3) pp. 1767-1782, 2020, DoI: 10.1109/TAES.2019.2933961.

112. A. Prochazka, H. Charvatova, O. Vysata, D. Jarchi, and S. Sanei, “Discrimination of cycling patterns using accelerometric data and deep learning techniques", Journal of Neural Computing and Applications, 33:7603–7613, 2020. IF= 4.774 (Q1), DOI: 10.1007/s00521-020-05504-3. (IF = 4.77)

111. M. Latifi, A. Khalili, A. Rastegarnia, W. Bazzi, and S. Sanei, “Demand-Side management for smart grid via diffusion adaptation,” IET Smart Grid 3 (1), 69-82, 2020.

110. H. Azami, S. E. Arnold, S. Sanei, Z. Chang, G. Sapiro, J. Escudero, and A. S. Gupta, “Multiscale fluctuation-based dispersion entropy and its applications to neurological diseases,” IEEE Access, vol. 7, no. 1, pp. 68718-68733, Print ISSN: 2169-3536, 2019, DoI: 10.1109/ACCESS.2019.2918560.

109. M. Latifi, A. Khalili, A. Rastegarnia, and S. Sanei, “A Distributed game-theoretic demand response with multi-class appliance control in smart grid" Elsevier Journal of Applied Energy, Vol. 179, 2019, https://doi.org/10.1016/j.epsr.2019.105946 (IF > 8).

108. A. Rastegarnia, P. Malekian, A. Khalili, W. M. Bazzi, and S. Sanei, “Tracking analysis of minimum kernel risk-sensitive loss algorithm under general non-Gaussian noise,” IEEE Transactions on Circuits and Systems II, Vol 66, no. 7, pp. 1262-1266, 2019. DoI: 10.1109/TCSII.2018.2874969

107. V. Vahidpour, A. Rastegarnia, A. Khalili, and S. Sanei, “Partial diffusion Kalman filtering for distributed state estimation in multiagent networks,” IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 12, pp. 3839 – 3846, 2019, DoI 10.1109/TNNLS.2019.2899052 (IF=11.69).

106. A. Akbari, M. Trocan, S. Sanei, and B. Granado, “Joint sparse learning with nonlocal and local image priors for image error concealment," IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 8, pp. 2559 – 2574, 2019.

105. M. Latifi, A. Rastegarnia, A. Khalili, and S. Sanei, “Agent-based decentralized optimal charging strategy for plug-in electric vehicles” IEEE Transactions on Industrial Electronics, vol. 66, no. 5, pp. 3668-3680, 2019 DoI. 10.1109/TIE.2018.2853609 (IF = 7.5).

104. E. Eqlimi, B. Makkiabadi, N. Samadzadehaghdam, H. Khajehpour, F. Mohagheian,  and S. Sanei, “A novel underdetermined source recovery algorithm based on k-sparse component analysis, Springer Journal of Circuits, Systems, and Signal Processing, Part of Springer Nature, pp. 1-23, 2018 (https://doi.org/10.1007/s00034-018-0910-9) (IF=2).

103. A. Prochazka, T. Dostálová, M. Kašparová, O. Vyšata, H. Charvátová, and S. Sanei, “Augmented reality implementations in stomatology,” MDPI Journal of Applied Sciences, Special Issue on Augmented, Reality: Current Trends, Challenges and Prospects, Invited review paper, MDPI 2019. doi:10.3390/app9142929.

102. D. Mandic, P. Djuric, A. Cichocki, C. C. Took, S. Sanei, and L. Hanzo, “Quo Vadis ICASSP – Echoes of the 2019 International Conference on Acoustics, Speech, and Signal Processing, Brighton, UK, 2019; Signal Processing Meets Needs of Modern Humankind.” IEEE signal Processing Magazine, Vol. 36, No. 5, 01.09.2019.

101. M. Latifi, A. Khalili, A. Rastegarnia, and S. Sanei, “A Bayesian real-time electric vehicle charging strategy for mitigating renewable energy fluctuations, IEEE Transactions on Industrial Informatics, vol. 15, no. 5, pp. 2555-2568, DoI. 10.1109/TII.2018.2866267, May 2019 (IF= 7.38).

100. A. Antoniades, L. Spyrou, D. Martin-Lopez, A. Valentin, G. Alarcon, S. Sanei, and C. Cheong Took, “Deep neural architectures for mapping scalp to intracranial EEG,” International Journal of Neural Systems, 28(8):1850009, 2018, DOI. 10.1142/S0129065718500090, online (IF=7).

99. S. Monajemi, S. Sanei, and S.-H. Ong, “Information reliability in complex multitask networks,” Elsevier Journal of Future Generation Computer Systems, Special Issue on Measurements and Security of Complex Networks and Systems, vol. 83, pp. 485-495, 2018. https://doi.org/10.1016/j.future. 2017.07.023  (IF=3.9).

98. D. Jarchi, J. Pope, T. K. M. Lee, L. Tamjidi, and S. Sanei, “A review on accelerometry based gait analysis and emerging clinical applications,” IEEE Reviews in Biomedical Engineering, vol. 11, issue 1, pp. 177-194, 2018, DOI. 10.1109/RBME.2018.2807182.

97. Z. Yang, W.-K. Ling, R. Tao, L. K. Woo, and S. Sanei “Optimal design of orders of DFrFTs for sparse representations,” IET Signal Processing, Vol. 12, no. 8, pp. 1023-1033, 2018, DOI.  10.1049/iet-spr.2017.0283.

96. A. Prochazka, J. Kuchynka, O. Vysata, M. Schatz, M. Yadollahi, S. Sanei, and M. Valis, “Sleep Scoring using polysomnography data features,” Springer Journal of Signal, Image and Video Processing (SIVP), vol. 12, no. 6, pp. 1-9, 2018, DoI 10.1107/s11760-018-1252-6.

95. A. Antoniades, L. Spyrou, D. Martin-Lopez, A. Valentin, G. Alarcon, S. Sanei, and C. Cheong Took, “Detection of interictal discharges using convolutional neural networks from multichannel intracranial EEG”, IEEE Transactions Neural Systems and Rehabilitation Engineering, vol. 25, no. 12, pp. 2285-2294, 2017.

94. S. Monajemi, D. Jarchi, S. H. Ong, and S. Sanei, “Cooperative particle filtering for detection and tracking of ERP subcomponents from multichannel EEG,”  Journal of Entropy, Special Issue on Entropy and Electroencephalography, 2017, Entropy 2017, 19(5), 199; INVITED FEATURE PAPER. doi:10.3390/e19050199.

93. A. Khalili, A. Rastegarnia, and S. Sanei, “Performance analysis of incremental LMS over flat fading channels”, IEEE Transactions on Control of Network Systems, Vol. 4, Issue 3, pp. 489-498, 2017, DOI 10.1109/TCNS.2016.2516826.

92. S. Kouchaki and S. Sanei, “Tensor factorisation for narrowband single channel source decomposition” Elsevier Journal of the Franklin Institute, 354 (7), 3152-3169, 2017. DOI: 10.1016/j.jfranklin.2017.01.018 (IF > 3)

91. M. Latifi, A. Khalili, A. Rastegarnia, and S. Sanei, “Fully distributed demand response using adaptive diffusion Stackelberg algorithm,” IEEE Transactions on Industrial Informatics, vol. 13, no. 5, pp. 2291-2301, DOI: 10.1109/TII.2017.2703132, 2017. (IF=5.5)

90. V Vahidpour, A Rastegarnia, A Khalili, WM Bazzi, S Sanei, “Analysis of partial diffusion LMS for adaptive estimation over networks with noisy links,” IEEE Transactions on Network Science and Engineering 5 (2), 101-112, 2017. (IF=3.9)

89. V. Vahidpour, A. Rastegarnia, A. Khalili, and S. Sanei, “Analysis of partial diffusion RLS adaptation over noisy links”, IET Signal Processing, 11 (6) 749-757, 2017 (IF > 1.25)

88. A. Khalili, A. Rastegarnia, W. M. Bazzi, and S. Sanei, “Analysis of incremental augmented affine projection algorithm for distributed estimation of complex-valued signals,” Journal of Circuits, Systems & Signal Processing, 36 (1), 119-136, 2017 (IF > 1.65).

87. S. Wang, H. L. Tang, L. I. Al Turk, Y. Hu, S. Sanei, G. M. Saleh and T. Peto, “Localising micro-aneurisms in fundus images through singular spectrum analysis,” IEEE Transactions on Biomedical Engineering, vol. 64, no. 5,  pp. 990 - 1002, 2016.

86. S. Monajemi, K. Eftaxias, S.-H. Ong, and S. Sanei, “An informed multitask diffusion adaptation approach to study tremor in Parkinson’s disease,” IEEE Journal of Selected Topics in Signal Processing; Special Issue on Advanced Signal Processing in Brain Networks,  Volume: 10, Issue: 7 , pp. 1306-1314, 2016.

85. L. Spyrou, D. M. Lopez, G. Alarcon, A. Valentin, and S. Sanei, “Detection of intracranial signatures of interictal epileptiform discharges from concurrent scalp EEG,” International Journal of Neural Systems, IJNS's Vol. 26, Issue No. 04, 2016, DOI: 10.1142/S0129065716500167.

84. S. Enshaeifar, S. Kouchaki, C. Cheong Took, and S. Sanei, “Quaternion singular spectrum analysis of electroencephalogram with application to sleep analysis,” IEEE Transactions on Neural Systems & Rehabilitation Engineering, Vol. 24, no. 1, pp. 57 - 67 , 2016.

83. A. Khalili, A. Rastegarnia, and S. Sanei, “Tracking performance of incremental augmented complex least mean square adaptive network in the presence of model non-stationarity,” IET Signal Processing 10 (7), 798-804, 2016.

82. A. Khalili, A. Rastegarnia, and S. Sanei, “Quantised augmented complex least mean-square algorithm: derivation and performance,” Journal of Signal Processing, Vol. 121, Issue C, April 2016
Pages 54-59, 10.1016/j.sigpro.2015.10.034.

81. S. Mahvash Mohammadi, M. Ghavami, S. Kouchaki, and S. Sanei, “Improving time-frequency domain sleep EEG classification via singular spectrum analysis,” Journal of Neuroscience Methods, 2016, 273:96-106, August 2016, doi:10.1016/j.jneumeth.2016.08.008

80. M. R. Daliri and S. Sanei, “Introduction to the 6th special section on Advances in Biomedical Signal and Image Processing, and Biometrics,” Journal of Computers and Electrical Engineering, vol. 53, July 2016.

79. S. Enshaeifar, L. Spyrou, S. Sanei and C. C. Took, “A regularised EEG informed Kalman filtering algorithm,” Elsevier Journal of Biomedical Signal Processing and Control, Volume 25, Pages 196–200, March 2016. 10.1016/j.bspc.2015.11.005

78. L. Spyrou, S. Kouchaki, and S. Sanei, “Multiview classification and dimensionality reduction of EEG data through tensor factorisation,” Elsevier Journal of Signal Processing Systems, INVITED PAPER, pp. 1-12, 2016, DOI: 10.1007/s11265-016-1164-z.

77. A. Safaei, H. Tang, and S. Sanei, “Robust search-free car number plate localization incorporating hierarchical saliency,” Journal of Computer Science and Systems Biology, vol. 9, pp. 093–103, June 2016.

76. A. Safaei, H. L. Tang, and S. Sanei, “Real time search free multiple license plate recognition via likelihood estimation of saliency,” Elsevier Journal of Computers and Electrical Engineering, Vol. 56, Pages 15–29, 2016.

75. S. Kouchaki, S. Sanei, E. L. Arbon, and D.-J. Dijk, “Tensor based Singular Spectrum Analysis for Automatic Scoring of Sleep EEG,” IEEE Transactions on Neural Systems & Rehabilitation Engineering, Vol. 23, no. 1, pp. 1-9, Jan. 2015. doi.org/10.1109/TNSRE.2014.2329557.

74. S. Ferdowsi, V. Abolghasemi, and S. Sanei, “A new informed tensor factorization approach to EEG-fMRI fusion,” Journal of Neuroscience Methods,  254, pp. 27-35, 2015.

73. S. Kouchaki, K. Eftaxias, and S. Sanei, “An adaptive filtering approach using supervised SSA for identification of sleep stages from EEG,” Journal of Frontiers in Biomedical Technologies 1 (4), 233-239, 2015.

72. T. K. M. Lee, J. G. Lim, S. Sanei, and S. S. W. Gan, “Advances on singular spectrum analysis of rehabilitative assessment data,” Journal of Medical Imaging and Health Informatics, Volume 5, Number 2, April 2015, pp. 350-358(9).

71. V. Abolghasemi, S. Ferdowsi, and S. Sanei, “Fast and incoherent dictionary learning algorithms with application to fMRI,” Elsevier Journal of Signal, Image, and Video Processing (SIViP), 9 (1), 147-158, 2015.

70. A. Khalili, A. Rastegarnia, and S. Sanei, “An incremental LMS network with reduced communication delay", Journal of Signal, Image and Video processing (SIViP), 10 (4), pp. 769-775, DOI. 10.1007/s11760-015-0809-x, 2015.

69. A. Khalili, A. Rastegarnia, and S. Sanei, “Robust frequency estimation in three-phase power systems using correntropy-based adaptive filter,” IET Journal of Science, Measurement & Technology, vol. 9, issue 8, pp. 928-935,  2015, DOI: 10.1049/iet-smt.2015.0018.

68. S. Sanei, S. Smaragdis, A. TS Ho, A. Nandi, and J. Larsen, “Guest Editorial: Machine Learning for Signal Processing,” Journal of Signal Processing Systems, Vol. 79, pp 113-116, 2015, (DOI) 10.1007/s11265-015-0973-9.

67. S. Ferdowsi, S. Sanei, and V. Abolghasemi, “A predictive modeling approach to analyze data in EEG–fMRI experiments,” International Journal of Neural Systems, vol. 25, no. 1, 15 pages, 08/2014 DOI: 10.1142/S0129065714400085, (IF = 7.2).

66. H. Azami, H. Hassanpour, J. Escudero, and S. Sanei, “An intelligent approach for variable size segmentation of non-stationary signals,” Elsevier Journal of Advanced Research, vol. 6, pp. 687–698, 2014, DOI: 10.1016/j.jare.2014.03.004 (IF=5).

65. H. Azami, J. Escudero, Ali Darzi, and S. Sanei, “Extracellular spike detection from multiple electrode array using novel intelligent filter and ensemble fuzzy decision making,” Elsevier Journal of Neuroscience Methods, 2015 Jan 15; vol. 239, pp.129-138. doi: 10.1016/j.jneumeth.2014.10.006. Epub  Oct 18, 2014 (IF=2.8).

64. M. R. Daliri and S. Sanei, “Introduction to the special issue on Advances in Biomedical Signal and Image Processing, and Biometrics,” Computers & Electrical Engineering 40(5):1714-1716 01 Jul 2014.

63. M. Azarbad, H. Azami, S. Sanei and A. Ebrahimzadeh, “New Neural Network-based Approaches for GPS GDOP Classification based on Neuro-Fuzzy Inference System, Radial Basis Function, and Improved Bee Algorithm,” Journal of Applied Soft Computing, V. 25, Pages 285–292, 2014.

62. A. Khalili, W. Bazzi, A. Rastegar, and S. Sanei "Analysis of cooperation gain for adaptive networks in different communication scenarios."  Journal of Electronics and Communications, 2014, doi.org/ 10.1016/j.aeue.2014.03.014.

61. H. Azami and S. Sanei, “Spike detection approaches for noisy neuronal data; assessment and comparison,” Journal of Neurocomputing, Volume 133, 10, pp. 491–506,  2014 (IF=3.317).

60. T. K. M. Lee, M. Belkhatir and S. Sanei, “A comprehensive review of past and present vision-based techniques for gait recognition,” Springer Journal of Multimedia Tools and Applications, vol. 72, pp. 2833–2869, 2014, doi.10.1007/s11042-013-1574-x.

59. S. Sanei, S. Ferdowsi, K. Nazarpour, and A. Cichocki, “Advances in Electroencephalography Signal Processing,” IEEE Signal Processing Magazine, vol. 30, no. 1, pp. 170 – 176, 2013.

58. S. Ferdowsi, V. Abolghasemi, and S. Sanei, “Removing balistocardiogram artifact from EEG using short-and-long-term linear predictor,” IEEE Transactions on Biomedical Engineering, vol. 60, no. 7, pp. 1900-1911, April 2013.

57. H. Azami and S. Sanei, “GPS GDOP classification via improved neural network trainings and principal component analysis,” International Journal of Electronic, 2013 (Editor Prof. Ian Hunter, University of Leeds, UK) ID: 832390 doi:10.1080/00207217.2013.832390.

56. H. Azami, M. Malekzadeh, S. Sanei and A. Khosravi,  “Optimization of orthogonal polyphase coding waveform for MIMO radar based on evolutionary algorithms,” Journal of mathematics and computer Science, issue 6, pp. 146 – 153, 2013.

55. M. Azarbad, H. Azami, S. Sanei, “A time-frequency approach for EEG signal segmentation,” (Iranian) Journal of AI and Data Mining, 2013.

54. H. Azami, M. Malekzadeh, and S. Sanei, “A new neural network approach for face recognition based on conjugate gradient algorithms and principal component analysis,” Journal of Mathematics and Computer Science, vol. 6, pp. 166-175, 2013.

53. H. Azami, S. Sanei, K. Mohammadi and H. Hassanpour, “A hybrid evolutionary approach to segmentation of non-stationary Signals,” Elsevier Journal of Digital Signal Processing, Volume 23, Issue 4, July 2013, Pages 1103-1114,  March 2013.

52. V. Abolghasemi, S. Ferdowsi, and S. Sanei, “Blind separation of image sources via adaptive dictionary learning,” IEEE Transactions on Image Processing, vol. 21, no. 6, pp. 2921 - 2930, 2012.

51. S. Sanei, T. K. M. Lee, and V. Abolghasemi, “A new adaptive line enhancer based on singular spectrum analysis,” IEEE Transactions on Biomedical Engineering, vol. 59, no. 2, pp. 428-434, 2012.

50. P. Ahmadian, S. Sanei, L. Ascari, L. Gonz´alez-Villanueva, M. A. Umilt, “Constrained blind source extraction of readiness potentials from EEG,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol.:21, no. 4, pp. 567-575, 2012.

49. V Abolghasemi, S Ferdowsi, S Sanei, “A gradient-based alternating minimization approach for optimization of the measurement matrix in compressive sensing,” Signal Processing, 92(4), 999-1009. 2012.

48. H. Azami, Mousavi, and S. Sanei, “Classification of GPS satellites using improved Back propagation training algorithms," Springer Journal of Wireless Personal Communications, vol. 71, no. 2, pp. 789-803 Jul 2013 DOI 10.1007/s11277-012-0844-7, 2012.

47. M. Azarbad, H. Azami, S. Sanei, “A time-frequency approach for EEG signal segmentation,” Journal of Signal and Information Processing, Issue 3, pp. 39-44, 2012, doi:10.4236/jsip.2012.3100646.

46. F. Marvasti, A. Amini, F. Haddadi, M. Soltanolkotabi, B. H. Khalaj, A. Aldroubi, S. Sanei, and J. Chambers, “A Unified Approach to Sparse Signal Processing,” EURASIP Journal on Advances in Signal Processing 2012, 2012:44 doi:10.1186/1687-6180-2012-44.

45. F. Ghaderi, H. Mohseni, and S. Sanei, “Localizing heart sounds in respiratory signals using singular spectrum analysis,” IEEE Transactions on Biomedical Engineering, vol. 59, no. 12, pp. 3360-3367, 2011.

44. D. Jarchi, S. Sanei, J. C. Principe, and B. Makkiabadi, “A new spatiotemporal filtering method for single-trial ERP subcomponent estimation,” IEEE Transactions on Biomedical Engineering, vol. 58, No. 1, pp. 132-143, Jan. 2011 (TOP ACCESSED PAPER).

43. S. Sanei, M. Ghodsi, and H. Hassani, “A constrained singular spectrum analysis approach to murmur detection from heart sounds,” Elsevier Journal of Medical Engineering and Physics, Vol. 33, Issue 3, PP. 362-367, 2011.

42. F. Babiloni, A. Cichocki, S. Sanei, L. Astolfi, F. Cincotti, and S. Gonzalez Andino, “Selected Papers from the 4th International Conference on Bioinspired Systems and Cognitive Signal Processing,” Computational Intelligence and Neuroscience, Vol. 2011 (2011), Article ID 913040, doi:10.1155/2011/913040.

41. H. Azami, S. Sanei, and K. Mohammadi, “A novel signal segmentation method based on standard deviation and variable threshold,” Journal of Computer Applications, vol. 34, no. 2, pp. 27-34, 2011.

40. H. Azami, S. Sanei, and K. Mohammadi, “Improving the neural network training for face recognition using adaptive learning rate, resilient back-propagation and conjugate gradient algorithm,”  Journal of Computer Applications, vol. 34, no. 2, pp. 22-26, 2011.

39. J. Escudero, S. Sanei, D. Jarchi, D. Ab´asolo, and R. Hornero, “Regional coherence evaluation in mild cognitive impairment and Alzheimer’s disease based on adaptively extracted magnetoencephalogram rhythms,” Journal of Physiological Measurements, vol. 32, no. 8, pp. 1163-1180, Aug. 2011. DOI: 10.1088/0967-3334/32/8/011.

38. T. K. M. Lee, S. Sanei, and M. Belkhatir, “Combining biometrics derived from different classes of nonlinear analyses of fronto-normal gait signals,” IARIA International Journal of Advances on Networks and Services, Vol. 4, No. 1&2, pp. 232-243, 2011.

37. D. Jarchi, S. Sanei, and M. M. Lorist, “Coupled particle filtering: a new approach for P300-based analysis of mental fatigue,” Journal of Biomedical Signal Processing and control, vol. 6, no. 2, p. 175-185 2011. DOI: doi:10.1016/j.bspc.2010.09.001.

36. F. Ghaderi, S. Sanei, K. Nazarpour, and J. McWhirter “Removal of ballistocardiogram artifacts from EEG/fMRI data using cyclostationary source extraction method,” IEEE Transactions on Biomedical Engineering, vol. 57, no. 11, pp. 2667-2676, 2010.

35. H. R. Mohseni, E. Wilding, and S. Sanei, “Variational Bayes for spatiotemporal identification of event-related potential subcomponents,” IEEE Transactions on Biomedical Engineering, vol. 57, no. 10, 2413 – 2428, Oct. 2010.

34. M. Ghodsi, H. Hassani, and S. Sanei, “Extracting foetal heart signal from noisy maternal ECG by singular spectrum analysis,” Journal of Statistics and its Interface, Special Issue on the Application of SSA, Vol. 3, pp. 399–411, 2010 (INVITED PAPER).

33. M. Ghodsi and S. Sanei, “Support vector machines for classification of temporomandibular disorders from facial pattern,” Journal of Computer Methods and Programs in Biomedicine, vol. 3, issue 6, pp. 1-13, 2010.

32. K. Nazarpour, P. Praamstra, R. C. Miall, and S. Sanei, “Steady-state movement related potentials for brain computer interfacing” IEEE Transactions Biomedical Engineering, vol. 56, no. 8, pp. 2104-2113, Aug. 2009.

31. T. Tsalaile, R. Sameni, S. Sanei, C. Jutten, and J. Chambers, “Sequential blind source extraction for quasi-periodic signals with time-varying period,” IEEE Transactions on Biomedical Engineering, Vol. 56, No. 3,  pp. 646-655, 2009.

30. Z. He, A. Cichocki, Y. Li, S. Xie, and S. Sanei, “K-hyperline clustering learning for sparse component analysis,” Journal of Signal Processing, vol. 89, Issue 6, Pages 1011-1022, June 2009.

29. H. R. Mohseni, K. Nazarpour, E. Wilding, and S. Sanei, “Application of particle filters in single trial event-related potential estimation,” Journal of Physiological Measurement, Vol. 30, pp. 1011–1016, 2009.

28. J.-L. Lo, K. Nazarpour, and S. Sanei, “A new adaptive source-channel coding for progressive transmission of medical images,” EUSASIP Journal of Telemedicine and Applications, Volume 2009, Article ID 519417, 12 pages, doi:10.1155/2009/519417.

27. D. Jarchi, R. Boostani, M. Taheri, and S. Sanei, “Seizure source localization using a hybrid second order blind identification and a new clustering technique", Elsevier Journal of Biomedical Signal Processing and Control, Volume 4, Issue 2, Pages 108-117, April 2009.

26. L. Spyrou and S. Sanei “Source localisation of event related potentials incorporating spatial notch filters,” IEEE Transactions on Biomedical Engineering, vol. 55, no. 9, pp. 2232-2239, Sept 2008.

25. C. Chong Took, S. Sanei, J. Chambers, S. Rickard, and S. Dunne, “Fractional delay estimation for blind source separation and localization of temporomandibular joint sounds,” IEEE Transactions on Biomedical Engineering, Vol. 55, no. 3, pp. 949-956, 2008.

24. K. Nazarpour, Y. Wangsawat, S. Sanei, J. A. Chambers, and S. Oraintara, "Removal of the eye-blink artifacts from EEGs via STF-TS modeling and robust minimum variance beamforming,” IEEE Transactions on Biomedical Engineering, vol. 55, no. 9, pp. 2221-2231, Sept 2008.

23. K. Nazarpour, H. R. Mohseni, C. Hesse, J. A. Chambers and S. Sanei, “A novel semi-blind signal extraction approach incorporating PARAFAC for the removal of eye-blink artifact from EEGs, “EURASIP Journal on Advances in Signal Processing,” vol. 2008, Article ID 857459, 12 pages, 2008. doi:10.1155/2008/857459.

22. W. Wang, Y. Luo, J. Chambers, and S. Sanei, “Note onset detection via non-negative spectrum factorization,” EURASIP Journal on Advances in Signal Processing Vol. 2008, Article ID 231367, 15 pages doi:10.1155/2008/231367, 2008.

21. A. Cichocki and S. Sanei, “EEG/EMG Signal Processing,” EURASIP J. Computational Neuroscience, published online, Feb. 12, 2008, doi: 115/2007/97026.

20. T. K. M. Lee, M. Belkhatir, P. A. Lee and S. Sanei, “Nonlinear characterisation of fronto-normal gait for human recognition,” Advances in Multimedia Information Processing - PCM 2008, Lecture Notes in Computer Science, pp. 466-475, ISBN: 978-3-540-89795-8.

19. M. Ghodsi, H. Hassani, S. Sanei, and Y. Hicks, “The use of noise information for detection of temporo-mandibular disorder,” Elsevier Journal of Biomedical Signal Processing and Control, 4 (2) (2008) 79 ISSN 17468094.

18. C. Cheong Took and S. Sanei, “Exploiting sparsity, sparseness, and super-Gaussianity in underdetermind blind identification of temporomandibular joint sounds,” (INVITED PAPER) Journal of Computers, Vol. 2, Issue 6, pp.65-71, 2007.

17. M. Jing and S. Sanei, “A Novel constrained Topographic ICA for separation of epileptic seizure signals,” EURASIP Journal of Computational Intelligence and Neuroscience, Published online 2007 August 6. doi: 10.1155/2007/21315 2007, ISSN:1687-5265.

16. Z. Zhang, J. A. Chambers, S. Sanei, P. Kendrick, and T. J. Cox, 'A new variable tap-length LMS algorithm to model an exponential decay impulse response,' IEEE Signal Processing Letters, vol. 14, no. 4, pp. 263-266, 2007.

15. M. A. Latif, S. Sanei, J. Chambers, and L. Spyrou, 'Partially constrained blind source separation for localization of unknown sources exploiting non-homogeneity of the head tissues,' Journal of VLSI  Signal Processing Systems,' vol. 49, pp. 217-232, 2007.

14. L. Spyrou, Min Jing, S. Sanei, and A. Sumich, “Separation and localisation of P300 sources and the subcomponents using constrained blind source separation,” EURASIP Journal on Advances in Signal Processing, vol. 2007, paper ID: 82912, pp. 1-10, 2007.

13. M. A. Latif, S. Sanei, and J. Chambers, 'Localization of abnormal EEG sources using blind source separation partially constrained by the locations of known sources, “IEEE, Signal Processing Letters, vol. 13, no. 3, pp. 117-120, March 2006.

12. C. Cheong, S. Sanei, J. Chambers, and S. Dunne, “Underdetermined blind source separation of temporomandibular joint sounds,” IEEE Transactions on Biomedical Engineering, vol. 53, no. 10, pp. 2123- 2126, Oct. 2006.

11. J. Corsini, L. Shoker, S. Sanei, and G. Alarcon, “Epileptic seizure predictability from scalp EEG incorporating BSS,” IEEE, Transactions on Biomedical Engineering, vol. 53, no. 5, pp. 790 – 799, May 2006.

10. L. Shoker, S. Sanei, and J. Chambers, “Artifact removal from electroencephalograms using a hybrid BSS-SVM algorithm,” IEEE Signal Processing Letters, Vol.12, No.10, pp. 721-724, 2005.

9. W. Wang, S. Sanei, and J.A. Chambers, Penalty function based joint diagonalization approach for convolutive blind separation of nonstationary sources, IEEE Transactions on Signal Processing, Vol. 53(5), pp. 1654-1669, 2005.    

8. W. Wang, J. Chambers, and S. Sanei, “A novel hybrid approach to permutation problem of frequency domain blind source separation,” Lecture Notes in Computer Science, vol. 3195, pp. 532-539, Springer, 2004.

7. L. Shoker, S. Sanei, W. Wang, and J. Chambers, “Removal of eye blinking artifact from EEG incorporating a new constrained BSS algorithm,” IEE Journal of Medical and Biological Engineering and Computing, pp. 290-295, 2004.

6. S. Sanei “Texture segmentation using semi-supervised support vector machines" International Journal of Computational Intelligence and Applications, vol. 4, No. 2, pp. 131-142, 2004.

5. W. Wang, M. G. Jafari, S. Sanei, and J. A. Chambers, “Blind Separation of convolutive mixtures of cyclostationary signals”, IEEE Int. Journal of Adaptive Control and Signal Processing, pp. 172-188, Feb. 2004.

4. S. Sanei and S.-H. Ong, “Reconstruction of electroencephalogram brain map by incorporating blind source separation concept”, Journal of Digital Imaging, Vol.13, Supplementary Issue, No. 1, pp. 230-232, vol. 13, May 2000.

3. S. Sanei, P. Sanaei, and M. Zahabsaniei, “Cephalogram analysis applying template matching and fuzzy logic”, Journal of Image & Vision Computing, vol.18, pp. 39-48, 1999. 

2. S. Sanei and T. K. M. Lee, “blood cell identification using shortest spanning tree image segmentation,” Journal of Image and Vision Computing, vol. 6, pp.122-131, 1996.

1. S. Sanei, R. Benjamin, and R. I. Kitney, “Variable rate and size transform coding of medical images,” Journal of Digital Imaging, vol. 4, pp. 18-27, 1993.