> Journal Papers 

Transportation Analytics

  • A. Prokhorchuk, J. Dauwels, P. Jaillet, "Estimating Travel Time Distributions by Bayesian Network Inference", IEEE Transactions on Intelligent Transportation Systems, March 2019 (IF 5.744) PDF

  • B. Ghosh,M.T. Asif, J. Dauwels,U. Fastenrath,H. Guo, "Dynamic Prediction of the Incident Duration Using Adaptive Feature Set", IEEE Transactions on Intelligent Transportation Systems, Nov 2018 PDF (5.744)

  • N. Mitrovic, A. Narayanan, T. Asif, A. Rauf, J. Dauwels, and P. Jaillet, "On Centralized and Decentralized Architectures for Traffic Applications," IEEE Transactions on Intelligent Transportation Systems, Jul 2016, Volume: 17, Issue: 7, Pages: 1988 - 1997, DOI: 10.1109/TITS.2016.2519922.    PDF

  • T. Asif, N. Mitrovic, J. Dauwels, P. Jaillet, “Matrix and Tensor based Methods for Missing Data Estimation in Large Traffic Networks,” IEEE Transactions on Intelligent Transportation Systems, Jul 2016, Volume: 17, Issue: 7 Pages: 1816 - 1825, DOI: 10.1109/TITS.2015.2507259.    PDF

  • N. Mitrovic, T. Asif, J. Dauwels, P. Jaillet, “Low-dimensional Models for Compression, Compressed Sensing, and Prediction of Large-Scale Traffic Data,” IEEE Transactions on Intelligent Transportation Systems, Oct 2015, Volume: 16, Issue: 5, Pages: 2949 - 2954, DOI: 10.1109/TITS.2015.2411675 (IF: 3.064).    PDF

  • T. Asif, N. Mitrovic, J. Dauwels, P. Jaillet, “Near-Lossless Compression for Large Traffic Networks,” IEEE Transactions on Intelligent Transportation Systems,  Aug 2015, Volume: 16, Issue: 4 Pages: 1817 - 1826, DOI: 10.1109/TITS.2014.2374335 (IF: 3.064).    PDF


  • T. Asif, J. Dauwels, C.Y. Goh, A. Oran, E. Fathi, M. Xu, M.M. Dhanya, N. Mitrovic, and P. Jaillet, "Spatiotemporal Patterns in Large-Scale Traffic Speed Prediction," IEEE Transactions on Intelligent Transportation Systems,  Apr 2014, vol. 15:2, pp.794-804, (IF: 3.064).    PDF  ​ 

Graphical Models​​

  • H. Yu, W. I. Uy, and J. Dauwels, “Modeling Spatial Extremes via Ensemble-of-Trees of Pairwise Copulas,” IEEE Transactions on Signal Processing, Feb 2017, Volume: 65, Issue: 3, Pages: 571 - 586, DOI: 10.1109/TSP.2016.2614485 (IF: 2.813).    PDF​

  • H. Yu and J. Dauwels, “Modeling Spatio-Temporal Extreme Events using Graphical Models,” IEEE Transactions on Signal Processing, Mar 2016, Volume: 64, Issue: 5, Pages: 1101 - 1116, DOI: 10.1109/TSP.2015.2491882 (IF: 2.813). PDF

  • J. Lui, D. Liu, J. Dauwels, and H.S. Seah, “3D Human Motion Tracking by Exemplar-based Conditional Particle Filter,” Signal Processing, May 2015, vol. 110, pp.164-177 (IF: 2.238).    PDF 

  • H. Yu, J. Dauwels, and P. Jonathan, “Extreme-Value Graphical Models with Multiple Covariates,” IEEE Trans Signal Processing, Nov 2014, vol. 62:21, pp. 5734 - 5747 (IF: 2.813).    PDF 

  • B. Kurkoski and J. Dauwels, “Reduced-Memory Decoding of Low-Density Lattice Codes,” IEEE Comms Letters, Jul 2010, vol. 14:7, pp. 659 – 661. (IF: 2.1).    PDF 

  • B. Kurkoski and J. Dauwels, "Iterative decoding of lattice codes using Gaussian mixtures," EEE Communications Letters, vol. 14, no. 5, May 2010.

  • J. Dauwels and H.A. Loeliger, “Computing information rates of continuous channels with memory by particle methods,” IEEE Transactions on Information Theory, Jan 2008, vol. 54:1, pp. 406-409. (IF: 2.25).    PDF 

  • H.-A. Loeliger, J. Dauwels, J. Hu, P. Li, S. Korl, and F. Kschischang, “The factor graph approach to model-based signal processing,” Proc. of the IEEE, Jun 2007, vol. 95:6, pp. 1295-1322 (invited)  (IF:3.34).    PDF 

  • B. Vigoda, J. Dauwels, M. Frey, N. Gershenfeld, T. Koch, H.A. Loeliger, and P. Merkli, “Synchronization of pseudo-random signals by forward-only message passing with application to electronic circuits,” IEEE Trans. Inform. Theory, Aug 2006, vol. 52:8, pp. 3843–3852.  (IF: 2.25).    PDF

Computational Neuroscience & Neural Signal Processing

  • E. Bagheri, J. Jin, J. Dauwels, S. Cash, M.B. Westover, "A Fast Machine Learning Approach to Facilitate the Detection of Interictal Epileptiform Discharges in the Scalp Electroencephalogram", Journal of neuroscience methods, July 2019 , Volume 326, pp. 108362 (IF 2.668)

  • Z. Tu, H. Li, D. Zhang, J. Dauwels, B. Li, J. Yuan, "Action-Stage Emphasized Spatiotemporal VLAD for Video Action Recognition", IEEE Transactions on Image Processing,  Volume: 28 , Issue: 6 , June 2019​ (IF 5.081)

  • Y. Tahir, Z. Yang, D. Chakraborty, N. Thalmann, D. Thalmann, Y. Maniam, B.L. Tan, J Lee, C. Keong, J. Dauwels, "Non-verbal speech cues as objective measures for negative symptoms in patients with schizophrenia", PloS one, April 2019, Volume 14, Issue 4, pp. e0214314 (IF 2.776)


  • N. Sinha, Y. Wang, J. Dauwels, M. Kaiser, T. Thesen, T. Thesen, R. Forsyth, P.N. Taylor, "Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy", NeuroImage: Clinical,  January 2019, Volume 21, pp. 101655  (IF 3.943)

  • K.R. Wan, T. Maszczyk, A.A.Q. See, J. Dauwels, N.K.K. King, "A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson’s disease", Clinical Neurophysiology, January 2019, Volume 130, Issue 1, pp. 145 - 154 (IF 3.675)​​

  • Z. Yang, N. A. A. Rashid, Y. F. Quek, M. Lam, Y. M. See, Y. Maniam, J. Dauwels, B. L. Tan, J. C. K. Lee, "Montreal Cognitive Assessment as a screening instrument for cognitive impairments in schizophrenia", Schizophrenia Research, March 2018, vol. 199, pp. 58-63, doi: 10.1016/j.schres.2018.03.008 (IF: 3.958).  

  • E. Bagheri, J. Dauwels, B. C. Dean, C. G. Waters, M. B. Westover, J. J. Halford, "Interictal epileptiform discharge characteristics underlying expert interrater agreement", Clinical Neurophysiology, October 2017, vol. 128:10, pp. 1994-2005, doi: 10.1016/j.clinph.2017.06.252 (IF: 3.614). 

  • N. Sinha, J. Dauwels, M. Kaiser, S. S. Cash, M. B. Westover, Y. Wang, P. N. Taylor, "Reply: Computer models to inform epilepsy surgery strategies: prediction of postoperative outcome", Brain, A Journal of Neurology, March 2017, doi: 10.1093/brain/awx068 (IF: 10.840). 

  • J. Jing, J. Dauwels, T. Rakthanmanon, E. Keogh, S.S. Cash, M.B. Westover, “Rapid annotation of interictal epileptiform discharges via template matching under Dynamic Time Warping,” Journal of Neuroscience Methods, Volume 274, Dec 2016, pp. 179-190.    PDF

  • N. Sinha, J. Dauwels,  M. Kaiser, S. S. Cash, M. B. Westover, Y. Wang, and P. N. Taylor, “Predicting neurosurgical outcomes in focal epilepsy patients using computational modelling,” Brain, 23 Dec 2016, vol. 140 (2), pp. 319-332,  (IF: 10.103).    PDF

       https://academic.oup.com/brain/article/doi/10.1093/brain/aww299/2736496/Predicting-neurosurgical-outcomes-        in-focal    (OPEN Access)

  • D. Menon, J. Dauwels, A.C.H. Chan, "Effect of Subliminal Lexical Priming on the Subjective Perception of Images: a Machine Learning Approach," PLoS ONE, Feb 2016, 11(2):e0148332, doi: 10.1371/journal.pone.0148332, (IF: 3.234).    PDF

       http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0148332   (PLOS ONE Access)

  • E. Gallego-Jutglà, J. Solé-Casals, F. Vialatte, J. Dauwels, A. Cichocki,  “EEG based index for early diagnosis of Alzheimer's disease,” Journal of Alzheimer's Disease, Jul 2015, vol. 43:4, pp. 1175-84, 2015 (IF: 4.17).    PDF

      http://journal.frontiersin.org/article/10.3389/fnins.2015.00202/full  (FRONTIERS Access)

  • C. Laske, H. R. Sohrabi, S. M. Frost, K. López-de-Ipiña, P. Garrard, M. Buscema, J. Dauwels, S. R. Soekadarl, S. Mueller, C. Linnemann, S. Bridenbaugh, Y. Kanagasingam, R. N. Martins, S. E. O'Bryant, “Innovative diagnostic tools for early detection of Alzheimer’s disease,” Alzheimer & Dementia, May 2015, vol. 11:5, pp. 561-78 (IF: 17.472).    PDF 

  • J. Sole-Casals, F. Vialatte, and J. Dauwels, “Alternative Techniques of Neural Signal Processing in Neuroengineering,” Cognitive Computation, Feb 2015, vol. 7:1, pp 1-2. (IF: 1.67).    PDF

  • E. Gallego-Jutglà, J. Solé-Casals, F. Vialatte, M. Elgendi, A. Cichocki, and J. Dauwels, “A hybrid feature selection approach for the early diagnosis of Alzheimer’s disease,” Journal of Neural Engineering, Feb 2015, vol. 12:1, 016018. doi: 10.1088/1741-2560/12/1/016018 (IF: 3.415).    PDF

  • P. Taylor, Y. Wang, M. Goodfellow, J. Dauwels, F. Moeller, U. Stephani, G. Baier, “A computational study of stimulus driven epileptic seizure abatement,” PLoS ONE, Dec 2014, vol. 9:12 (IF: 3.534).    PDF

       http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0114316   (PLOS ONE Access)

  • P. Taylor, M. Kaiser, J. Dauwels, “Structural connectivity based whole brain modelling in epilepsy,” Journal Neuroscience Methods, Oct 2014, vol. 236, pp. 51-57 (invited) (IF: 2.114).    PDF 

  • J. Dauwels, K. Srinivasan, M. Ramasubba, and A. Cichocki, “Near-lossless multi-channel EEG compression based on matrix and tensor decompositions,” IEEE J Biomed Health Inform., May 2013, vol.17:3, pp. 708-714 (IF: 1.939).   PDF

  • K. Srinivasan, J. Dauwels, M. Ramasubba, “Multichannel EEG compression: Wavelet-based image and volumetric coding approach,” IEEE J Biomed Health Inform., Jan 2013, vol. 17:1, pp.113-20 (IF: 1.939).    PDF

  • F. Vialatte, J. Dauwels, T. Musha, A. Cichocki, "Audio representations of multi-channel EEG: a new tool for diagnosis of brain disorders," American Journal of Neurodegenerative Disease, Nov 2012, vol.1:3, pp. 292-304.    PDF

  • J. Dauwels and K. Srinivasan, “Diagnosis of Alzheimer’s Disease Using Electric Signals of the Brain: A Grand Challenge,” Asia Pacific Biotech News, Oct – Nov  2012, vol. 16:10-11.    PDF

  • J. Dauwels, T. Weber, F. Vialatte, and A. Cichocki, “Quantifying Statistical Interdependence—Part III: N > 2 Point Processes,” Neural Computation, Feb 2012, vol. 24:2, pp. 408–454. (IF: 2.335).    PDF 

  • K. Srinivasan, J. Dauwels, and M. Ramasubba, "A two-dimensional approach for lossless EEG compression," Biomedical Signal Processing and Control, Volume 6, Issue 4, Oct 2011, Pages 387-394.    PDF  

  • F. Vialatte, J. Dauwels, M. Maurice, and A. Cichocki, "Improving the specificity of EEG for diagnosing Alzheimer's disease," International Journal of Alzheimer's Disease, (invited paper), Volume 2011, Article ID 259069, 7 pages, Mar 2011, doi:10.4061/2011/259069.    PDF 

  • J. Dauwels,  K. Srinivasan, M. Ramasubba, T. Musha, F.Vialatte, C. Latchoumane, J. Jeong, A. Cichocki, "Slowing and loss of complexity in Alzheimer's EEG: Two sides of the same coin?,"  International Journal of Alzheimer's Disease, (invited paper), Volume 2011, Article ID 539621, Feb 2011, doi:10.4061/2011/539621.    PDF

  • J. Dauwels, F Vialatte, and A Cichocki, “Early Diagnosis of Alzheimer’s Disease from EEG Signals: Where Are We Standing?,” Current Alzheimer’s Research, Sep 2010, vol. 7:6, pp. 487-505 (invited) (IF: 4.971).    PDF

  • F. Vialatte, M. Maurice, J. Dauwels, and A. Cichocki, “Steady-state visually evoked potentials: focus on essential paradigms and future perspectives,” Progress in Neurobiology, Apr 2010, vol. 90:4, pp. 418-438 (invited). (IF: 9.992).    PDF​

  • J. Dauwels, F. Vialatte, T. Musha, A. Cichocki,  “A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG,” Neuroimage, Jan 2010, vol. 49:1, pp. 668-693 (IF: 7.168).    PDF 

  • F. Vialatte, J. Dauwels, M. Maurice, and A. Cichocki, "Steady-state visually evoked potentials: time-frequency analysis and oscillatory event synchrony," Cognitive Neurodynamics, Sep 2009, 3(3):251-261.    PDF


  • F. Vialatte, J. Dauwels, M. Maurice, and A. Cichocki, “On the synchrony of steady state visual evoked potentials and oscillatory burst events,” Cognitive Neurodynamics, Sep 2009, vol. 3:3, pp. 251-261. (IF: 1.67).    PDF

  • J. Dauwels, F. Vialatte, T. Weber, and A. Cichocki, “Quantifying Statistical Interdependence by Message Passing on Graphs—Part II: Multidimensional Point Processes,” Neural Computation, Aug 2009, vol. 21:8, pp. 2203-2268. (IF: 2.335)  Selected for cover image.    PDF 

  • J. Dauwels, F. Vialatte, T. Weber, and A. Cichocki, “Quantifying Statistical Interdependence by Message Passing on Graphs—Part I: One-Dimensional Point Processes,” Neural Computation, Aug 2009, vol. 21:8, pp. 2152–2202.  (IF: 2.335).   PDF ​

  • F. Vialatte, J. Solé-Casals, J. Dauwels, M. Maurice, and A. Cichocki, “Bump Time-Frequency Toolbox: a Toolbox for Time-Frequency Oscillatory Bursts Extraction in Electrophysiological Signals,” BMC Neuroscience, May 2009, vol. 10:46. (IF: 2.67).    PDF

  • F. Vialatte, J. Dauwels, T. Rutkowski, and A. Cichocki, "Oscillatory Event Synchrony during Steady State Visually Evoked Potentials," Advances in Cognitive Neurodynamics, Springer, Oct 2008 (invited paper), pp 439-442. 


  • J. Dauwels, F. Vialatte, T. Rutkowski, and A. Cichocki, "Measuring Neural Synchrony by Message Passing, In Advances in Neural Information Processing Systems 20," NIPS 2007, Vancouver, British Columbia, Canada — Dec 03 - 06, 2007, Edited by J Platt, D Koller, Y Singer, S Roweis, Cambridge, MA: MIT Press 2008:361-368.    PDF  


Computational Biology and Biostatistics

  • M. Wang, L.L.S. Ong, J. Dauwels, H. H. Asada, "Multicell migration tracking within angiogenic networks by deep learning-based segmentation and augmented Bayesian filtering", Journal of Medical Imaging, June 2018,  Volume: 5, Issue: 2, DOI: 10.1117/1.JMI.5.2.024005. (IF 1.109)

  • M. Wang, L.L.S. Ong, J. Dauwels, H. H. Asada, ""Automated tracking and quantification of angiogenic vessel formation in 3D microfluidic devices", PLOS ONE, Nov 2017, Volume:  12, Issue: 11, DOI: 10.17605/OSF.IO/8MJPW), (IF: 11.675).

  • W. Zhao, J. Dauwels, and J. Cao, “The effects of cell asynchrony on gene expression levels: analysis and application to Plasmodium falciparum,” IEEE Journal of Biomedical and Health Informatics, Jul 2015, Volume: 19, Issue: 4 Pages: 1301 - 1307, DOI: 10.1109/JBHI.2015.2434499, (IF: 1.939).    PDF 

  • L. Garg, J. Dauwels, A. Earnest, and K.P. Leong, “Tensor based methods for handling missing data in quality-of-life questionnaires,” IEEE Transactions on Information Technology in Biomedicine, IEEE J Biomed Health Inform, Sep 2014, vol.18:5, pp. 1571 - 1580 (IF: 1.939).    PDF ​ ​​

  • L.L. Ong, J. Dauwels, M.H. Ang Jr, and H.H. Asada, “A Bayesian filtering approach to incorporate 2D/3D time-lapse confocal images for tracking angiogenic sprouting cells interacting with the gel matrix,” Med Image Anal., Jan 2014, vol. 18:1, pp. 211-27 (IF: 4.087).    PDF 

Computational Optics

  • Z. Jingshan, J. Dauwels, L. Tian, L. Waller, “Partially Coherent Phase Imaging with Unknown Source Shapes,” Biomedical Optics Express, Jan 2015, vol. 6:1, pp. 257–265 (IF: 3.497).    PDF   


  • Z. Jingshan, R. A. Claus, J. Dauwels, L. Tian, and L. Waller, “Transport of intensity phase imaging by intensity spectrum fitting of unequally spaced defocus planes,” Optics Express, May 2014, vol. 22:9, pp. 10661-10674 (IF: 3.546).    PDF  ​

  • Z. Jingshan, J. Dauwels, M.A. Vázquez, and L. Waller, “Sparse ACEKF for phase reconstruction,” Optics Express, Jul 2013, vol. 21:15, pp.18125-37 (IF: 3.546).    PDF​ 


  • P. Gupta, T. T. T. Zan,  J. Dauwels, A. Ukil, "Flow Based Estimation and Comparative Study of Gas Demand Profile for Residential Units in Singapore", IEEE Transactions on Sustainable Energy, July 2018, doi: 10.1109/TSTE.2018.2861821. (IF: 6.235). 

  • T. T. T. Zan, P. Gupta, M. Wang, J. Dauwels, A. Ukil, "Multi-Objective Optimal Sensor Placement for Low-Pressure Gas Distribution Networks", IEEE Sensors Journal, June 2018, vol. 18:16, pp. 6660-6668 (IF: 2.617)

  • Y. Tahir, J. Dauwels, D. Thalmann, N. M. Thalmann, "A User Study of a Humanoid Robot as a Social Mediator for Two-Person Conversations", International Journal of Social Robotics, April 2018, doi: 10.1007/s12369-018-0478-3 (IF: 2.009).

  • S. R. Ravula, S. C. Narasimman, L. Wang, A. Ukil, "Experimental Validation of Leak and Water-Ingression Detection in Low-Pressure Gas Pipeline Using Pressure and Flow Measurements", IEEE Sensors Journal, October 2017, vol. 17:20, pp. 6734-6742 (IF: 2.617). 

  • L. Wang, S. C. Narasimman, S. R. Ravula, A. Ukil, "Water Ingress Detection in Low-Pressure Gas Pipelines Using Distributed Temperature Sensing System", IEEE Sensors Journal, May 2017, vol. 17:10, pp. 3165-3173 (IF: 2.617)

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