Stephan Lau

Dr Stephan Lau

Post-doctoral Researcher

School of Computer Science

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.

  • Journals

    Year Citation
    2022 Almaghrabi, S. A., Thewlis, D., Thwaites, S., Rogasch, N. C., Lau, S., Clark, S. R., & Baumert, M. (2022). The Reproducibility of Bio-Acoustic Features is Associated With Sample Duration, Speech Task, and Gender. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, 167-175.
    2022 Milton, A. G., Lau, S., Kremer, K. L., Rao, S. R., Mas, E., Snel, M. F., . . . Koblar, S. A. (2022). FAST-IT: F ind A S imple T est- I n T IA (transient ischaemic attack): a prospective cohort study to develop a multivariable prediction model for diagnosis of TIA through proteomic discovery and candidate lipid mass spectrometry, neuroimaging and machine learning - study protocol. BMJ Open, 12(4), 9 pages.
    2022 Dölker, E. -M., Lau, S., Bernhard, M. A., & Haueisen, J. (2022). Perception thresholds and qualitative perceptions for electrocutaneous stimulation.. Scientific reports, 12(1), 12 pages.
    2022 Dölker, E., Lau, S., Bernhard, M. A., & Haueisen, J. (2022). Publisher Correction: Perception thresholds and qualitative perceptions for electrocutaneous stimulation (Scientific Reports, (2022), 12, 1, (7335), 10.1038/s41598-022-10708-9). Scientific Reports, 12(1), 9965.
    2020 Naskovska, K., Lau, S., Korobkov, A. A., Haueisen, J., & Haardt, M. (2020). Coupled CP decomposition of simultaneous MEG-EEG signals for differentiating oscillators during photic driving. Frontiers in Neuroscience, 14, 261-1-261-18.
    DOI Scopus6 WoS3
    2017 Lau, S., Flemming, L., & Haueisen, J. (2017). Corrigendum: “Magnetoencephalography signals are influenced by skull defects” (Clin. Neurophysiol. 125 (2014) 1653–1662) (Clinical Neurophysiology, (S1388245713013564), (10.1016/j.clinph.2013.12.099)). Clinical Neurophysiology, 128(6), 1116.
    DOI Scopus1
    2016 Lau, S., Petković, B., & Haueisen, J. (2016). Optimal magnetic sensor vests for cardiac source imaging. Sensors (Switzerland), 16(6), 17 pages.
    DOI Scopus6 WoS6 Europe PMC2
    2016 Lau, S., Güllmar, D., Flemming, L., Grayden, D., Cook, M., Wolters, C., & Haueisen, J. (2016). Skull defects in finite element head models for source reconstruction from magnetoencephalography signals. Frontiers in Neuroscience, 10(1), 141-1-141-15.
    DOI Scopus15 WoS14 Europe PMC7
    2016 Lau, S., & Haueisen, J. (2016). Biosignal analysis. BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK, 61(6), 577-578.
    2015 Goernig, M., Hoeffling, B., Lau, S., Figulla, H., & Haueisen, J. (2015). T vector and loop characteristics improve detection of myocardial injury after infarction. Journal of Medical and Biological Engineering, 35(3), 381-386.
    DOI Scopus3 WoS2
    2014 Lau, S., Flemming, L., & Haueisen, J. (2014). Magnetoencephalography signals are influenced by skull defects. Clinical Neurophysiology, 125(8), 1653-1662.
    DOI Scopus13 WoS15 Europe PMC11
    2014 Lau, S., Flemming, L., & Haueisen, J. (2014). P506: MEG is influenced by skull defects. Clinical Neurophysiology, 125, S185-S186.
    2014 Lau, S., Vogrin, S. J., D'Souza, W., Haueisen, J., & Cook, M. J. (2014). P888: Clustering of interictal events for improved fMRI specificity in high density EEG-fMRI studies. Clinical Neurophysiology, 125, S282.
    2014 Liebl, M., Steinhoff, U., Wiekhorst, F., Baumgarten, D., & Gutkelch, D. (2014). Track j: magnetic methods in medicine.. Biomedizinische Technik. Biomedical engineering, 59 Suppl 1(Supplement), s649-s699.
    2013 Lau, S., Guellmar, D., Flemming, L., & Haueisen, J. (2013). Influence of skull defects on MEG source reconstruction in an in-vivo animal experiment. Biomedical Engineering / Biomedizinische Technik, 58(Suppl.1), 1-2.
    2012 Lau, S., Guellmar, D., Flemming, L., & Haueisen, J. (2012). Skull Defects in MEG and EEG: Experimental Results and Modelling. BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK, 57, 308.
    2012 Lau, S., Petkovic, B., Di Rienzo, L., & Haueisen, J. (2012). Optimizing a magnetic sensor vest for cardiac source imaging. Biomedizinische Technik, 57(SI-1 Track-E), 1016.
    2012 Lau, S., Güllmar, D., Flemming, L., & Haueisen, J. (2012). Skull Defects in MEG and EEG: Experimental Results and Modelling. Biomedizinische Technik, 57(SI-1 Track-M), 308.
    2012 Sonntag, H., Haueisen, J., Lau, S., Eichardt, R., Wolters, C., Vorwerk, J., . . . Güllmar, D. (2012). Influence of finite element discretization on the EEG/MEG forward solution in rabbits. Biomedizinische Technik, 57(SI-1 Track-M), 309.
    2011 Schneider, R., Lau, S., Kuhlmann, L., Vogrin, S., Gratkowski, M., Cook, M., & Haueisen, J. (2011). Matching pursuit based removal of cardiac pulse-related artifacts in EEG/fMRI. World Academy of Science, Engineering and Technology, 56, 1559-1564.
    2009 Lau, S., Maktabi, M., Güllmar, D., & Haueisen, J. (2009). Sensitivity of EEG/MEG-based reconstruction of neural activity to the finite element model discretization. BMC Neuroscience, 10(S1).
    2008 Lau, S., Eichardt, R., Di Rienzo, L., & Haueisen, J. (2008). Tabu search optimization of magnetic sensor systems for magnetocardiography. IEEE Transactions on Magnetics, 44(6), 1442-1445.
    DOI Scopus27 WoS21
    2008 Jaros, U., Hilgenfeld, B., Lau, S., Curio, G., & Haueisen, J. (2008). Nonlinear interactions of high-frequency oscillations in the human somatosensory system. Clinical Neurophysiology, 119(11), 2647-2657.
    DOI Scopus14 WoS11 Europe PMC9
    Bozek, J., Griffanti, L., Lau, S., & Jenkinson, M. (n.d.). Normative models for neuroimaging markers: Impact of model selection, sample size and evaluation criteria.
  • Conference Papers

    Year Citation
    2021 Milton, A. G., Lau, S., Edwards, S., Duvenage, H. A., Djukic, M., Snel, M., . . . Hamilton-Bruce, M. A. (2021). Searching for de novo Transient Ischemic Attack (TIA) biomarkers using new-generation mass spectrometry. In INTERNATIONAL JOURNAL OF STROKE Vol. 16 (pp. 22). SAGE PUBLICATIONS LTD.
    2018 Naskovska, K., Lau, S., Aboughazala, A., Haardt, M., & Haueisen, J. (2018). Joint MEG-EEG signal decomposition using the coupled SECSI framework: Validation on a controlled experiment. In 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017 Vol. 2017-December (pp. 1-5). Online: IEEE.
    DOI Scopus6
    2009 Lau, S., Flemming, L., Gießler, F., Güllmar, D., & Haueisen, J. (2009). Development of an experimental setup to investigate the effect of skull discontinuities on the EEG. In O. Dossel, & W. C. Schlegel (Eds.), IFMBE Proceedings Vol. 25 (pp. 1620-1623). Munich, GERMANY: SPRINGER.
    2006 Goernig, M., Tute, C., Liehr, M., Lau, S., Haueisen, J., Figulla, H. R., & Leder, U. (2006). Spatiotemporal correlation analyses: A new procedure for standardisation of DC magnetocardiograms. In Biomedizinische Technik Vol. 51 (pp. 198-200). Germany: WALTER DE GRUYTER & CO.
    DOI Scopus3 WoS3 Europe PMC2
    2006 Lau, S., Haueisen, J., Schukat-Talamazzini, E. G., Voss, A., Goernig, M., Leder, U., & Figulla, H. R. (2006). Low HRV entropy is strongly associated with myocardial infarction. In Biomedizinische Technik Vol. 51 (pp. 186-189). Germany: WALTER DE GRUYTER GMBH.
    DOI Scopus4 WoS3 Europe PMC4
  • Conference Items

    Year Citation
    2020 Milton, A. G., Kremer, K. L., Rao, S. R., Mas, E., Snel, M. F., Trim, P. J., . . . Hamilton-Bruce, M. A. (2020). A Prospective Cohort Study to Develop and Validate a Multivariable Prediction Model for Transient Ischaemic Attack (TIA) Diagnosis Using Proteomic Discovery and Candidate Lipid Mass Spectrometry, Neuroimaging and Machine Learning: Study Protocol. Poster session presented at the meeting of Abstracts of the Annual Conference of the Asia Pacific Stroke Organization (APSO 2020), as published in Cerebrovascular Diseases. Korea: Karger.
    2014 Haueisen, J., Lau, S., Flemming, L., Sonntag, H., Maess, B., & Gullmar, D. (2014). Influence of volume conductor modeling on source reconstruction in magnetoencephalography and electroencephalography. Poster session presented at the meeting of 2014 31th URSI General Assembly and Scientific Symposium, URSI GASS 2014. Beijing, PEOPLES R CHINA: IEEE.
  • Current Higher Degree by Research Supervision (University of Adelaide)

    Date Role Research Topic Program Degree Type Student Load Student Name
    2022 Co-Supervisor Using AI to predict clinical outcomes in dementia Doctor of Philosophy Doctorate Full Time Luke Thomas Whitbread
    2021 Co-Supervisor Anatomically-based Deep Learning Models for Improved Neuroimaging Analysis Doctor of Philosophy under a Jointly-awarded Degree Agreement with Doctorate Full Time Miss Georgia Kenyon
    2021 Co-Supervisor “Utility of Inflammatory Biomarkers to Predict Brainstem Imaging Changes in Parkinson’s Disease and TBI” Doctor of Philosophy Doctorate Full Time Mr Angus McNamara
  • Memberships

    Date Role Membership Country
    2008 - ongoing Member IEEE Society for Engineering in Medicine and Biology Australia
  • Position: Post-doctoral Researcher
  • Phone: 83131295
  • Email:
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 2
  • Org Unit: Australian Institute for Machine Learning - Operations

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