Hau-Tieng Wu

Hau-Tieng Wu
  • Associate Professor of Mathematics
  • Associate Professor of Statistical Science (Joint)
External address: 207 Physics Building, 120 Science Drive, Durham, NC 27708
Internal office address: Box 90320, Durham, NC 27708
Phone: (919) 660-2861

Research Areas and Keywords


harmonic analysis, wavelet analysis, time-frequency analysis

Biological Modeling

physiological time series, multimodal time series

Geometry: Differential & Algebraic

spectral geometry


empirical process, large deviation theory

Signals, Images & Data

machine learning, unsupervised learning, data analysis

Education & Training
  • Ph.D., Princeton University 2011

  • M.D., National Yang Ming University (Taiwan) 2003

Selected Grants

HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms awarded by National Science Foundation (Senior Investigator). 2019 to 2022

Wu, Hau-Tieng, et al. “A new approach to complicated and noisy physiological waveforms analysis: peripheral venous pressure waveform as an example.Journal of Clinical Monitoring and Computing, June 2020. Epmc, doi:10.1007/s10877-020-00524-9. Full Text

Frasch, Martin G., et al. “Brief Report: Can a Composite Heart Rate Variability Biomarker Shed New Insights About Autism Spectrum Disorder in School-Aged Children?Journal of Autism and Developmental Disorders, May 2020. Epmc, doi:10.1007/s10803-020-04467-7. Full Text

Wang, Shen-Chih, et al. “Novel Imaging Revealing Inner Dynamics for Cardiovascular Waveform Analysis via Unsupervised Manifold Learning.Anesthesia and Analgesia, vol. 130, no. 5, May 2020, pp. 1244–54. Epmc, doi:10.1213/ane.0000000000004738. Full Text

Malik, John, et al. “An adaptive QRS detection algorithm for ultra-long-term ECG recordings.Journal of Electrocardiology, vol. 60, May 2020, pp. 165–71. Epmc, doi:10.1016/j.jelectrocard.2020.02.016. Full Text

Liu, Gi-Ren, et al. “Save Muscle Information-Unfiltered EEG Signal Helps Distinguish Sleep Stages.Sensors (Basel, Switzerland), vol. 20, no. 7, Apr. 2020. Epmc, doi:10.3390/s20072024. Full Text

Liu, Yi-Wen, et al. “Transient-evoked otoacoustic emission signals predicting outcomes of acute sensorineural hearing loss in patients with Ménière's disease.Acta Oto Laryngologica, vol. 140, no. 3, Mar. 2020, pp. 230–35. Epmc, doi:10.1080/00016489.2019.1704865. Full Text

Lo, Yu-Lun, et al. “Hypoventilation patterns during bronchoscopic sedation and their clinical relevance based on capnographic and respiratory impedance analysis.Journal of Clinical Monitoring and Computing, vol. 34, no. 1, Feb. 2020, pp. 171–79. Epmc, doi:10.1007/s10877-019-00269-0. Full Text

Lobmaier, Silvia M., et al. “Fetal heart rate variability responsiveness to maternal stress, non-invasively detected from maternal transabdominal ECG.Archives of Gynecology and Obstetrics, vol. 301, no. 2, Feb. 2020, pp. 405–14. Epmc, doi:10.1007/s00404-019-05390-8. Full Text

Liu, G. R., et al. “Diffuse to fuse EEG spectra – Intrinsic geometry of sleep dynamics for classification.” Biomedical Signal Processing and Control, vol. 55, Jan. 2020. Scopus, doi:10.1016/j.bspc.2019.101576. Full Text

Su, Pei-Chun, et al. “Recovery of the fetal electrocardiogram for morphological analysis from two trans-abdominal channels via optimal shrinkage.Physiol Meas, vol. 40, no. 11, Dec. 2019, p. 115005. Pubmed, doi:10.1088/1361-6579/ab4b13. Full Text


Thai, D. H., et al. “Locally convex kernel mixtures: Bayesian subspace learning.” Proceedings  18th Ieee International Conference on Machine Learning and Applications, Icmla 2019, 2019, pp. 272–75. Scopus, doi:10.1109/ICMLA.2019.00051. Full Text

Martinez, N., et al. “Non-Contact Photoplethysmogram and Instantaneous Heart Rate Estimation from Infrared Face Video.” Proceedings  International Conference on Image Processing, Icip, vol. 2019-September, 2019, pp. 2020–24. Scopus, doi:10.1109/ICIP.2019.8803109. Full Text

Wu, J. C., et al. “A Portable Monitoring System with Automatic Event Detection for Sleep Apnea Level-IV Evaluation.” Proceedings  Ieee International Symposium on Circuits and Systems, vol. 2018-May, 2018. Scopus, doi:10.1109/ISCAS.2018.8351221. Full Text

Lederman, R. R., et al. “Alternating diffusion for common manifold learning with application to sleep stage assessment.” Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing  Proceedings, vol. 2015-August, 2015, pp. 5758–62. Scopus, doi:10.1109/ICASSP.2015.7179075. Full Text

Lederman, Roy R., et al. “ALTERNATING DIFFUSION FOR COMMON MANIFOLD LEARNING WITH APPLICATION TO SLEEP STAGE ASSESSMENT.” 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), 2015, pp. 5758–62.

Daubechies William Benter Prize

On June 4th, 2018, Professor Ingrid Daubechies was the first female recipient of the William Benter Prize in Applied Mathematics.  This prestigious award recognizes outstanding mathematical contributions that have had a direct and fundamental impact... read more »

Hau-Tieng Wu: Vital Signs

Bridging mathematics, statistics and medicine with new Duke professor https://today.duke.edu/2017/10/hau-tieng-wu-vital-signs read more »