Scholars@Duke

• Background
• 

  Education, Training, & Certifications

  • Ph.D., Princeton University 2011
  • M.D., National Yang Ming University (Taiwan) 2003
• Recognition
• 

  In the News

  • OCT 17, 2017

    Hau-tieng Wu: Vital Signs
• Research
• 

  Selected Grants

  • HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms awarded by  National Science Foundation 2019 - 2022
• Publications & Artistic Works
• 

  Selected Publications

  • Academic Articles

    • Huang, Yu-Chen, Ting-Yu Lin, Hau-Tieng Wu, Po-Jui Chang, Chun-Yu Lo, Tsai-Yu Wang, Chih-Hsi Scott Kuo, et al. “Cardiorespiratory coupling is associated with exercise capacity in patients with chronic obstructive pulmonary disease.” Bmc Pulmonary Medicine 21, no. 1 (January 12, 2021): 22. https://doi.org/10.1186/s12890-021-01400-1.
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    • Ding, X., and H. T. Wu. “On the Spectral Property of Kernel-Based Sensor Fusion Algorithms of High Dimensional Data.” Ieee Transactions on Information Theory 67, no. 1 (January 1, 2021): 640–70. https://doi.org/10.1109/TIT.2020.3026255.
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    • Frasch, Martin G., Chao Shen, Hau-Tieng Wu, Alexander Mueller, Emily Neuhaus, Raphael A. Bernier, Dana Kamara, and Theodore P. Beauchaine. “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 51, no. 1 (January 2021): 346–56. https://doi.org/10.1007/s10803-020-04467-7.
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    • Su, Pei-Chun, Elsayed Z. Soliman, and Hau-Tieng Wu. “Robust T-End Detection via T-End Signal Quality Index and Optimal Shrinkage.” Sensors (Basel, Switzerland) 20, no. 24 (December 9, 2020). https://doi.org/10.3390/s20247052.
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    • Malik, John, Zak Loring, Jonathan P. Piccini, and Hau-Tieng Wu. “Interpretable morphological features for efficient single-lead automatic ventricular ectopy detection.” J Electrocardiol 65 (December 3, 2020): 55–63. https://doi.org/10.1016/j.jelectrocard.2020.11.014.
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    • Wang, Hsin-Hsiao Scott, Dylan Cahill, John Panagides, Caleb P. Nelson, Hau-Tieng Wu, and Carlos Estrada. “Pattern recognition algorithm to identify detrusor overactivity on urodynamics.” Neurourology and Urodynamics, November 18, 2020. https://doi.org/10.1002/nau.24578.
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    • Chang, Zhuoqing, Ziyu Chen, Christopher D. Stephen, Jeremy D. Schmahmann, Hau-Tieng Wu, Guillermo Sapiro, and Anoopum S. Gupta. “Accurate detection of cerebellar smooth pursuit eye movement abnormalities via mobile phone video and machine learning.” Scientific Reports 10, no. 1 (October 29, 2020): 18641. https://doi.org/10.1038/s41598-020-75661-x.
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    • Chang, Hung-Chi, Hau-Tieng Wu, Po-Chiun Huang, Hsi-Pin Ma, Yu-Lun Lo, and Yuan-Hao Huang. “Portable Sleep Apnea Syndrome Screening and Event Detection Using Long Short-Term Memory Recurrent Neural Network.” Sensors (Basel, Switzerland) 20, no. 21 (October 25, 2020). https://doi.org/10.3390/s20216067.
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    • Frasch, Martin G., Silvia M. Lobmaier, Tamara Stampalija, Paula Desplats, María Eugenia Pallarés, Verónica Pastor, Marcela A. Brocco, et al. “Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale multi-species perspective on data collection and analysis.” Neuroscience and Biobehavioral Reviews 117 (October 2020): 165–83. https://doi.org/10.1016/j.neubiorev.2018.05.026.
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    • Wu, H. T. “Current state of nonlinear-type time–frequency analysis and applications to high-frequency biomedical signals.” Current Opinion in Systems Biology 23 (October 1, 2020): 8–21. https://doi.org/10.1016/j.coisb.2020.07.013.
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    • Huang, Yu-Chen, Aymen Alian, Yu-Lun Lo, Kirk Shelley, and Hau-Tieng Wu. “Scientific impact of the standard phase reconstruction method and its clinical applications,” September 30, 2020. https://doi.org/10.1101/2020.09.29.310417.
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    • Liu, Gi-Ren, Ting-Yu Lin, Hau-Tieng Wu, Yuan-Chung Sheu, Ching-Lung Liu, Wen-Te Liu, Mei-Chen Yang, et al. “Large scale assessment of consistency in sleep stage scoring rules among multiple sleep centers using an interpretable machine learning algorithm.” Journal of Clinical Sleep Medicine : Jcsm : Official Publication of the American Academy of Sleep Medicine, September 23, 2020. https://doi.org/10.5664/jcsm.8820.
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    • Chang, Cheng-Hsi, Yue-Lin Fang, Yu-Jung Wang, Hau-Tieng Wu, and Yu-Ting Lin. “Differentiation of skin incision and laparoscopic trocar insertion via quantifying transient bradycardia measured by electrocardiogram.” Journal of Clinical Monitoring and Computing 34, no. 4 (August 2020): 753–62. https://doi.org/10.1007/s10877-019-00378-w.
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    • Wu, Hau-Tieng, Aymen Alian, and Kirk Shelley. “A new approach to complicated and noisy physiological waveforms analysis: peripheral venous pressure waveform as an example.” Journal of Clinical Monitoring and Computing, June 11, 2020. https://doi.org/10.1007/s10877-020-00524-9.
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    • Shen, Chao, Yu-Ting Lin, and Hau-Tieng Wu. “Robust and scalable manifold learning via landmark diffusion for long-term medical signal processing,” June 2020. https://doi.org/10.1101/2020.05.31.126649.
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    • Malik, John, Elsayed Z. Soliman, and Hau-Tieng Wu. “An adaptive QRS detection algorithm for ultra-long-term ECG recordings.” Journal of Electrocardiology 60 (May 2020): 165–71. https://doi.org/10.1016/j.jelectrocard.2020.02.016.
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    • Wang, Shen-Chih, Hau-Tieng Wu, Po-Hsun Huang, Cheng-Hsi Chang, Chien-Kun Ting, and Yu-Ting Lin. “Novel Imaging Revealing Inner Dynamics for Cardiovascular Waveform Analysis via Unsupervised Manifold Learning.” Anesthesia and Analgesia 130, no. 5 (May 2020): 1244–54. https://doi.org/10.1213/ane.0000000000004738.
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    • Liu, Gi-Ren, Caroline Lustenberger, Yu-Lun Lo, Wen-Te Liu, Yuan-Chung Sheu, and Hau-Tieng Wu. “Save Muscle Information-Unfiltered EEG Signal Helps Distinguish Sleep Stages.” Sensors (Basel, Switzerland) 20, no. 7 (April 3, 2020). https://doi.org/10.3390/s20072024.
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    • Liu, Yi-Wen, Sheng-Lun Kao, Hau-Tieng Wu, Tzu-Chi Liu, Te-Yung Fang, and Pa-Chun Wang. “Transient-evoked otoacoustic emission signals predicting outcomes of acute sensorineural hearing loss in patients with Ménière's disease.” Acta Oto Laryngologica 140, no. 3 (March 2020): 230–35. https://doi.org/10.1080/00016489.2019.1704865.
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    • Lo, Yu-Lun, Hau-Tieng Wu, Yu-Ting Lin, Han-Pin Kuo, and Ting-Yu Lin. “Hypoventilation patterns during bronchoscopic sedation and their clinical relevance based on capnographic and respiratory impedance analysis.” Journal of Clinical Monitoring and Computing 34, no. 1 (February 2020): 171–79. https://doi.org/10.1007/s10877-019-00269-0.
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    • Lobmaier, Silvia M., A. Müller, C. Zelgert, C. Shen, P. C. Su, G. Schmidt, B. Haller, et al. “Fetal heart rate variability responsiveness to maternal stress, non-invasively detected from maternal transabdominal ECG.” Archives of Gynecology and Obstetrics 301, no. 2 (February 2020): 405–14. https://doi.org/10.1007/s00404-019-05390-8.
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    • Huroyan, Vahan, Gilad Lerman, and Hau-Tieng Wu. “Solving Jigsaw Puzzles by the Graph Connection Laplacian.” Siam Journal on Imaging Sciences 13, no. 4 (January 2020): 1717–53. https://doi.org/10.1137/19m1290760.
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    • Liu, G. R., Y. L. Lo, J. Malik, Y. C. Sheu, and H. T. Wu. “Diffuse to fuse EEG spectra – Intrinsic geometry of sleep dynamics for classification.” Biomedical Signal Processing and Control 55 (January 1, 2020). https://doi.org/10.1016/j.bspc.2019.101576.
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    • Su, Pei-Chun, Stephen Miller, Salim Idriss, Piers Barker, and Hau-Tieng Wu. “Recovery of the fetal electrocardiogram for morphological analysis from two trans-abdominal channels via optimal shrinkage.” Physiol Meas 40, no. 11 (December 2, 2019): 115005. https://doi.org/10.1088/1361-6579/ab4b13.
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    • Talmon, R., and H. T. Wu. “Latent common manifold learning with alternating diffusion: Analysis and applications.” Applied and Computational Harmonic Analysis 47, no. 3 (November 1, 2019): 848–92. https://doi.org/10.1016/j.acha.2017.12.006.
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    • Korolj, Anastasia, Hau-Tieng Wu, and Milica Radisic. “A healthy dose of chaos: Using fractal frameworks for engineering higher-fidelity biomedical systems.” Biomaterials 219 (October 2019): 119363. https://doi.org/10.1016/j.biomaterials.2019.119363.
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    • Alagapan, Sankaraleengam, Hae Won Shin, Flavio Fröhlich, and Hau-Tieng Wu. “Diffusion geometry approach to efficiently remove electrical stimulation artifacts in intracranial electroencephalography.” Journal of Neural Engineering 16, no. 3 (June 2019): 036010. https://doi.org/10.1088/1741-2552/aaf2ba.
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    • Lu, Y., H. T. Wu, and J. Malik. “Recycling cardiogenic artifacts in impedance pneumography.” Biomedical Signal Processing and Control 51 (May 1, 2019): 162–70. https://doi.org/10.1016/j.bspc.2019.02.027.
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    • Chen, Hsing-Yu, Heng-Chih Pan, Yung-Chang Chen, Yu-Chun Chen, Yi-Hsuan Lin, Sien-Hung Yang, Jiun-Liang Chen, and Hau-Tieng Wu. “Traditional Chinese medicine use is associated with lower end-stage renal disease and mortality rates among patients with diabetic nephropathy: a population-based cohort study.” Bmc Complementary and Alternative Medicine 19, no. 1 (April 3, 2019): 81. https://doi.org/10.1186/s12906-019-2491-y.
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    • Zhang, J. T., M. Y. Cheng, H. T. Wu, and B. Zhou. “A new test for functional one-way ANOVA with applications to ischemic heart screening.” Computational Statistics and Data Analysis 132 (April 1, 2019): 3–17. https://doi.org/10.1016/j.csda.2018.05.004.
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    • Tan, Chunyu, Liming Zhang, and Hau-Tieng Wu. “A Novel Blaschke Unwinding Adaptive-Fourier-Decomposition-Based Signal Compression Algorithm With Application on ECG Signals.” Ieee Journal of Biomedical and Health Informatics 23, no. 2 (March 2019): 672–82. https://doi.org/10.1109/jbhi.2018.2817192.
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    • Katz, O., R. Talmon, Y. L. Lo, and H. T. Wu. “Alternating diffusion maps for multimodal data fusion.” Information Fusion 45 (January 1, 2019): 346–60. https://doi.org/10.1016/j.inffus.2018.01.007.
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    • Lin, Yu-Ting, Yu-Lun Lo, Chen-Yun Lin, Martin G. Frasch, and Hau-Tieng Wu. “Unexpected sawtooth artifact in beat-to-beat pulse transit time measured from patient monitor data.” Plos One 14, no. 9 (January 2019): e0221319. https://doi.org/10.1371/journal.pone.0221319.
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    • Shnitzer, T., R. R. Lederman, G. R. Liu, R. Talmon, and H. T. Wu. “Diffusion operators for multimodal data analysis” 20 (January 1, 2019): 1–39. https://doi.org/10.1016/bs.hna.2019.07.008.
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    • Lin, C. Y., and H. T. Wu. “Embeddings of Riemannian manifolds with finite eigenvector fields of connection Laplacian.” Calculus of Variations and Partial Differential Equations 57, no. 5 (October 1, 2018). https://doi.org/10.1007/s00526-018-1401-3.
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    • Escalona-Vargas, Diana, Hau-Tieng Wu, Martin G. Frasch, and Hari Eswaran. “A Comparison of Five Algorithms for Fetal Magnetocardiography Signal Extraction.” Cardiovascular Engineering and Technology 9, no. 3 (September 2018): 483–87. https://doi.org/10.1007/s13239-018-0351-4.
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    • Malik, John, Yu-Lun Lo, and Hau-Tieng Wu. “Sleep-wake classification via quantifying heart rate variability by convolutional neural network.” Physiological Measurement 39, no. 8 (August 20, 2018): 085004. https://doi.org/10.1088/1361-6579/aad5a9.
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    • Wu, H. T., J. C. Wu, P. C. Huang, T. Y. Lin, T. Y. Wang, Y. H. Huang, and Y. L. Lo. “Phenotype-based and self-learning inter-individual sleep apnea screening with a level IV-like monitoring system.” Frontiers in Physiology 9, no. JUL (July 2, 2018). https://doi.org/10.3389/fphys.2018.00723.
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    • Wu, Hau-Tieng, and Yi-Wen Liu. “Analyzing transient-evoked otoacoustic emissions by concentration of frequency and time.” The Journal of the Acoustical Society of America 144, no. 1 (July 2018): 448. https://doi.org/10.1121/1.5047749.
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    • Lin, C. Y., A. Minasian, X. J. Qi, and H. T. Wu. “Manifold Learning via the Principle Bundle Approach.” Frontiers in Applied Mathematics and Statistics 4 (June 25, 2018). https://doi.org/10.3389/fams.2018.00021.
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    • Wu, Hau-Tieng, and Elsayed Z. Soliman. “A new approach for analysis of heart rate variability and QT variability in long-term ECG recording.” Biomedical Engineering Online 17, no. 1 (May 3, 2018): 54. https://doi.org/10.1186/s12938-018-0490-8.
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    • Lin, C. Y., L. Su, and H. T. Wu. “Wave-Shape Function Analysis: When Cepstrum Meets Time–Frequency Analysis.” Journal of Fourier Analysis and Applications 24, no. 2 (April 1, 2018): 451–505. https://doi.org/10.1007/s00041-017-9523-0.
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    • Shen, C., M. G. Frasch, H. T. Wu, C. L. Herry, M. Cao, A. Desrochers, G. Fecteau, and P. Burns. “Non-invasive acquisition of fetal ECG from the maternal xyphoid process: a feasibility study in pregnant sheep and a call for open data sets.” Physiological Measurement 39, no. 3 (March 27, 2018): 035005. https://doi.org/10.1088/1361-6579/aaaaa4.
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    • Kowalski, M., A. Meynard, and H. T. Wu. “Convex Optimization approach to signals with fast varying instantaneous frequency.” Applied and Computational Harmonic Analysis 44, no. 1 (January 1, 2018): 89–122. https://doi.org/10.1016/j.acha.2016.03.008.
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    • Wu, H. T., and N. Wu. “Think globally, fit locally under the manifold setup: Asymptotic analysis of locally linear embedding.” Annals of Statistics 46, no. 6B (January 1, 2018): 3805–37. https://doi.org/10.1214/17-AOS1676.
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    • Wu, Han-Kuei, Yu-Shien Ko, Yu-Sheng Lin, Hau-Tieng Wu, Tung-Hu Tsai, and Hen-Hong Chang. “Corrigendum to "The correlation between pulse diagnosis and constitution identification in traditional Chinese medicine" [Complementary Ther. Med. 30 (2017) 107-112].” Complementary Therapies in Medicine 35 (December 2017): 145. https://doi.org/10.1016/j.ctim.2017.09.004.
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    • Lin, Y. Y., H. T. Wu, C. A. Hsu, P. C. Huang, Y. H. Huang, and Y. L. Lo. “Sleep Apnea Detection Based on Thoracic and Abdominal Movement Signals of Wearable Piezoelectric Bands.” Ieee Journal of Biomedical and Health Informatics 21, no. 6 (November 1, 2017): 1533–45. https://doi.org/10.1109/JBHI.2016.2636778.
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    • Lin, Y., H. Wu, Z. Yang, and Q. Lin. “Erratum: Validation of the Name Paraphlomis hispida (Lamiaceae) (Novon (2017) 25 (436-437) DOI: 10.3417/D-16-00022).” Novon 26, no. 2 (November 1, 2017): 256. https://doi.org/10.3417/2018296.
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    • Chao, Yi-Sheng, Hau-Tieng Wu, Marco Scutari, Tai-Shen Chen, Chao-Jung Wu, Madeleine Durand, and Antoine Boivin. “A network perspective on patient experiences and health status: the Medical Expenditure Panel Survey 2004 to 2011.” Bmc Health Services Research 17, no. 1 (August 22, 2017): 579. https://doi.org/10.1186/s12913-017-2496-5.
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    • Lin, Ting-Yu, Yueh-Fu Fang, Shih-Hao Huang, Tsai-Yu Wang, Chih-Hsi Kuo, Hau-Tieng Wu, Han-Pin Kuo, and Yu-Lun Lo. “Capnography monitoring the hypoventilation during the induction of bronchoscopic sedation: A randomized controlled trial.” Scientific Reports 7, no. 1 (August 17, 2017): 8685. https://doi.org/10.1038/s41598-017-09082-8.
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    • Georgiou, A. S., J. M. Bello-Rivas, C. W. Gear, H. T. Wu, E. Chiavazzo, and I. G. Kevrekidis. “An exploration algorithm for stochastic simulators driven by energy gradients.” Entropy 19, no. 7 (July 1, 2017). https://doi.org/10.3390/e19070294.
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    • Malik, John, Neil Reed, Chun-Li Wang, and Hau-Tieng Wu. “Single-lead f-wave extraction using diffusion geometry.” Physiological Measurement 38, no. 7 (June 22, 2017): 1310–34. https://doi.org/10.1088/1361-6579/aa707c.
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    • Sheu, Y. L., L. Y. Hsu, P. T. Chou, and H. T. Wu. “Entropy-based time-varying window width selection for nonlinear-type time–frequency analysis.” International Journal of Data Science and Analytics 3, no. 4 (June 1, 2017): 231–45. https://doi.org/10.1007/s41060-017-0053-2.
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    • Su, L., and H. T. Wu. “Extract Fetal ECG from Single-Lead Abdominal ECG by De-Shape Short Time Fourier Transform and Nonlocal Median.” Frontiers in Applied Mathematics and Statistics 3 (February 22, 2017). https://doi.org/10.3389/fams.2017.00002.
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    • Herry, Christophe L., Martin Frasch, Andrew Je Seely, and Hau-Tieng Wu. “Heart beat classification from single-lead ECG using the synchrosqueezing transform.” Physiological Measurement 38, no. 2 (February 2017): 171–87. https://doi.org/10.1088/1361-6579/aa5070.
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    • Wu, Han-Kuei, Yu-Shien Ko, Yu-Sheng Lin, Hau-Tieng Wu, Tung-Hu Tsai, and Hen-Hong Chang. “The correlation between pulse diagnosis and constitution identification in traditional Chinese medicine.” Complementary Therapies in Medicine 30 (February 2017): 107–12. https://doi.org/10.1016/j.ctim.2016.12.005.
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    • Wu, H. T. “Embedding Riemannian manifolds by the heat kernel of the connection Laplacian.” Advances in Mathematics 304 (January 2, 2017): 1055–79. https://doi.org/10.1016/j.aim.2016.05.023.
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    • Cicone, Antonio, and Hau-Tieng Wu. “How Nonlinear-Type Time-Frequency Analysis Can Help in Sensing Instantaneous Heart Rate and Instantaneous Respiratory Rate from Photoplethysmography in a Reliable Way.” Frontiers in Physiology 8 (January 2017): 701. https://doi.org/10.3389/fphys.2017.00701.
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    • Coifman, R. R., S. Steinerberger, and H. T. Wu. “Carrier frequencies, holomorphy. And unwinding.” Siam Journal on Mathematical Analysis 49, no. 6 (January 1, 2017): 4838–64. https://doi.org/10.1137/16M1081087.
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    • Frasch, Martin G., Geraldine B. Boylan, Hau-Tieng Wu, and Declan Devane. “Commentary: Computerised interpretation of fetal heart rate during labour (INFANT): a randomised controlled trial.” Frontiers in Physiology 8 (January 2017): 721. https://doi.org/10.3389/fphys.2017.00721.
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    • Li, Ruilin, Martin G. Frasch, and Hau-Tieng Wu. “Efficient Fetal-Maternal ECG Signal Separation from Two Channel Maternal Abdominal ECG via Diffusion-Based Channel Selection.” Frontiers in Physiology 8 (January 2017): 277. https://doi.org/10.3389/fphys.2017.00277.
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    • Lin, Yu-Ting, and Hau-Tieng Wu. “ConceFT for Time-Varying Heart Rate Variability Analysis as a Measure of Noxious Stimulation During General Anesthesia.” Ieee Transactions on Bio Medical Engineering 64, no. 1 (January 2017): 145–54. https://doi.org/10.1109/tbme.2016.2549048.
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    • Liu, Wen-Te, Hau-Tieng Wu, Jer-Nan Juang, Adam Wisniewski, Hsin-Chien Lee, Dean Wu, and Yu-Lun Lo. “Prediction of the severity of obstructive sleep apnea by anthropometric features via support vector machine.” Plos One 12, no. 5 (January 2017): e0176991. https://doi.org/10.1371/journal.pone.0176991.
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    • Singer, A., and H. T. Wu. “Spectral convergence of the connection Laplacian from random samples.” Information and Inference 6, no. 1 (January 1, 2017): 58–123. https://doi.org/10.1093/imaiai/iaw016.
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    • Wu, Cheng-Ham, Tzung-Dau Wang, Chia-Hung Hsieh, Shih-Hung Huang, Jong-Wei Lin, Szu-Chun Hsu, Hau-Tieng Wu, Yao-Ming Wu, and Tzu-Ming Liu. “Imaging Cytometry of Human Leukocytes with Third Harmonic Generation Microscopy.” Scientific Reports 6 (November 15, 2016): 37210. https://doi.org/10.1038/srep37210.
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    • Marchesini, S., Y. C. Tu, and H. T. Wu. “Alternating projection, ptychographic imaging and phase synchronization.” Applied and Computational Harmonic Analysis 41, no. 3 (November 1, 2016): 815–51. https://doi.org/10.1016/j.acha.2015.06.005.
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    • Lin, Yu-Ting, Patrick Flandrin, and Hau-Tieng Wu. “When Interpolation-Induced Reflection Artifact Meets Time-Frequency Analysis.” Ieee Transactions on Bio Medical Engineering 63, no. 10 (October 2016): 2133–41. https://doi.org/10.1109/tbme.2015.2510580.
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    • Wu, Hau-Tieng, Gregory F. Lewis, Maria I. Davila, Ingrid Daubechies, and Stephen W. Porges. “Optimizing Estimates of Instantaneous Heart Rate from Pulse Wave Signals with the Synchrosqueezing Transform.” Methods of Information in Medicine 55, no. 5 (October 2016): 463–72. https://doi.org/10.3414/me16-01-0026.
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    • O’Neal, Wesley T., Yi Grace Wang, Hau-Tieng Wu, Zhu-Ming Zhang, Yabing Li, Larisa G. Tereshchenko, E Harvey Estes, Ingrid Daubechies, and Elsayed Z. Soliman. “Electrocardiographic J Wave and Cardiovascular Outcomes in the General Population (from the Atherosclerosis Risk In Communities Study).” The American Journal of Cardiology 118, no. 6 (September 2016): 811–15. https://doi.org/10.1016/j.amjcard.2016.06.047.
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    • Chui, C. K., Y. T. Lin, and H. T. Wu. “Real-Time dynamics acquisition from irregular samples-With application to anesthesia evaluation.” Analysis and Applications 14, no. 4 (July 1, 2016): 537–90. https://doi.org/10.1142/S0219530515500165.
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    • Daubechies, Ingrid, Yi Grace Wang, and Hau-tieng Wu. “ConceFT: concentration of frequency and time via a multitapered synchrosqueezed transform.” Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences 374, no. 2065 (April 2016): 20150193. https://doi.org/10.1098/rsta.2015.0193.
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    • El Karoui, N., and H. T. Wu. “Graph connection Laplacian methods can be made robust to noise.” Annals of Statistics 44, no. 1 (February 1, 2016): 346–72. https://doi.org/10.1214/14-AOS1275.
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    • Herry, Christophe L., Marina Cortes, Hau-Tieng Wu, Lucien D. Durosier, Mingju Cao, Patrick Burns, André Desrochers, Gilles Fecteau, Andrew J. E. Seely, and Martin G. Frasch. “Temporal Patterns in Sheep Fetal Heart Rate Variability Correlate to Systemic Cytokine Inflammatory Response: A Methodological Exploration of Monitoring Potential Using Complex Signals Bioinformatics.” Plos One 11, no. 4 (January 2016): e0153515. https://doi.org/10.1371/journal.pone.0153515.
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    • Wu, Hau-Tieng, Han-Kuei Wu, Chun-Li Wang, Yueh-Lung Yang, Wen-Hsiang Wu, Tung-Hu Tsai, and Hen-Hong Chang. “Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.” Plos One 11, no. 6 (January 2016): e0157135. https://doi.org/10.1371/journal.pone.0157135.
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    • Vatter, T., H. T. Wu, V. Chavez-Demoulin, and B. Yu. “Non-parametric estimation of intraday spot volatility: Disentangling instantaneous trend and seasonality.” Econometrics 3, no. 4 (December 1, 2015): 864–87. https://doi.org/10.3390/econometrics3040864.
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    • Sheu, Yae-Lin, Hau-Tieng Wu, and Liang-Yan Hsu. “Exploring laser-driven quantum phenomena from a time-frequency analysis perspective: a comprehensive study.” Optics Express 23, no. 23 (November 2015): 30459–82. https://doi.org/10.1364/oe.23.030459.
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    • Wu, Hau-Tieng, Ronen Talmon, and Yu-Lun Lo. “Assess sleep stage by modern signal processing techniques.” Ieee Transactions on Bio Medical Engineering 62, no. 4 (April 2015): 1159–68. https://doi.org/10.1109/tbme.2014.2375292.
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    • Karoui, N. E., and H. T. Wu. “Graph connection Laplacian and random matrices with random blocks.” Information and Inference 4, no. 1 (March 1, 2015): 1–42. https://doi.org/10.1093/imaiai/iav001.
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    • Wu, H. T., F. Baudin, M. G. Frasch, and G. Emeriaud. “Respiratory variability during NAVA ventilation in children: Authors' reply.” Frontiers in Pediatrics 3, no. FEB (February 1, 2015). https://doi.org/10.3389/fped.2015.00013.
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    • Wang, Yi Grace, Hau-Tieng Wu, Ingrid Daubechies, Yabing Li, E Harvey Estes, and Elsayed Z. Soliman. “Automated J wave detection from digital 12-lead electrocardiogram.” Journal of Electrocardiology 48, no. 1 (January 2015): 21–28. https://doi.org/10.1016/j.jelectrocard.2014.10.006.
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    • Baudin, F., H. T. Wu, A. Bordessoule, J. Beck, P. Jouvet, M. G. Frasch, and G. Emeriaud. “Impact of ventilatory modes on the breathing variability in mechanically ventilated infants.” Frontiers in Pediatrics 2, no. NOV (November 1, 2014). https://doi.org/10.3389/fped.2014.00132.
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    • Sheu, Y. L., L. Y. Hsu, H. T. Wu, P. C. Li, and S. I. Chu. “A new time-frequency method to reveal quantum dynamics of atomic hydrogen in intense laser pulses: Synchrosqueezing transform.” Aip Advances 4, no. 11 (November 1, 2014). https://doi.org/10.1063/1.4903164.
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    • Wu, H. T., Y. H. Chan, Y. T. Lin, and Y. H. Yeh. “Using synchrosqueezing transform to discover breathing dynamics from ECG signals.” Applied and Computational Harmonic Analysis 36, no. 2 (March 1, 2014): 354–59. https://doi.org/10.1016/j.acha.2013.07.003.
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    • Wu, Hau-Tieng, Shu-Shua Hseu, Mauo-Ying Bien, Yu Ru Kou, and Ingrid Daubechies. “Evaluating physiological dynamics via synchrosqueezing: prediction of ventilator weaning.” Ieee Transactions on Bio Medical Engineering 61, no. 3 (March 2014): 736–44. https://doi.org/10.1109/tbme.2013.2288497.
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    • Lin, Y. -. T., H. -. T. Wu, J. Tsao, H. -. W. Yien, and S. -. S. Hseu. “Time-varying spectral analysis revealing differential effects of sevoflurane anaesthesia: non-rhythmic-to-rhythmic ratio.” Acta Anaesthesiologica Scandinavica 58, no. 2 (February 2014): 157–67. https://doi.org/10.1111/aas.12251.
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    • Chen, Y. C., M. Y. Cheng, and H. T. Wu. “Non-parametric and adaptive modelling of dynamic periodicity and trend with heteroscedastic and dependent errors.” Journal of the Royal Statistical Society. Series B: Statistical Methodology 76, no. 3 (January 1, 2014): 651–82. https://doi.org/10.1111/rssb.12039.
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    • Marchesini, S., A. Schirotzek, C. Yang, H. T. Wu, and F. Maia. “Augmented projections for ptychographic imaging.” Inverse Problems 29, no. 11 (November 1, 2013). https://doi.org/10.1088/0266-5611/29/11/115009.
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    • Wu, H. T. “Instantaneous frequency and wave shape functions (I).” Applied and Computational Harmonic Analysis 35, no. 2 (September 1, 2013): 181–99. https://doi.org/10.1016/j.acha.2012.08.008.
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    • Thakur, G., E. Brevdo, N. S. Fučkar, and H. T. Wu. “The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness properties and new paleoclimate applications.” Signal Processing 93, no. 5 (May 1, 2013): 1079–94. https://doi.org/10.1016/j.sigpro.2012.11.029.
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    • Auger, F., P. Flandrin, Y. T. Lin, S. McLaughlin, S. Meignen, T. Oberlin, and H. T. Wu. “Time-frequency reassignment and synchrosqueezing: An overview.” Ieee Signal Processing Magazine 30, no. 6 (January 1, 2013): 32–41. https://doi.org/10.1109/MSP.2013.2265316.
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    • Cheng, M. Y., and H. T. Wu. “Local linear regression on manifolds and its geometric interpretation.” Journal of the American Statistical Association 108, no. 504 (January 1, 2013): 1421–34. https://doi.org/10.1080/01621459.2013.827984.
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    • Singer, A., and H. -. T. Wu. “Two-Dimensional Tomography from Noisy Projections Taken at Unknown Random Directions.” Siam Journal on Imaging Sciences 6, no. 1 (January 2013): 136–75. https://doi.org/10.1137/090764657.
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    • Wang, Yu-Ming, Hau-Tieng Wu, Eng-Yen Huang, Yu Ru Kou, and Shu-Shya Hseu. “Heart rate variability is associated with survival in patients with brain metastasis: a preliminary report.” Biomed Research International 2013 (January 2013): 503421. https://doi.org/10.1155/2013/503421.
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    • Singer, A., and H. -. T. Wu. “Vector Diffusion Maps and the Connection Laplacian.” Communications on Pure and Applied Mathematics 65, no. 8 (August 2012). https://doi.org/10.1002/cpa.21395.
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    • Thakur, G., and H. T. Wu. “Synchrosqueezing-based recovery of instantaneous frequency from nonuniform samples.” Siam Journal on Mathematical Analysis 43, no. 5 (November 21, 2011): 2078–95. https://doi.org/10.1137/100798818.
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    • Singer, Amit, and Hau-Tieng Wu. “Orientability and Diffusion Maps.” Applied and Computational Harmonic Analysis 31, no. 1 (July 2011): 44–58. https://doi.org/10.1016/j.acha.2010.10.001.
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    • Wu, H. T., P. Flandrin, and I. Daubechies. “One or two frequencies? the synchrosqueezing answers.” Advances in Adaptive Data Analysis 3, no. 1–2 (April 1, 2011): 29–39. https://doi.org/10.1142/S179353691100074X.
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    • Daubechies, Ingrid, Jianfeng Lu, and Hau-Tieng Wu. “Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool.” Applied and Computational Harmonic Analysis 30, no. 2 (March 2011): 243–61. https://doi.org/10.1016/j.acha.2010.08.002.
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    • Chen, Ziyu, and Hau-Tieng Wu. “When Ramanujan meets time-frequency analysis in complicated time series analysis,” n.d.
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    • Chiu, Neng-Tai, Stephanie Huwiler, M Laura Ferster, Walter Karlen, Hau-Tieng Wu, and Caroline Lustenberger. “Get rid of the beat in mobile EEG applications: A framework towards automated cardiogenic artifact detection and removal in single-channel EEG,” n.d. https://doi.org/10.1101/2021.02.09.430184.
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    • Chung, Yu-Min, Chuan-Shen Hu, Yu-Lun Lo, and Hau-Tieng Wu. “A persistent homology approach to heart rate variability analysis with an application to sleep-wake classification,” n.d.
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    • Cicone, Antonio, and Hau-Tieng Wu. “Convergence analysis of Adaptive Locally Iterative Filtering and SIFT method,” n.d.
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    • Ding, Xiucai, and Hau-Tieng Wu. “Phase transition of graph Laplacian of high dimensional noisy random point cloud,” n.d.
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    • Gavish, Matan, Ronen Talmon, Pei-Chun Su, and Hau-Tieng Wu. “Optimal Recovery of Mahalanobis Distance in High Dimension,” n.d.
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    • Malik, John, Yu-Ting Lin, Ronen Talmon, and Hau-Tieng Wu. “Unsupervised ensembling of multiple software sensors: a new approach for electrocardiogram-derived respiration using one or two channels,” n.d.
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    • Sourisseau, Matt, Hau-Tieng Wu, and Zhou Zhou. “Inference of synchrosqueezing transform -- toward a unified statistical analysis of nonlinear-type time-frequency analysis,” n.d.
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    • Sourisseau, Matt, Yu Guang Wang, Robert S. Womersley, Hau-Tieng Wu, and Wei-Hsuan Yu. “Improve Concentration of Frequency and Time (Conceft) by Novel Complex Spherical Designs,” n.d. https://doi.org/10.1101/2020.11.23.394007.
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    • Steinerberger, Stefan, and Hau-tieng Wu. “On Zeroes of Random Polynomials and an Application to Unwinding.” International Mathematics Research Notices, n.d. https://doi.org/10.1093/imrn/rnz096.
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    • Wang, Yu Guang, Robert S. Womersley, Hau-Tieng Wu, and Wei-Hsuan Yu. “Numerical computation of triangular complex spherical designs with small mesh ratio,” n.d.
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    • Wu, H., and L. Su. “Fetal ECG extraction from single-lead abdominal ECG by de-shape short time Fourier transform and nonlocal median.” Front. Appl. Math. Stat., n.d.
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    • Zhang, Jin-Ting, Ming-Yen Cheng, Chi-Jen Tseng, and Hau-Tieng Wu. “A New Test for One-Way ANOVA with Functional Data and Application to Ischemic Heart Screening,” n.d.
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  • Conference Papers

    • Thai, D. H., H. T. Wu, and D. B. Dunson. “Locally convex kernel mixtures: Bayesian subspace learning.” In Proceedings  18th Ieee International Conference on Machine Learning and Applications, Icmla 2019, 272–75, 2019. https://doi.org/10.1109/ICMLA.2019.00051.
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    • Martinez, N., M. Bertran, G. Sapiro, and H. T. Wu. “Non-Contact Photoplethysmogram and Instantaneous Heart Rate Estimation from Infrared Face Video.” In Proceedings  International Conference on Image Processing, Icip, 2019-September:2020–24, 2019. https://doi.org/10.1109/ICIP.2019.8803109.
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    • Kao, S. L., H. W. Lien, T. C. Liu, H. T. Wu, T. Y. Fang, P. C. Wang, and Y. W. Liu. “Meniere's disease prognosis by learning from transient-evoked otoacoustic emission signals.” In Proceedings of the International Congress on Acoustics, 2019-September:6505–12, 2019. https://doi.org/10.18154/RWTH-CONV-239245.
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    • Liu, T. C., H. T. Wu, Y. H. Chen, T. Y. Fang, P. C. Wang, and Y. W. Liu. “Analysis of click-evoked otoacoustic emissions by concentration of frequency and time: Preliminary results from normal hearing and Ménière's disease ears.” In Aip Conference Proceedings, Vol. 1965, 2018. https://doi.org/10.1063/1.5038538.
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    • Wu, J. C., C. W. Wang, Y. H. Huang, H. T. Wu, P. C. Huang, and Y. L. Lo. “A Portable Monitoring System with Automatic Event Detection for Sleep Apnea Level-IV Evaluation.” In Proceedings  Ieee International Symposium on Circuits and Systems, Vol. 2018-May, 2018. https://doi.org/10.1109/ISCAS.2018.8351221.
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    • Lederman, R. R., R. Talmon, H. T. Wu, Y. L. Lo, and R. R. Coifman. “Alternating diffusion for common manifold learning with application to sleep stage assessment.” In Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing  Proceedings, 2015-August:5758–62, 2015. https://doi.org/10.1109/ICASSP.2015.7179075.
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    • Lederman, Roy R., Ronen Talmon, Hau-tieng Wu, Yu-Lun Lo, Ronald R. Coifman, and Ronald R. IEEE. “ALTERNATING DIFFUSION FOR COMMON MANIFOLD LEARNING WITH APPLICATION TO SLEEP STAGE ASSESSMENT.” In 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), 5758–62, 2015.
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• Teaching & Mentoring
• 

  Recent Courses

  • MATH 342D: Statistics 2020
  • MATH 494: Research Independent Study 2020
  • MATH 561: Numerical Linear Algebra, Optimization and Monte Carlo Simulation 2020
  • STA 250D: Statistics 2020
  • STA 790-1: Special Topics in Statistics 2020
  • MATH 230: Probability 2019
  • MATH 393: Research Independent Study 2019
  • MATH 493: Research Independent Study 2019
  • MATH 531: Real Analysis I 2019
  • STA 230: Probability 2019
  • STA 993: Independent Study 2019

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