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Math @ Duke





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Ingrid Daubechies, James B. Duke Professor of Mathematics and Professor of Electrical and Computer Engineering

Ingrid Daubechies
Contact Info:
Office Location:  111 Physics
Office Phone:  (919) 660-2805
Email Address: send me a message
Web Pages:  https://math.duke.edu/people/ingrid-daubechies
https://ece.duke.edu/faculty/ingrid-daubechies

Teaching (Spring 2019):

  • MATH 240.01, INTRO APPLIED MATH Synopsis
    Gross Hall 318, TuTh 01:25 PM-02:40 PM
Education:

Ph.D.Vrije Universiteit Brussel (Belgium)1980
Specialties:

Applied Math
Analysis
Keywords:

Algorithms • Analysis of Variance • Animals • Art--Conservation and restoration • Brain • Brain Mapping • Cell Line • Computer Simulation • Diet • DNA Replication • Genome, Viral • Herpesviridae • Humans • Image Interpretation, Computer-Assisted • Image Processing, Computer-Assisted • Industry • Inverse problems • Machine learning • Magnetic Resonance Imaging • Microscopy, Fluorescence • Models, Anatomic • Models, Biological • Models, Theoretical • Molar • Reproducibility of Results • Signal Processing, Computer-Assisted • Strepsirhini • Swine • Tooth Crown • Tooth Wear • Tupaia • Wavelets (Mathematics) • X-Ray Microtomography

Postdocs Mentored

  • Tingran Gao (2015/06-present)  
  • Bruno Cornelis (2014 - 2015)  
  • Jameson Cahill (2013 - 2015)  
  • Grace Wang (2012 - 2015)  
  • Rayan Saab (January 01, 2012 - July 31, 2013)  
Recently Featured in:

Recent Publications   (More Publications)

  1. Yin, R; Daubechies, I, Directional Wavelet Bases Constructions with Dyadic Quincunx Subsampling, Journal of Fourier Analysis and Applications, vol. 24 no. 3 (June, 2018), pp. 872-907, Springer Nature [doi]
  2. Gao, T; Yapuncich, GS; Daubechies, I; Mukherjee, S; Boyer, DM, Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation., Anatomical Record (Hoboken, N.J. : 2007), vol. 301 no. 4 (April, 2018), pp. 636-658 [doi]  [abs]
  3. Xu, J; Yang, H; Daubechies, I, Recursive Diffeomorphism-Based Regression for Shape Functions, Siam Journal on Mathematical Analysis, vol. 50 no. 1 (January, 2018), pp. 5-32, Society for Industrial & Applied Mathematics (SIAM) [doi]  [abs]
  4. Alaifari, R; Daubechies, I; Grohs, P; Yin, R, Stable Phase Retrieval in Infinite Dimensions, Foundations of Computational Mathematics (January, 2018), Springer Nature America, Inc [doi]  [abs]
  5. Alaifari, R; Daubechies, I; Grohs, P; Thakur, G, Reconstructing Real-Valued Functions from Unsigned Coefficients with Respect to Wavelet and Other Frames, Journal of Fourier Analysis and Applications, vol. 23 no. 6 (December, 2017), pp. 1480-1494 [doi]
Recent Grant Support

  • Simons Foundation - Math + X Investigators, Simons Foundation, 2016/07-2021/06.      
  • New Approaches for Better Spatial Frequency Localization in 2 and 3-Dimensional Data Analysis, National Science Foundation, 1516988, 2015/09-2019/08.      
  • New Approaches for Better Spatial Frequency Localization in 2 and 3-Dimensional Data Analysis, National Science Foundation, 1516988, 2015/09-2018/08.      
  • Structured Dictionary Models and Learning for High Resolution Images, National Science Foundation, 2013/08-2017/07.      
  • Structured Dictionary Models and Learning for High Resolution Images, National Science Foundation, DMS-1320655, 2013/08-2017/07.      
  • The Keck Automated Phenotyping Algorithm Initiative (KAPAI), W.M. Keck Foundation, 2014/08-2016/09.      
  • Discovery of Empirical Components by Information Theory, Random Matrix Theory, and Computational Topology, Princeton University, 00002113, 2013/02-2016/02.      

 

dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320