Math @ Duke
Ingrid Daubechies, James B. Duke Distinguished Professor of Mathematics and Professor of Electrical and Computer Engineering
- Contact Info:
Teaching (Fall 2021):
Teaching (Spring 2022):
- MATH 635.01, FUNCTIONAL ANALYSIS
- Gross Hall 318, MW 05:15 PM-06:30 PM
- MATH 240.01, INTRO APPLIED MATH
- Gross Hall 318, WF 01:45 PM-03:00 PM
|Ph.D.||Vrije Universiteit Brussel (Belgium)||1980|
- 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
- Cheng, C; Daubechies, I; Dym, N; Lu, J, Stable phase retrieval from locally stable and conditionally connected measurements,
Applied and Computational Harmonic Analysis, vol. 55
pp. 440-465 [doi] [abs]
- Fornasier, M; Vybíral, J; Daubechies, I, Robust and resource efficient identification of shallow neural networks by fewest samples,
Information and Inference, vol. 10 no. 2
pp. 625-695 [doi] [abs]
- Fulwood, EL; Shan, S; Winchester, JM; Kirveslahti, H; Ravier, R; Kovalsky, S; Daubechies, I; Boyer, DM, Insights from macroevolutionary modelling and ancestral state reconstruction into the radiation and historical dietary ecology of Lemuriformes (Primates, Mammalia).,
Bmc Ecology and Evolution, vol. 21 no. 1
pp. 60 [doi] [abs]
- Daubechies, I; DeVore, R; Foucart, S; Hanin, B; Petrova, G, Nonlinear Approximation and (Deep) ReLU Networks,
(January, 2021) [doi] [abs]
- Pu, W; Sober, B; Daly, N; Higgitt, C; Daubechies, I; Rodrigues, MRD, A connected auto-encoders based approach for image separation with side information: With applications to art investigation,
2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), vol. 2020-May
pp. 2213-2217, ISBN 9781509066315 [doi] [abs]
- Recent Grant Support
- RTG: Training Tomorrow's Workforce in Analysis and Applications, National Science Foundation, 2021/07-2026/06.
- Simons Foundation - Math + X Investigators, Simons Foundation, 2016/07-2026/06.
- Collaborative Reseach: Transferable, Hierarchical, Expressive, Optimal, Robust, Interpretable NETworks (THEORINET), National Science Foundation, 2020/09-2025/08.
- Collaborative Reseach: Transferable, Hierarchical, Expressive, Optimal, Robust, Interpretable NETworks (THEORINET), Simons Foundation, 2020/09-2025/08.
- HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms, National Science Foundation, 2019/10-2022/09.
- New Approaches for Better Spatial Frequency Localization in 2 and 3-Dimensional Data Analysis, National Science Foundation, 1516988, 2015/09-2020/08.
Duke University, Box 90320
Durham, NC 27708-0320