[HN Gopher] Ingrid Daubechies Awarded National Medal of Science
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Ingrid Daubechies Awarded National Medal of Science
Author : sedtacet
Score : 115 points
Date : 2025-01-11 10:35 UTC (12 hours ago)
(HTM) web link (today.duke.edu)
(TXT) w3m dump (today.duke.edu)
| _kb wrote:
| For those unfamiliar with her work, there's a very approachable
| lecture on wavelets and their common applications here:
| https://www.youtube.com/watch?v=a90kMHY0Uto.
| anyfoo wrote:
| Thank you for that, I was looking for exactly this. I consider
| myself fairly competent in a bunch of DSP topics (Fourier and
| Laplace, and respectively the z-transform, are no mystery to
| me), but I have a few problems to solve where I feel that
| wavelets could be very beneficial.
| kkylin wrote:
| Here is the full list of this year's awardees:
|
| https://new.nsf.gov/honorary-awards/national-medal-science#n...
|
| (Also includes National Medal of Technology and Innovation.)
|
| And if you ever get the chance to hear Daubechies speak, go! She
| gives very clear and accessible talks, and is also very
| approachable.
| szvsw wrote:
| Daubechies wavelets are such incredibly strange and beautiful
| objects, particularly for how _deviant_ they are compared to
| everything you are typically familiar with when you are starting
| your signal processing journey... if it's possible for a
| mathematical construction to be punk, then it would be the
| Daubechies wavelets.
| ska wrote:
| Well deserved!
| littlestymaar wrote:
| Almost 40 years after the creation of Daubechies wavelets, I know
| we should wait a bit before awarding people since we can't always
| know in advance what would stick as important and what would just
| be temporary hype, but 40 years is too much IMHO...
| nimish wrote:
| Well deserved
| cosmic_quanta wrote:
| This award is well-deserved!
|
| I was inspired by her work in the 2010s and have since used the
| wavelets to denoise time-series with great success [0]. I believe
| that learning about wavelet transforms is both beneficial in
| itself, but also beneficial in understand the ubiquitous Fourier
| transform.
|
| [0]: https://laurentrdc.xyz/posts/wavelet-filtering.html
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