## Simon Foucart## Professor## Presidential Impact Fellow## Department of Mathematics## Texas A&M University |
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Current Research Activity:

Mathematical Data Science,
Approximation-Theory Flavored

(Compressive Sensing included)

- Classical Approximation Theory
- Sparse and Structured Recovery
- (Deep) Learning
- Scientific Computing
- Applications in Engineering and Bioinformatics

- Reading seminar on Data Science and Compressive Sensing (link)

- Students:
Chunyang Liao;
Bolong Ma;
Ryan Malthaner;
Tushar Pandey;
Srinivas Subramanian

Prospective - apply via the standard departmental process (link) - Postdocs:
Josiah Park

Prospective - apply via mathjobs.org

S. F., H. Rauhut,
A mathematical introduction to compressive sensing.
Applied and Numerical Harmonic Analysis, Birkhäuser. List of errata |
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Approximation Theory XV: San Antonio 2016, Springer Proceedings in Mathematics & Statistics, vol 201, 61--104.

- S. F., C. Liao, S. Shahrampour, Y. Wang, Learning from non-random data in Hilbert spaces: an optimal recovery perspective. (pdf) (reproducible)
- M. Ettehad, S. F., Instances of computational optimal recovery: dealing with observation errors. (pdf) (reproducible)

- S. F., J. B. Lasserre,
Determining projection constants of univariate polynomial spaces.

Journal of Approximation Theory, 235, 74--91, 2018. (doi) (pdf) - R. Baraniuk, S. F., D. Needell, Y. Plan, M. Wootters,
Exponential decay of reconstruction error from binary measurements of sparse signals.

IEEE Transactions on Information Theory, 63/6, 3368--3385, 2017. (doi) (pdf) - D. Koslicki, S. F., G. Rosen,
Quikr: a method for rapid reconstruction of bacterial communities via compressive sensing.
(doi)
(pdf)

Bioinformatics, 29/17, 2096--2102, 2013. - S. F.,
Hard thresholding pursuit: an algorithm for compressive sensing.
(doi)
(pdf)

SIAM Journal on Numerical Analysis, 49/6, 2543--2563, 2011. - S. F., A. Pajor, H. Rauhut, T. Ullrich,
The Gelfand widths of $\ell_p$-balls for $0 < p \le 1$.
(doi)
(pdf)

Journal of Complexity, 26/6, 629--640, 2010.

**Foundations and Methods of Approximation**(syllabus) (notes) (codes)

**Topics in Mathematical Data Science**(supplanted soon, restricted access) (pdf) (codes) (old pdf)**Matrix Analysis**(a few lectures missing) (pdf)**Mathematics of Genome Analysis**(very incomplete, restricted access) (pdf)**Problem Solving Competitions**(selected topics) (pdf)**Compressed Sensing**(supplanted by the book written with H. Rauhut) (pdf)**Numerical Mathematics**(some updates required) (pdf)

Go to my Github page for download.

- MinProj
- This is a MATLAB package that computes exact projection constants and minimal projections in coordinate spaces and matrix spaces by solving linear programs, as well as approximate projection constants and minimal projections in polynomial spaces by solving linear or semidefinite programs. It relies on the external packages CVX and Chebfun.
- Basc
- This is a MATLAB package that computes Best Approximations by Splines under Constraints relative to various norms. Relying on the external packages CVX and Chebfun, it is based on a reformulation of constrained approximation problems as semidefinite programs. (demo)
- SplineDim
- This is a collection of SAGE routines designed to generate formulas for the dimension of multivariate spline spaces over specific partitions. It is based on Hilbert series computations. The core of the code was written by P. Clarke.
- Quikr and WGSQuikr
- These computational packages determine the composition of bacteria in an environmental sample analyzed by 16S rRNA amplicon and whole-genome shotgun sequencing technologies. The packages were assembled by D. Koslicki, who also set up this Galaxy server.
- HTP
- These are three MATLAB routines to be used when trying to recover a sparse vector x or a row-sparse matrix X from the incomplete linear measurements y=Ax or Y=AX. They are implementations of the HTP, FHTP, and SHTP algorithms.
- Allometry
- This is a collection of MATLAB routines to be used for the computation of exact constants in Banach space geometry.

- 2001-05: PhD, University of Cambridge.
- 2000-01: Part III of Math Tripos (Distinction), University of Cambridge.
- 1998-01: Masters of Engineering, Ecole Centrale Paris.

- 2019-now: Professor of Mathematics, Texas A&M University.
- 2015-19: Associate Professor of Mathematics, Texas A&M University.
- 2013-15: Assistant Professor of Mathematics, University of Georgia.
- 2010-13: Assistant Professor of Mathematics, Drexel University.
- 2009-10: Postdoctoral Researcher, University of Paris 6.
- 2006-09: Postdoctoral Researcher, Vanderbilt University.

- January-June 2019: University of Wisconsin-Madison.
- June 2018: LAAS-CNRS, Toulouse.
- December 2017: Hong Kong University of Science and Technology.
- May-June 2015: University of South Florida.
- July-August 2009: University of Bonn.

- 2019: Recipient of a Presidential Impact Fellowship, Texas A&M University.
- 2012: Recipient of the Antelo Devereux Award for Young Faculty, Drexel University.
- 2010: Journal of Complexity Best Paper Award.

- Josiah Park (Postdoc, Aug 2020-).
- Mahmood Ettehad (Grad student, Aug 2016-Jul 2020, now postdoc at the IMA, University of Minnesota).
- Richard G. Lynch (Postdoc, Aug 2016-Jun 2019, now Instructional Assistant Professor at Texas A&M University).
- Jean-Luc Bouchot (Postdoc, Nov 2012-Aug 2014, now Assistant Professor at Beijing Institute of Technology).
- David Koslicki (Postdoc, Jan-Sep 2012, now Associate Professor at Pennsylvania State University).
- Michael Minner (Grad Student, Sep 2012-Mar 2016, now at Sandia National Lab).

- Journal of Approximation Theory (Aug 2017-now).
- Sampling Theory, Signal Processing, and Data Analysis (Jun 2020-now).
- Journal of Numerical Mathematics (May 2021-now).

Consultation hours: T 2:15pm-3:00pm, W 8:30am-9:15am, and by appointment.

Office location:
502D Blocker Building

Ireland Street

College Station

Texas

Mailing address:
Texas A&M University

Department of Mathematics

3368 TAMU

College Station, TX 77843-3368

E-mail: foucart@tamu.edu or simon.foucart@centraliens.net