This is a webpage for Adam Marcus.

Specifically, Adam W. Marcus the mathematician, not to be confused with (for example)

About me:

I received my B.A./M.A. in Mathematics from Washington University in St. Louis in 2003 and my Ph.D. in Algorithms, Combinatorics, and Optimization under the supervision of Prasad Tetali from Georgia Tech in 2008. I then spent 4 years as a Gibbs Assistant Professor in Applied Mathematics at Yale University under the supervision of Daniel Spielman, followed by 3 years as Chief Scientist at a machine learning-driven startup called Crisply. I then spent 5 years as an Assistant Professor in the Mathematics Department and Program in Applied and Computational Mathematics at Princeton University.

I currently hold the Chair of Combinatorial Analysis in the School of Mathematics at EPFL in Lausanne, Switzerland. You can find my contact information here.

For potential students:

Students wishing to come to EPFL for a Ph.D. need to apply to a doctoral program. The mathematics program is EDMA and the computer science one is EDIC. Part of the application process will ask you to list faculty that you would have interest in working with. You should put my name if you want me to see the application. My ability to take students changes all of the time, so if you do not hear from me, it is very likely that I am not able to take any students at that time.

For those looking to come to EPFL for a summer project, the only program that I am aware of is this one in the computer science department.

Research interests:

When I am pretending to be a mathematician, my main research interests lie in various areas of combinatorics. In particular, I tend to like things that are constrained in ways that current tools are not equipped to deal with (like restricted orderings and, more recently, dimensionality restrictions).

When I am pretending to be a computer scientist, my interests lie in areas that involve algorithms and computation in high-dimensional vector spaces. In particular, I have a growing interest in a number of topics in machine learning, computational geometry, and optimization.

When I am pretending to be a Frankenstein-like combination of the two, my interests lie in what I like to call "combinatorial linear algebra," a mixing of ideas from the theory of stable polynomials, convex geometry, geometric functional analysis, convex programming, and (of course) linear algebra and combinatorics.

Teaching interests:

My primary interest here lies in creating innovative curricula for general education mathematics courses. There are many practical skills that mathematics can teach someone (problem solving, understanding of probability and statistics, etc) and the current paradigm does not address these as adequately as it could.


I currently advise two graduate students from my time at Princeton (both in the PACM program): Aurelien Gribinski and Benno Mirabelli.


My research at Princeton was supported by National Science Foundation CAREER grant, Grant No. DMS-1552520.

My time at the Institute for Advanced Study was supported by a Von Neumman Fellowship, National Science Foundation Grant No. DMS-1128155.

My research at Yale was funded in part by the National Science Foundation under a Mathematical Sciences Postdoctoral Research Fellowship, Grant No. DMS-0902962.

Some slides from previous talks:

  1. Interlacing families and bipartite Ramanujan graphs PDF
  2. Interlacing families and Kadison-Singer PDF
  3. A more general ``method of interlacing polynomials'' talk PDF
  4. Polynomials and (finite) free probability PDF

Some actual talks:

  1. Non-commutative probability for computer scientists: Note that the use of the term "computer scientist" here is short for "any person that would like to see how results from non-commutative probability can be used for their problems before investing any serious effort in learning any details." There is no actual computer science background needed.

  2. Bounding roots of polynomials (and applications): A follow-up of the previous talk, it shows how to combine the ideas of non-commutative probability with polynomial convolutions to say non-trivial things in (for example) spectral graph theory.


(in reverse chronological order of writing, not publication) [ With short descriptions when titles are ambiguous. ]
  1. A. Gribinski, A. W. Marcus, A rectangular convolution for polynomials. arXiv
    [ Introduces convolutions for general singular value problems, with bounds on the largest root. ]

  2. A. W. Marcus, N. Srivastava, The solution of the Kadison-Singer problem, Current Developments in Mathematics, 2016. arXiv

  3. V. Gorin, A. W. Marcus, Crystallization of random matrix orbits, International Mathematics Research Notices, 2020 (3), 883-913. arXiv

  4. A. W. Marcus, A determinantal identity for the permanent of a rank 2 matrix, preprint. PDF

  5. A. W. Marcus, W. Yomjinda, Analysis of rank 1 perturbations in general β ensembles, preprint. PDF

  6. A. W. Marcus, Discrete unitary invariance. arXiv

  7. A. W. Marcus, Polynomial convolutions and (finite) free probability, preprint. PDF
    [ Shows that the finite free convolutions associated to the eigenvalues of Hermitian matrices, in the appropriate limit, become free convolutions. ]

  8. M. Bownik, P. Casazza, A. W. Marcus, D. Speegle, Improved bounds in Weaver and Feichtinger conjectures, Crelles Journal, 2016. arXiv

  9. A. W. Marcus, D. A. Spielman, N. Srivastava, Interlacing families IV: bipartite Ramanujan graphs of all sizes, FOCS (2015). arXiv
    [ Uses finite free convolutions to show the existence of Ramanujan graphs. Turned into a construction by Cohen. ]

  10. A. W. Marcus, D. A. Spielman, N. Srivastava, Finite free convolutions of polynomials, submitted. arXiv
    [ Original paper defining finite free convolutions (for eigenvalues of Hermite matrices and singular values of square matrices), with bounds on the largest root. ]

  11. A. W. Marcus, D. A. Spielman, N. Srivastava, Ramanujan graphs and the solution of the Kadison-Singer problem, Proc. ICM, Vol III (2014), 375-386. arXiv

  12. A. W. Marcus, D. A. Spielman, N. Srivastava, Interlacing families III: improved bounds for restricted invertibility, accepted (Isr. J. Math.). arXiv
    [ Arguably the first appearance of finite free convolutions. ]

  13. A. W. Marcus, D. A. Spielman, N. Srivastava, Interlacing families II: mixed characteristic polynomials and the Kadison-Singer problem, Ann. of Math. 182-1 (2015), 327-350. arXiv

  14. A. W. Marcus, D. A. Spielman, N. Srivastava, Interlacing families I: bipartite Ramanujan graphs of all degrees, Ann. of Math. 182-1 (2015), 307-325. (preliminary version appeared in FOCS 2013) arXiv
    [ Uses 2-lifts to show existence of Ramanujan graphs. No construction known. ]

  15. M. Madiman, A. W. Marcus, P. Tetali, Entropy and set cardinality inequalities for partition-determined functions, Random Struct. Algorithms 40 (2012), no. 4, 399-424. PDF

  16. M. Klazar, A. Marcus, Extensions of the linear bound in the Füredi-Hajnal conjecture, Adv. in Appl. Math. 38 (2006), no. 2, 258-266. PDF PS BibTeX entry

  17. A. Marcus, G. Tardos, Intersection reverse sequences and geometric applications, J. Combin. Theory Ser. A 113 (2006), no. 4, 675-691. PDF PS BibTeX entry
    (Preliminary version appeared in GD 2004 (J. Pach, ed.), LNCS, no. 3383, 2004, 349-359)

  18. A. Marcus, G. Tardos, Excluded permutation matrices and the Stanley-Wilf conjecture, J. Combin. Theory Ser. A 107 (2004), no. 1, 153-160. PDF PS BibTeX entry

  19. R. Kawai, A. Marcus, Negative Conductance in Two Finite-size Coupled Brownian Motor Models, manuscript (2000). PDF PS BibTeX entry

  20. J. Goodwin, D. Johnston, A. Marcus, Radio Channel Assignments, UMAP Journal 21.3 (Fall 2000), 369-378. Preprint version: PDF PS BibTeX entry **DISCLAIMER**: This paper was written as a contest entry to the MCM 2000 competition, which took place over a span of 4 days (not much time). It is here because it has some mathematical value, but there are some mistakes so please read at your own risk!!

Links related to my research:

Other (still mostly math) links: