Raphael Arkady Meyer

I recently got a Ph.D. from NYU Tandon School of Engineering, advised by Christopher Musco and part of the Algorithms and Foundations Group.

I research problems in mathematical computing from the perspective of theoretical computer science.

In the summer of 2022, I visited Michael Kapralov's group at EPFL and Haim Avron's group at TAU.

Links: Google Scholar, dblp, Github, Zoom Room

My recent publications have looked at:

Of course, I am interested in problems beyond these areas, and if you want to work with me on a problem, send me an email: ram900@nyu.eduram900@nyu.edu


  • I'll be joining Caltech as a postdoc in Joel Tropp's group this fall!

  • I've been awarded the Pearl Brownstein Doctoral Research Award (i.e. best dissertation award) for my research! Big thanks to the Tandon CSE department for awarding this to me, and congrats to the other awardees, Aecios and Mengwei!

  • I gave a talk at the Center for Communications Research on Trace Estimation and Kronecker-Trace Estimation.


April 2024

  • I just successfully defended my thesis, on April 16th 2024! See details about my talk here: link.

March 2024

  • The Responsible AI Lab at NYU Tandon (who I have been a part of for the past two years) wrote a spotlight on me! Thanks to Caterina and the R/AI team for writing this up. See the short interview here: link.

January 2024

November 2023

October 2023

September 2023

May 2023

March 2023

  • I gave two talks at the NYU / UMass Quantum Linear Algebra reading group.

  • I gave a talk at the BIRS Perspectives on Matrix Computations about my new work on Krylov methods.

January 2023

November 2022

  • I gave a talk at the TCS Seminar at Purdue in early November to present my new research on the role of block size in Krylov Methods.

October 2022

  • New paper accepted at SODA 2023: Near-Linear Sample Complexity for LpL_p Polynomial Regression! I just gave a talk on it last week Friday at the Grad Student Seminar at CDS (at NYU).

September 2022

  • I gave a talk at GAMM ANLA on the role of block size in Krylov Methods for low-rank approximation. A preprint will be available very soon, but until then you can check out my slides for a preview! Slides

July 2022

  • I gave a talk at the SIAM Annual Meeting Minisymposium on Matrix Functions, Operator Functions, and Related Approximation Methods. Thanks to Heather, Andrew, and Ke for organizing!

June 2022

May 2022

  • I recently organized a mini-conference for NYU CS Theory researchers to present their "Pandemic Papers" in-person. Thanks to everyone who showed up and made it a success! More details here

  • I'm honored to be awarded the Deborah Rosenthal, MD Award for Best Quals Examination in 2022, for my presentation Towards Optimal Spectral Sum Estimation in the Matrix-Vector Oracle Model.

April 2022

  • I'm honored to be a ICLR 2022 Highlighted Reviewer.



[1] Slides
[2] Code available on github \cdot Slides using TCS language \cdot Slides using Applied Math language
[3] Slides
[4] Poster
[5] Code available on github \cdot Landscape Poster \cdot Portrait Poster \cdot 4min Slides \cdot 12min Slides \cdot 25min Slides \cdot 35min Slides \cdot 1hr Slides
[6] Slides
[7] Poster \cdot Slides.

Talks & Presentations

To date, I have presented every paper I published at the associated conference. This is a list of other talks or presentations I have given.

[8] Slides available here. Video starts at 1:04:55 here.

[9] Assets available in the Publications section.

[10] Link to relevant paper here.
[11] Link to relevant paper here. My slides available here.
[12] Link to the original paper here. My slides available here.


I really enjoy teaching, and have been a TA for a few courses now:


Service outside of reviewing:

  1. Organizer for the Minisymposium "The Matrix-Vector Complexity of Linear Algebra" at SIAM-NNP 2023

  2. Organizer for NYU TCS "Pandemic Presentations" Day

  3. Organizer for NYU Tandon Theory Reading Group

Service as a reviewer:

  1. NeurIPS 2024 Reviewer

  2. FOCS 2024 External Reviewer

  3. IMA Journal of Numerical Analysis 2024 Reviewer

  4. ICALP 2024 External Reviewer

  5. ICML 2024 Reviewer

  6. IJCAI 2024 Reviewer

  7. ICLR 2024 Reviewer

  8. NeurIPS 2023 Reviewer

  9. TMLR 2023 Reviewer

  10. ICLR 2023 Reviewer

  11. SODA 2023 External Reviewer

  12. NeurIPS 2022 Reviewer

  13. ICML 2022 Reviewer

  14. STOC 2022 External Reviewer

  15. ICLR 2022 Reviewer*

  16. NeurIPS 2021 Reviewer*

  17. ISIT 2017 External Reviewer

* Denotes Highlighted / Outstanding Reviewer