Shashwat Silas

Photo of Shashwat

PhD Student, Stanford University

Google Scholar

silas — at — stanford — dot — edu

About Me

I am a PhD student in Computer Science at Stanford University. I am very fortunate to be advised by Prof. Mary Wootters. Part of my PhD was by funded by a Google Graduate Fellowship in the School of Engineering.

My research interests lie in combinatorics, algorithms and error-correcting codes. Starting April, I will be working at Google, where I will think about topics related to distributed storage and reliability of SSDs.

Outside of Math/CS, I love cooking, playing tennis, and learning about wine.

Education

Stanford University
PhD, Computer Science
Advisor: Mary Wootters
2016 — 2021.

University of Cambridge
MPhil, Computer Science, Distinction
2015 — 2016.

Brown University
Sc.B. Mathematics, Magna cum laude & Phi Beta Kappa
2011 — 2015.

Teaching

I have been a TA (and sometimes Head TA) for the Design and Analysis of Algorithms course and the Randomized Algorithms course at both Stanford and Brown. I have also been a TA for various courses in Probability, Galois Theory, Representation Theory and Linear Algebra at Brown. At Stanford Wine Society, I also teach blind wine tasting.

Professional Service

I have been a reviewer for ESA 2015, RANDOM 2020, FOCS 2020, ISIT 2021 and IEEE Transactions on Information Theory. I was the student coordinator of Stanford Theory Seminar for 2017-18.

Publications

Real-time oblivious erasure correction with linear time decoding and constant feedback
Shashwat Silas.
arXiv: 2101.11136 | In Review.

Sharp threshold rates for random codes
Venkat Guruswami, Jonathan Moshieff, Nicolas Resch, Shashwat Silas, Mary Wootters.
arXiv: 2009.04553 | ITCS 2021.
I gave a short talk about this work at ITCS in January 2021: Talk.

Flash translation layer design using reinforcement learning
Shashwat Silas, Narges Shahidi, Tao Gong and Ricky Benitez.
US Patent Application 2020 (for Google LLC).

Bounds for list-decoding and list-recovery of random linear codes
Venkat Guruswami, Ray Li, Jonathan Moshieff, Nicolas Resch, Shashwat Silas, Mary Wootters.
arXiv: 2004.13247 | RANDOM 2020.

LDPC codes achieve list decoding capacity
Jonathan Moshieff, Nicolas Resch, Noga Ron-Zewi, Shashwat Silas, Mary Wootters.
arXiv: 1909.06430 | FOCS 2020.
Invited to the FOCS 2020 special issue of SICOMP.
Mary gave a talk about this work at The Institute of Advanced Study in November 2020: Talk.

On list recovery of high-rate tensor codes
Swastik Kopparty, Nicolas Resch, Noga Ron-Zewi, Shubhangi Saraf, Shashwat Silas.
ECCC: 2019/080 | IEEE Transactions on Information Theory.
A preliminary version of this work appeared in RANDOM 2019.

Load-balanced fractional repetition codes
Alexandra Porter, Shashwat Silas, Mary Wootters.
arXiv: 1802.00872 | ISIT 2018.

Weak compression and (in)security of rational proofs of storage
Ben Fisch, Shashwat Silas.
IACR: 2018/514 | Manuscript 2018.

Delta-connectivity in random lifts of graphs
Shashwat Silas
EJC | Electronic Journal of Combinatorics 2017.

Dedekind sums s(a,b) and inversions modulo b
Yiwang Chen, Nicholas Dunn, Campbell Hewett and Shashwat Silas.
arXiv:1411.4092 | International Journal of Number Theory 2015.

Theses

Threshold rates for error-correcting codes
PhD Thesis.
Advisor: Prof. Mary Wootters.
Thesis | Slides

Algebraic techniques for random covering graphs
Masters Thesis.
Advisor: Dr. Thomas Sauerwald
Winner of the best Masters thesis award, Cambridge Computer Laboratory
Thesis