PhD, Stanford University
shashwat — at — alumni — dot — stanford — dot — edu
I work at Google on projects/research related to distributed storage and SSD reliability. Previously, I did a PhD at Stanford University where I was advised by Prof. Mary Wootters. Part of my PhD was funded by a Google Graduate Fellowship in the School of Engineering.
My primary interests are combinatorics, error-correcting codes and applications of them to real world problems.
Outside of Math/CS, I love cooking, playing tennis, and learning about wine.
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.
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.
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.
Real-time oblivious erasure correction with linear time decoding and constant feedback
Shashwat Silas.
arXiv: 2101.11136
| ISIT 2021.
Finalist
for the IEEE Jack Keil Wolf Student Paper Award.
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.
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
| RANDOM 2019.
Load-balanced fractional repetition codes
Alexandra Porter, Shashwat Silas, Mary Wootters.
arXiv: 1802.00872
| ISIT 2018.
Sharp threshold rates for random codes
Venkat Guruswami, Jonathan Moshieff, Nicolas Resch, Shashwat Silas, Mary Wootters.
arXiv: 2009.04553
| Submitted.
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
| Submitted.
LDPC codes achieve list decoding capacity
Jonathan Moshieff, Nicolas Resch, Noga Ron-Zewi, Shashwat Silas, Mary Wootters.
arXiv: 1909.06430
| Submitted to FOCS 2020 special issue of SICOMP.
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 2021.
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.
Flash translation layer design using reinforcement learning
Shashwat Silas, Narges Shahidi, Tao Gong and Ricky Benitez.
US Patent Application 2020 (for Google LLC).
Weak compression and (in)security of rational proofs of storage
Ben Fisch, Shashwat Silas.
IACR: 2018/514
| Manuscript 2018.
Threshold rates for error-correcting codes
PhD Thesis.
Advisor: Prof. Mary Wootters.
Thesis | Slides
Algebraic techniques for random covering graphs Masters Thesis. Winner of the best Masters thesis award, Cambridge Computer Laboratory Advisor: Dr. Thomas Sauerwald Thesis
