Jay Mardia

About Me:

I am a PhD student in Electrical Engineering at Stanford University [since September 2017] and am grateful to have been supported by a Stanford Graduate Fellowship [2017-2020].

I am advised by Tsachy (Itschak) Weissman and Greg Valiant, and have also had the singular pleasure of working with Mary Wootters.

Before this, I received a B. Tech in EE from IIT-Bombay [also in 2017].

I am broadly interested in algorithms, high-dimensional statistics and information theory, and mostly enjoy thinking about the interplay between 'information' and 'computation'.

Here are some other things I like doing in my spare time.

Theoretical works:

  • Is the space complexity of planted clique recovery the same as that of detection? [arxiv] [8 min talk] [25 min talk] [Innovations in Theoretical Computer Science 2021]
    Jay Mardia

  • Finding Planted Cliques in Sublinear Time [arxiv]
    Jay Mardia, Hilal Asi, Kabir Aladin Chandrasekher

  • Concentration Inequalities for the Empirical Distribution of Discrete Distributions : Beyond the Method of Types [arxiv] [Information and Inference 2019]
    Jay Mardia, Jiantao Jiao, Ervin Tánczos, Robert D. Nowak, Tsachy Weissman

  • Repairing Multiple Failures for Scalar MDS Codes [arxiv] [IEEE Transactions on Information Theory 2018] (Part of a line of work excellently presented in this [talk] by Mary Wootters)
    Jay Mardia, Burak Bartan, Mary Wootters

Experimental works:

  • Overcoming high nanopore basecaller error rates for DNA storage via basecaller-decoder integration and convolutional codes [biorxiv] [GitHub] [ICASSP 2020]
    Shubham Chandak, Joachim Neu, Kedar Tatwawadi, Jay Mardia, Billy Lau, Matthew Kubit, Reyna Hulett, Peter Griffin, Mary Wootters, Tsachy Weissman, Hanlee Ji

  • Improved read/write cost tradeoff in DNA-based data storage using LDPC codes [biorxiv] [Allerton 2019] ([Slides], [poster], and [talk] by Shubham at ISMB / ECCB 2019)
    Shubham Chandak, Kedar Tatwawadi, Billy Lau, Jay Mardia, Matthew Kubit, Joachim Neu, Peter Griffin, Mary Wootters, Tsachy Weissman, Hanlee Ji

Course Projects:

  • Implementation and analysis of stabilizer codes in pyQuil [code] [report] (Spring 2019, CS269Q)
    Shubham Chandak, Jay Mardia, Meltem Tolunay
    Stabilizer codes form a large family of quantum error correcting codes that includes well-known codes such as the Shor code, Steane code, CSS codes and toric codes. In this work, we build a framework for encoding and decoding of general stabilizer codes on pyQuil and test specific single qubit codes with standard quantum noise models.

Professional Activities:

Reviewer: STOC 2021, ITW 2020, SODA 2021, ICASSP 2020, NeurIPS ITML 2019, IEEE Communications Letters, IEEE Transactions on Information Theory, ISIT 2018-20
Teaching: TA for CS 265 at Stanford during Autumn 2020

Contact: jmardia [at] stanford [dot] edu [?]