____ __ ___
/ __ \__ ______ _____ / |/ /___ _____________ _______
/ /_/ / / / / __ `/ __ \ / /|_/ / __ `/ ___/ ___/ / / / ___/
/ _, _/ /_/ / /_/ / / / / / / / / /_/ / / / /__/ /_/ (__ )
/_/ |_|\__, /\__,_/_/ /_/ /_/ /_/\__,_/_/ \___/\__,_/____/
/____/
___ __ ___
/ _ \__ _____ ____ / |/ /__ ___________ _____
/ , _/ // / _ `/ _ \ / /|_/ / _ `/ __/ __/ // (_-<
/_/|_|\_, /\_,_/_//_/ /_/ /_/\_,_/_/ \__/\_,_/___/
/___/
___ __ ___
/ _ \/ |/ /__ ___________ _____
/ , _/ /|_/ / _ `/ __/ __/ // (_-<
/_/|_/_/ /_/\_,_/_/ \__/\_,_/___/
About Me
I'm currently a CS postdoc researcher at MIT under the supervision of Tim Kraska.
I research applications of machine learning to both traditional and cloud databases.
MIT
Postdoc
April 2019 - present
Google
Ph.D. intern
Summer 2018
Microsoft Research
Ph.D. intern
Summer 2017
HPE Vertica
Software engineer
2016 - 2017
Los Alamos National Lab
HPC software engineer
2007 - 2015
Brandeis University
CS Ph.D. student
2014 - 2019
University of Arizona
Undergraduate
2010 - 2014
Featured Publications
- Benchmaring Learned Indexes
- Ryan Marcus
- Andreas Kipf
- Alexander Van Renen
- Mihail Stoian
- Sanchit Misra
- Alfons Kemper
- Thomas Neumann
- Tim Kraska
VLDB '21 (pdf)
- Neo: A Learned Query Optimizer
- Ryan Marcus
- Parimarjan Negi
- Hongzi Mao
- Chi Zhang
- Mohammad Alizadeh
- Tim Kraska
- Olga Papaemmanouil
- Nesime Tatbul
VLDB '19 (pdf)
Blog Posts
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Machine learning for systems 06 Jun 2019
A recent groundswell of research has been pushing machine learning into computer systems
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Good comment, bad comment 05 Nov 2018
A few collected tips on writing readable code
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Overflow in consistent hashing 14 Sep 2018
Exploring the implications of fixed-capacity machines in consistent hashing schemes
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Pretty pictures with perlin noise fields 04 Mar 2018
Procedurally generated flurry-like graphics and videos with particle tracing in a Perlin noise field
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Computer-generated lines with a human feel 23 Oct 2017
Computers can create lines that look hand drawn
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The often-overlooked random forest kernel 04 Oct 2017
Random forest models can be used to measure the similarity between datapoints. This allows random forests to be used as very effective kernel functions
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No, really, what's a monad? 14 Dec 2016
My attempt at the infamous monad tutorial. Explains the concepts of monads using concrete examples in C++, Python, Java, and JavaScript
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The personal website and blog of Ryan Marcus, a postdoc at MIT CSAIL. I research applications of machine learning to both traditional and cloud databases.