Hi! I’m Alana Marzoev.

I’m the co-founder and CEO of Readyset, a data infrastructure startup that is helping developers build performant data-driven applications effortlessly. We’ve raised $30M to date and are backed by Index Ventures, Amplify Partners, and Sequoia Capital.

I love supporting technical founders and actively angel invest in early stage cloud infrastructure and AI startups. If you’re interested in chatting, don’t hesitate to drop me a line.

Background

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Before starting Readyset, I was a computer science PhD student at MIT, where I was supported by a Jacobs Presidential Fellowship. During my time there, I thought about the future of data systems, including exploring novel architectures as well as how to democratize data access through machine learning.

Before MIT, I was an undergraduate at Cornell University, where I explored the implications of resource disaggregation in the cloud,  investigated the effects of low precision arithmetic and variance reduction on the performance and hardware efficiency of stochastic gradient descent (SGD), and led a team of 50+ engineers in designing and building a fully-functional prototype of a Hyperloop pod. 

My other past experiences include working on:

Publications

I stopped conducting research in 2020 to focus on building Readyset. Some of my past publications include:

Unnatural Language Processing: Bridging the Gap Between Synthetic and Natural Language Data
Alana Marzoev, Samuel Madden, Frans Kaashoek, Michael Cafarella, Jacob Andreas
Preprint

Towards Multiverse Databases
Alana Marzoev, Lara Timbó Araújo, Malte Schwarzkopf, Samyukta Yagati, Eddie Kohler, Robert Morris, M. Frans Kaashoek, Sam Madden
HotOS 2019

High Accuracy SGD Using Low-Precision Arithmetic and Variance Reduction (for Linear Models)
Alana Marzoev, Christopher De Sa
SysML 2018.